Optimal Dynamic Strategies for Index Tracking and Algorithmic Trading
Ward, Brian
In this thesis we study dynamic strategies for index tracking and algorithmic trading. Tracking problems have become ever more important in Financial Engineering as investors seek to precisely control their portfolio risks and exposures over different time horizons. This thesis analyzes various tracking problems and elucidates the tracking errors and strategies one can employ to minimize those errors and maximize profit. In Chapters 2 and 3, we study the empirical tracking properties of exchange traded funds (ETFs), leveraged ETFs (LETFs), and futures products related to spot gold and the Chicago Board Option Exchange (CBOE) Volatility Index (VIX), respectively. These two markets provide interesting and differing examples for understanding index tracking. We find that static strategies work well in the nonleveraged case for gold, but fail to track well in the corresponding leveraged case. For VIX, tracking via neither ETFs, nor futures\\ portfolios succeeds, even in the nonleveraged case. This motivates the need for dynamic strategies, some of which we construct in these two chapters and further expand on in Chapter 4. There, we analyze a framework for index tracking and risk exposure control through financial derivatives. We derive a tracking condition that restricts our exposure choices and also define a slippage process that characterizes the deviations from the index over longer horizons. The framework is applied to a number of models, for example, Black Scholes model and Heston model for equity index tracking, as well as the Square Root (SQR) model and the Concatenated Square Root (CSQR) model for VIX tracking. By specifying how each of these models fall into our framework, we are able to understand the tracking errors in each of these models. Finally, Chapter 5 analyzes a tracking problem of a different kind that arises in algorithmic trading: schedule following for optimal execution. We formulate and solve a stochastic control problem to obtain the optimal
Directory of Open Access Journals (Sweden)
Rafał Dreżewski
2018-05-01
Full Text Available In this paper, the evolutionary algorithm for the optimization of Forex market trading strategies is proposed. The introduction to issues related to the financial markets and the evolutionary algorithms precedes the main part of the paper, in which the proposed trading system is presented. The system uses the evolutionary algorithm for optimization of a parameterized greedy strategy, which is then used as an investment strategy on the Forex market. In the proposed system, a model of the Forex market was developed, including all elements that are necessary for simulating realistic trading processes. The proposed evolutionary algorithm contains several novel mechanisms that were introduced to optimize the greedy strategy. The most important of the proposed techniques are the mechanisms for maintaining the population diversity, a mechanism for protecting the best individuals in the population, the mechanisms preventing the excessive growth of the population, the mechanisms of the initialization of the population after moving the time window and a mechanism of choosing the best strategies used for trading. The experiments, conducted with the use of real-world Forex market data, were aimed at testing the quality of the results obtained using the proposed algorithm and comparing them with the results obtained by the buy-and-hold strategy. By comparing our results with the results of the buy-and-hold strategy, we attempted to verify the validity of the efficient market hypothesis. The credibility of the hypothesis would have more general implications for many different areas of our lives, including future sustainable development policies.
Trading strategies of corporate insiders
Klein, O.; Maug, E.; Schneider, Christoph
2017-01-01
We test two complementary theories of optimal trading strategies by analyzing the transaction patterns of corporate insiders. According to information-based theories, investors trade faster if they compete with others for exploiting the same information, while liquidity-based theories predict the
Multi-Period Trading via Convex Optimization
DEFF Research Database (Denmark)
Boyd, Stephen; Busseti, Enzo; Diamond, Steve
2017-01-01
We consider a basic model of multi-period trading, which can be used to evaluate the performance of a trading strategy. We describe a framework for single-period optimization, where the trades in each period are found by solving a convex optimization problem that trades oﬀ expected return, risk......, transaction cost and holding cost such as the borrowing cost for shorting assets. We then describe a multi-period version of the trading method, where optimization is used to plan a sequence of trades, with only the ﬁrst one executed, using estimates of future quantities that are unknown when the trades....... In this paper, we do not address a critical component in a trading algorithm, the predictions or forecasts of future quantities. The methods we describe in this paper can be thought of as good ways to exploit predictions, no matter how they are made. We have also developed a companion open-source software...
Optimal algorithmic trading and market microstructure
Labadie , Mauricio; Lehalle , Charles-Albert
2010-01-01
The efficient frontier is a core concept in Modern Portfolio Theory. Based on this idea, we will construct optimal trading curves for different types of portfolios. These curves correspond to the algorithmic trading strategies that minimize the expected transaction costs, i.e. the joint effect of market impact and market risk. We will study five portfolio trading strategies. For the first three (single-asset, general multi-asseet and balanced portfolios) we will assume that the underlyings fo...
Optimal strategy for a single-qubit gate and the trade-off between opposite types of decoherence
International Nuclear Information System (INIS)
Alicki, Robert; Horodecki, Michal; Horodecki, Ryszard; Horodecki, Pawel; Jacak, Lucjan; Machnikowski, Pawel
2004-01-01
We study reliable quantum-information processing (QIP) under two different types of environment. The first type is Markovian exponential decay, and the appropriate elementary strategy of protection of qubit is to apply fast gates. The second one is strongly non-Markovian and occurs solely during operations on the qubit. The best strategy is then to work with slow gates. If the two types are both present, one has to optimize the speed of gate. We show that such a trade-off is present for a single-qubit operation in a semiconductor quantum dot implementation of QIP, where recombination of exciton (qubit) is Markovian, while phonon dressing gives rise to the non-Markovian contribution
Optimal trading strategy for GenCo in LMP-based and bilateral ...
African Journals Online (AJOL)
GenCo) in multi-market environment including day-ahead spot and long term bilateral contract markets using self-organising hierarchical particle swarm optimisation with time-varying acceleration coefficients (SPSO-TVAC). The proposed trading ...
Optimal trading strategy for GenCo in LMP-based and bilateral ...
African Journals Online (AJOL)
cboonchu
GenCo) ... In Li and Shahidehpour (2005), a game-based bidding strategy for GenCos with ..... With the different demands, dispatched levels of GenCos vary as shown in Table 6. .... optimisation, AI applications to power systems, and power system ...
Optimal Trading with Alpha Predictors
Filippo Passerini; Samuel E. Vazquez
2015-01-01
We study the problem of optimal trading using general alpha predictors with linear costs and temporary impact. We do this within the framework of stochastic optimization with finite horizon using both limit and market orders. Consistently with other studies, we find that the presence of linear costs induces a no-trading zone when using market orders, and a corresponding market-making zone when using limit orders. We show that, when combining both market and limit orders, the problem is furthe...
Directory of Open Access Journals (Sweden)
Qiuzhuo Ma
2014-01-01
length of the decision duration period. The capacitated strategy is also discussed, in which different combinations of different decision intervals of different production rates are explicitly explored. The impact of various factors on the length of these intervals is qualitatively described. Through the sensitivity analysis, we further discuss the impact of product prices on the positions of the switch time points between the decision intervals. Company’s performance including profit and emission is numerically compared in the situation of joining or not joining the cap-and-trade system.
Optimal execution in high-frequency trading with Bayesian learning
Du, Bian; Zhu, Hongliang; Zhao, Jingdong
2016-11-01
We consider optimal trading strategies in which traders submit bid and ask quotes to maximize the expected quadratic utility of total terminal wealth in a limit order book. The trader's bid and ask quotes will be changed by the Poisson arrival of market orders. Meanwhile, the trader may update his estimate of other traders' target sizes and directions by Bayesian learning. The solution of optimal execution in the limit order book is a two-step procedure. First, we model an inactive trading with no limit order in the market. The dealer simply holds dollars and shares of stocks until terminal time. Second, he calibrates his bid and ask quotes to the limit order book. The optimal solutions are given by dynamic programming and in fact they are globally optimal. We also give numerical simulation to the value function and optimal quotes at the last part of the article.
Trade Liberalization and Optimal Environmental Policies in Vertical Related Markets
Directory of Open Access Journals (Sweden)
Yan-Shu Lin
2012-12-01
Full Text Available This paper establishes a symmetric two-country model with vertically related markets. In the downstream market, there is one firm in each country selling a homogeneous good, whose production generates pollution, to its home and the foreign markets a la Brander (1981. In the intermediate good market, there is also one upstream firm in each country, supplying the intermediate good only to its own country’s downstream market. The upstream firms can choose either price or quantity to maximize their profits. With this setting, the paper examines the optimal environmental policy and how it is affected by the tariff on the final good. It is found that, under free trade, the optimal final-good output with imperfect intermediate-good market will have the same output level as that with perfect intermediate-good market after imposing the optimal emission tax. The optimal environmental tax is smaller and the optimal environmental policy is less likely to be a green strategy under trade liberalization if the market structure in the intermediate good market is imperfect than perfect competition. On the other hand, the optimal environmental tax is necessarily higher if the upstream firm chooses price than quantity. Moreover, the optimal environmental policy is less likely to be a green strategy under trade liberalization if the upstream firms choose quantity than price to maximize their profits.
Trade Intelligence and Contemporary Exports Strategy
Directory of Open Access Journals (Sweden)
M. Tayfun Gülle
2013-11-01
Full Text Available The book mainly focuses on the divergences in the competitive environment resulting from the entrance of information and communications technologies into commercial life. Denoting that these divergences are rooted, above all, in the differences among countries in historical, social and geographic terms, the book claims that the increased use of trade information combined with these divergences will facilitate obtaining results in trade and that the synergy to emerge will pave the way for trade intelligence. The book also underlines that such trade intelligence, which is actually the natural commercial manner of Turkish entrepreneurs, could be accepted as the Turkish Style in international trade, with the rational management of the export process, and that this would ferment the national competition intelligence, as the strategy of contemporary exports.
Optimal trading strategies—a time series approach
Bebbington, Peter A.; Kühn, Reimer
2016-05-01
Motivated by recent advances in the spectral theory of auto-covariance matrices, we are led to revisit a reformulation of Markowitz’ mean-variance portfolio optimization approach in the time domain. In its simplest incarnation it applies to a single traded asset and allows an optimal trading strategy to be found which—for a given return—is minimally exposed to market price fluctuations. The model is initially investigated for a range of synthetic price processes, taken to be either second order stationary, or to exhibit second order stationary increments. Attention is paid to consequences of estimating auto-covariance matrices from small finite samples, and auto-covariance matrix cleaning strategies to mitigate against these are investigated. Finally we apply our framework to real world data.
Optimal GENCO bidding strategy
Gao, Feng
Electricity industries worldwide are undergoing a period of profound upheaval. The conventional vertically integrated mechanism is being replaced by a competitive market environment. Generation companies have incentives to apply novel technologies to lower production costs, for example: Combined Cycle units. Economic dispatch with Combined Cycle units becomes a non-convex optimization problem, which is difficult if not impossible to solve by conventional methods. Several techniques are proposed here: Mixed Integer Linear Programming, a hybrid method, as well as Evolutionary Algorithms. Evolutionary Algorithms share a common mechanism, stochastic searching per generation. The stochastic property makes evolutionary algorithms robust and adaptive enough to solve a non-convex optimization problem. This research implements GA, EP, and PS algorithms for economic dispatch with Combined Cycle units, and makes a comparison with classical Mixed Integer Linear Programming. The electricity market equilibrium model not only helps Independent System Operator/Regulator analyze market performance and market power, but also provides Market Participants the ability to build optimal bidding strategies based on Microeconomics analysis. Supply Function Equilibrium (SFE) is attractive compared to traditional models. This research identifies a proper SFE model, which can be applied to a multiple period situation. The equilibrium condition using discrete time optimal control is then developed for fuel resource constraints. Finally, the research discusses the issues of multiple equilibria and mixed strategies, which are caused by the transmission network. Additionally, an advantage of the proposed model for merchant transmission planning is discussed. A market simulator is a valuable training and evaluation tool to assist sellers, buyers, and regulators to understand market performance and make better decisions. A traditional optimization model may not be enough to consider the distributed
Optimal intermittent search strategies
International Nuclear Information System (INIS)
Rojo, F; Budde, C E; Wio, H S
2009-01-01
We study the search kinetics of a single fixed target by a set of searchers performing an intermittent random walk, jumping between different internal states. Exploiting concepts of multi-state and continuous-time random walks we have calculated the survival probability of a target up to time t, and have 'optimized' (minimized) it with regard to the transition probability among internal states. Our model shows that intermittent strategies always improve target detection, even for simple diffusion states of motion
Bubbles, shocks and elementary technical trading strategies
Fry, John
2014-01-01
In this paper we provide a unifying framework for a set of seemingly disparate models for bubbles, shocks and elementary technical trading strategies in financial markets. Markets operate by balancing intrinsic levels of risk and return. This seemingly simple observation is commonly over-looked by academics and practitioners alike. Our model shares its origins in statistical physics with others. However, under our approach, changes in market regime can be explicitly shown to represent a phase transition from random to deterministic behaviour in prices. This structure leads to an improved physical and econometric model. We develop models for bubbles, shocks and elementary technical trading strategies. The list of empirical applications is both interesting and topical and includes real-estate bubbles and the on-going Eurozone crisis. We close by comparing the results of our model with purely qualitative findings from the finance literature.
Optimal fuel inventory strategies
International Nuclear Information System (INIS)
Caspary, P.J.; Hollibaugh, J.B.; Licklider, P.L.; Patel, K.P.
1990-01-01
In an effort to maintain their competitive edge, most utilities are reevaluating many of their conventional practices and policies in an effort to further minimize customer revenue requirements without sacrificing system reliability. Over the past several years, Illinois Power has been rethinking its traditional fuel inventory strategies, recognizing that coal supplies are competitive and plentiful and that carrying charges on inventory are expensive. To help the Company achieve one of its strategic corporate goals, an optimal fuel inventory study was performed for its five major coal-fired generating stations. The purpose of this paper is to briefly describe Illinois Power's system and past practices concerning coal inventories, highlight the analytical process behind the optimal fuel inventory study, and discuss some of the recent experiences affecting coal deliveries and economic dispatch
Optimal intermittent search strategies
Energy Technology Data Exchange (ETDEWEB)
Rojo, F; Budde, C E [FaMAF, Universidad Nacional de Cordoba, Ciudad Universitaria, X5000HUA Cordoba (Argentina); Wio, H S [Instituto de Fisica de Cantabria, Universidad de Cantabria and CSIC E-39005 Santander (Spain)
2009-03-27
We study the search kinetics of a single fixed target by a set of searchers performing an intermittent random walk, jumping between different internal states. Exploiting concepts of multi-state and continuous-time random walks we have calculated the survival probability of a target up to time t, and have 'optimized' (minimized) it with regard to the transition probability among internal states. Our model shows that intermittent strategies always improve target detection, even for simple diffusion states of motion.
Economically optimized electricity trade modeling. Iran-Turkey case
International Nuclear Information System (INIS)
Shakouri G, H.; Eghlimi, M.; Manzoor, D.
2009-01-01
The advantages of power trade between countries, which are attainable for various facts, are distinguished now. Daily differences in the peak-load times of neighboring countries commonly occur for differences in the longitudes of their location. Seasonal differences are also caused by differences in the latitudes leading to different climates. Consequently, different load curves help to have such a production schedule that reduces blackouts and investments for power generation by planning for a proper trade between countries in a region. This paper firstly describes the methodology and framework for the power trade and then the results of an optimal power trade model between Iran and Turkey, which shows a potential benefit for both countries by peak shaving, are presented. The results, in the worst case design, represent optimality of about 1500 MW electricity export from Iran to Turkey at the Turkish peak times, as well as 447 MW electricity import from Turkey at the Iranian peak times. In addition, results derived from running a Long-Run model show that there will be greater potential for power export from Iran to Turkey, which is a guideline of an energy conservation strategy for both countries in the future. (author)
Derivative Trade Optimizing Model Utilizing GP Based on Behavioral Finance Theory
Matsumura, Koki; Kawamoto, Masaru
This paper proposed a new technique which makes the strategy trees for the derivative (option) trading investment decision based on the behavioral finance theory and optimizes it using evolutionary computation, in order to achieve high profitability. The strategy tree uses a technical analysis based on a statistical, experienced technique for the investment decision. The trading model is represented by various technical indexes, and the strategy tree is optimized by the genetic programming(GP) which is one of the evolutionary computations. Moreover, this paper proposed a method using the prospect theory based on the behavioral finance theory to set psychological bias for profit and deficit and attempted to select the appropriate strike price of option for the higher investment efficiency. As a result, this technique produced a good result and found the effectiveness of this trading model by the optimized dealings strategy.
Implementing optimal thinning strategies
Kurt H. Riitters; J. Douglas Brodie
1984-01-01
Optimal thinning regimes for achieving several management objectives were derived from two stand-growth simulators by dynamic programming. Residual mean tree volumes were then plotted against stand density management diagrams. The results supported the use of density management diagrams for comparing, checking, and implementing the results of optimization analyses....
Optimal trading based on ideal coordination
International Nuclear Information System (INIS)
Egeland, H.
1992-01-01
The author places more emphasis on the technical than on the economical aspects of trading with electric power. Calculation models which can be used to study this trade taking place under the influence of unequal preconditions in Denmark, Finland, Norway and Sweden are presented. It is suggested that trade between these countries is currently satisfactory and should be further developed. The advantages of standard contracts are mentioned. Forms of exchange of, for example, technology know-how between these Nordic countries in the process of connecting their distribution systems etc. would be most advantageous. (AB)
Optimizing decommissioning strategies
International Nuclear Information System (INIS)
Passant, F.H.
1993-01-01
Many different approaches can be considered for achieving satisfactory decommissioning of nuclear installations. These can embrace several different engineering actions at several stages, with time variations between the stages. Multi-attribute analysis can be used to help in the decision making process and to establish the optimum strategy. It has been used in the Usa and the UK to help in selecting preferred sites for radioactive waste repositories, and also in UK to help with the choice of preferred sites for locating PWR stations, and in selecting optimum decommissioning strategies
Formation of trading strategy based on technical analysis and application in the FOREX market
Butkus, Mindaugas; Tamašauskas, Mantas
2016-01-01
This paper accomplishes modification of technical analysis based trading strategy for the FOREX market. New strategy performance was checked using historical data. Most profitable modification was excluded and optimized. Straipsnyje atliktas technine analize grįstos prekybos strategijos, skirtos FOREX rinkai, modifikavimas. Naujos strategijos veikimas patikrintas su istoriniais duomenimis. Buvo atrinkta ir optimizuota pelningiausia modifikacija.
International Nuclear Information System (INIS)
Chen, C.Y.; Shih, L.H.
1992-01-01
Recently, the main power company in Taiwan has shifted the primary energy resource from oil to coal and tried to diversify the coal supply from various sources. The company wants to have the imported coal meet the environmental standards and operation requirements as well as to have high heating value. In order to achieve these objectives, establishment of a coal blending system for Taiwan is necessary. A mathematical model using mixed integer programming technique is used to model the import strategy and the blending system. 6 refs., 1 tab
Trade and Industrial Policy Strategies (TIPS) Core Grant - Phase IV ...
International Development Research Centre (IDRC) Digital Library (Canada)
Established in 1996, Trade and Industrial Policy Strategies (TIPS) is an organization that coordinates a network of researchers that seeks to provide the Government of South Africa, civil society and the region with independent advice on economic policy, with a particular focus on trade and industrial issues. Earlier phases of ...
Optimal trading quantity integration as a basis for optimal portfolio management
Directory of Open Access Journals (Sweden)
Saša Žiković
2005-06-01
Full Text Available The author in this paper points out the reason behind calculating and using optimal trading quantity in conjunction with Markowitz’s Modern portfolio theory. In the opening part the author presents an example of calculating optimal weights using Markowitz’s Mean-Variance approach, followed by an explanation of basic logic behind optimal trading quantity. The use of optimal trading quantity is not limited to systems with Bernoulli outcome, but can also be used when trading shares, futures, options etc. Optimal trading quantity points out two often-overlooked axioms: (1 a system with negative mathematical expectancy can never be transformed in a system with positive mathematical expectancy, (2 by missing the optimal trading quantity an investor can turn a system with positive expectancy into a negative one. Optimal trading quantity is that quantity which maximizes geometric mean (growth function of a particular system. To determine the optimal trading quantity for simpler systems, with a very limited number of outcomes, a set of Kelly’s formulas is appropriate. In the conclusion the summary of the paper is presented.
Trade and Industrial Policy Strategies (TIPS) - Phase III | IDRC ...
International Development Research Centre (IDRC) Digital Library (Canada)
Trade and Industrial Policy Strategies (TIPS) is an network of researchers ... bring the quality of research done locally closer to international best practice. ... the Real Economy Study and a program of work on the economics of education.
Looker, Gerard
2015-01-01
This thesis considers the role of union full time officers in union organising strategies. Two decades of promoting union organising influenced by models developed by the AFL-CIO, has failed to arrest the decline of UK trade unions let alone produce evidence of renewal. Focusing mainly on one region in the UKs largest public sector trade union, Unison, the research provides for a detailed account of how organising strategies affect union work, presenting thick and deep data from full time off...
Switching strategies to optimize search
International Nuclear Information System (INIS)
Shlesinger, Michael F
2016-01-01
Search strategies are explored when the search time is fixed, success is probabilistic and the estimate for success can diminish with time if there is not a successful result. Under the time constraint the problem is to find the optimal time to switch a search strategy or search location. Several variables are taken into account, including cost, gain, rate of success if a target is present and the probability that a target is present. (paper: interdisciplinary statistical mechanics)
Optimal Strategy and Business Models
DEFF Research Database (Denmark)
Johnson, Peter; Foss, Nicolai Juul
2016-01-01
This study picks up on earlier suggestions that control theory may further the study of strategy. Strategy can be formally interpreted as an idealized path optimizing heterogeneous resource deployment to produce maximum financial gain. Using standard matrix methods to describe the firm Hamiltonia...... variable of firm path, suggesting in turn that the firm's business model is the codification of the application of investment resources used to control the strategic path of value realization....
International Nuclear Information System (INIS)
2001-01-01
There is growing interest everywhere in the topic of emissions trading in order to meet the commitments made under the Kyoto Protocol. During this conference, most aspects of emissions trading were discussed, ranging from the need to establish credible emission reduction estimates to the means of achieving those goals, to the trading activities of Ontario Power Generation in the field of emissions trading both at the domestic and the international level. There were presentations that focussed on greenhouse gas policies, markets and strategic plays, and the preparation for the regulation of greenhouse gas. An emissions trading regime for Canada was examined by one of the presenters. This conference provided a useful venue for all stakeholders to discuss various strategies and ideas related to emissions trading. Speakers represented governments, the private sector and utilities, as well as the National Round Table on the Environment and the Economy. tabs., figs
Optimal Initial Public O¤ering design with aftermarket trading.
Fabrice Rousseau; Sarah Parlane
2009-01-01
We characterize the optimal pricing and allocation of shares in the presence of distinct adverse selection problems. Some investors have private information at the time of the IPO and sell their shares in the after-market upon facing liquidity needs. Others learn their private interest in the after-market, and sell their shares strategically. The optimal mechanism trades-o¤ informational rents and rents to strategic traders. Flipping facilitates truthful information revelation. When liquidity...
Forecasting stock market averages to enhance profitable trading strategies
Haefke, Christian; Helmenstein, Christian
1995-01-01
In this paper we design a simple trading strategy to exploit the hypothesized distinct informational content of the arithmetic and geometric mean. The rejection of cointegration between the two stock market indicators supports this conjecture. The profits generated by this cheaply replicable trading scheme cannot be expected to persist. Therefore we forecast the averages using autoregressive linear and neural network models to gain a competitive advantage relative to other investors. Refining...
Study on Electricity Purchase Optimization in Coordination of Electricity and Carbon Trading
Liu, Dunnan; Meng, Yaru; Zhang, Shuo
2017-07-01
With the establishment of carbon emissions trading market in China, the power industry has become an important part of the market participants. The power grid enterprises need to optimize their own strategies in the new environment of electricity market and carbon market coordination. First, the influence of electricity and carbon trading coordination on electricity purchase strategy for grid enterprises was analysed in the paper. Then a power purchase optimization model was presented, which used the minimum cost of low carbon, energy saving and environment protection as the goal, the power generation capacity, installed capacity and pollutant emission as the constraints. Finally, a provincial power grid was taken as an example to analyse the model, and the optimization order of power purchase was obtained, which provided a new idea for the low carbon development of power grid enterprises.
Trade liberalization and tax reform strategies: The case of the Korean oil industry
International Nuclear Information System (INIS)
Shim, Kieun; Jung, Yonghun
2012-01-01
The decline in government revenues due to tariff reductions has become a major concern for most developing countries, including Korea. This paper focuses on the Korean oil industry to examine which post-trade liberalization tax reform strategy is optimal, depending on the government's priority between social welfare and government revenue. We find that the important factors for choosing an optimal tax reform policy are price elasticity of demand and market competition. Based on a price-inelastic demand and the low competitive market for Korea's oil industry, if the goal of a tax reform policy is to increase social welfare, the recommended strategy is to raise the consumption tax by a scale of less than the sum of tariff cuts times the crude oil price and oil import tax cuts. This strategy would also reduce inflation, but it could be detrimental to government revenue. However, if the policy's goal is the preservation of government revenue, the recommended strategy is to raise the consumption tax by a scale equal to the sum of tariff cuts times the crude oil price at the pre-tax reform and oil import tax cuts. This strategy does not change either government revenue or social welfare. - Highlights: ▶ Which post-trade liberalization tax reform is optimal for Korea's oil industry? ▶ Both final and intermediate markets are modeled under imperfect competition. ▶ Both price elasticity and market competition are important for an optimal tax reform. ▶ The optimal tax reform depends on the priority between welfare and government revenue.
Trading Strategies for Distribution Company with Stochastic Distributed Energy Resources
DEFF Research Database (Denmark)
Zhang, Chunyu; Wang, Qi; Wang, Jianhui
2016-01-01
This paper proposes a methodology to address the trading strategies of a proactive distribution company (PDISCO) engaged in the transmission-level (TL) markets. A one-leader multi-follower bilevel model is presented to formulate the gaming framework between the PDISCO and markets. The lower...
Trade and Industrial Policy Strategies (TIPS) Core Grant - Phase IV ...
International Development Research Centre (IDRC) Digital Library (Canada)
Established in 1996, Trade and Industrial Policy Strategies (TIPS) is an organization that coordinates a network of researchers that seeks to provide the Government of ... International Water Resources Association, in close collaboration with IDRC, is holding a webinar titled “Climate change and adaptive water management: ...
Persuasive and Politeness Strategies in Chinese Foreign Trade
Institute of Scientific and Technical Information of China (English)
张芳芳
2013-01-01
During international trade negotiations Chinese salespersons tend to employ a variety of persuasive and politeness strat⁃egies in marketing their products. Persuasion involves face-threatening acts (FTAs), thus politeness strategies which are applied to reduce face-threatening are combined with persuasive communication. This paper, taking Brown and Levinson’s model of po⁃liteness as a reference, makes an analysis on politeness strategies used in persuasive communication of the salespersons.
ASEAN’s Preferential Trade Agreements (PTA Strategy
Directory of Open Access Journals (Sweden)
Guanyi Leu
2011-01-01
Full Text Available This paper provides a diversification explanation in order understand the development of PTAs in Southeast Asia. I argue that an important reason why ASEAN states participate in PTAs has been to diversify existing trade ties and to reduce overdependence on a narrow range of export markets. Southeast Asian countries have formed PTAs with markets with which they had weak or unexplored economic relations, as demonstrated by three case analyses: the ASEAN Free Trade Area (AFTA, the ASEAN-China Free Trade Agreement (ACFTA and the ASEAN-Japan Comprehensive Economic Partnership Agreement (AJCEP. To maximise the economic gains and the diversification effects of PTA participation, ASEAN countries have pursued a strategy of strengthening economic unity while keeping external economic linkages as diversified as possible. Although East Asia, and especially China, was an important alternative market to reduce ASEAN’s dependence on trade with America, ASEAN countries have also pursued PTAs with a number of other trading partners. This paper explains how PTAs have helped ASEAN states to develop more policy autonomy in their trading environment.
Fricke, Daniel
2012-12-01
We analyze the correlations in patterns of trading for members of the Italian interbank trading platform e-MID. The trading strategy of a particular member institution is defined as the sequence of (intra-) daily net trading volumes within a certain semester. Based on this definition, we show that there are significant and persistent bilateral correlations between institutions’ trading strategies. In most semesters we find two clusters, with positively (negatively) correlated trading strategies within (between) clusters. We show that the two clusters mostly contain continuous net buyers and net sellers of money, respectively, and that cluster memberships of individual banks are highly persistent. Additionally, we highlight some problems related to our definition of trading strategies. Our findings add further evidence on the fact that preferential lending relationships on the micro-level lead to community structure on the macro-level.
Real-Time Trading Strategies of Proactive DISCO with Heterogeneous DG Owners
DEFF Research Database (Denmark)
Zhang, Chunyu; Wang, Qi; Wang, Jianhui
2017-01-01
This paper presents a methodology to obtain the optimal trading strategies between the proactive distribution company (PDISCO), heterogeneous distributed generation owners (DGOs) and wholesale market in a real-time trading framework. In this framework, the PDISCO’s decisions cover the power...... procurements from DGOs and the transactions within the real-time market. A one-leader multi-follower-type bilevel model is proposed to embody the PDISCO-DGO gaming structure. The upper-level (UL) problem is to maximize the PDISCO’s profit, while the lower-level (LL) problem indicates the profit maximization...... the effectiveness and scalability of the proposed model....
Carry trade as a speculative investment strategy in Serbia
Directory of Open Access Journals (Sweden)
Bungin Sanja
2012-12-01
Full Text Available This paper is analyses causes and the consequences of a speculative investment carry trade strategy in the exchange market in Serbia. The presence of such type of investor is related to high yields of risk free securities denominated in dinars, as well as the perception of future movements of dinar exchange rate related to currency that serves as source of investment. The consequences of carry trade may significantly influence exchange rate movements when monetary policy has limited facilities to combat negative and sudden shocks.
Korea’s Trade Strategies for Mega Free Trade Agreements in Regional and Global Economic Integration
Directory of Open Access Journals (Sweden)
Sang-Chul Park
2016-12-01
Full Text Available Korea has developed rapidly since the 1960s. It is one of the four Asian tiger economies and a good model for developing countries. Korea shows the world how a developing country can develop its economy rapidly and become industrialized. Its development strategy has mainly been an export-oriented trade policy. As a result, its trade volume grew from $1 billion in 1966 to $1 trillion in 2011, which is a 1,000-fold increase within five decades. Since 2011, Korea has become one of seven countries with a trade volume over $1 trillion. However, the Korean economy has experienced turbulence as well as positive growth. It underwent severe economic crises such as the Asian financial crisis in 1997 and the global financial crisis in 2008. Its economy has been extremely vulnerable to the external economic environment, although it has improved and strengthened, particularly since the global financial crisis. During those two crises, the government carried out an appropriate trade policy with a strategic approach to upgrade its industrial structure and competitiveness in global markets. This article comprehensively discusses Korean trade policy and strategy over the last five decades, and how its national economy has developed rapidly. It also explores how the government sets its strategic targets in Asia and the Asia Pacific region. It considers two mega free trade agreements (FTAs — the Regional Comprehensive Economic Partnership and the Trans-Pacific Partnership — as new opportunities for further development. Therefore, it is wise to analyze these regional mega FTAs in order to maximize the national interest.
Evolution strategies for robust optimization
Kruisselbrink, Johannes Willem
2012-01-01
Real-world (black-box) optimization problems often involve various types of uncertainties and noise emerging in different parts of the optimization problem. When this is not accounted for, optimization may fail or may yield solutions that are optimal in the classical strict notion of optimality, but
Watershed-based point sources permitting strategy and dynamic permit-trading analysis.
Ning, Shu-Kuang; Chang, Ni-Bin
2007-09-01
Permit-trading policy in a total maximum daily load (TMDL) program may provide an additional avenue to produce environmental benefit, which closely approximates what would be achieved through a command and control approach, with relatively lower costs. One of the important considerations that might affect the effective trading mechanism is to determine the dynamic transaction prices and trading ratios in response to seasonal changes of assimilative capacity in the river. Advanced studies associated with multi-temporal spatially varied trading ratios among point sources to manage water pollution hold considerable potential for industries and policy makers alike. This paper aims to present an integrated simulation and optimization analysis for generating spatially varied trading ratios and evaluating seasonal transaction prices accordingly. It is designed to configure a permit-trading structure basin-wide and provide decision makers with a wealth of cost-effective, technology-oriented, risk-informed, and community-based management strategies. The case study, seamlessly integrating a QUAL2E simulation model with an optimal waste load allocation (WLA) scheme in a designated TMDL study area, helps understand the complexity of varying environmental resources values over space and time. The pollutants of concern in this region, which are eligible for trading, mainly include both biochemical oxygen demand (BOD) and ammonia-nitrogen (NH3-N). The problem solution, as a consequence, suggests an array of waste load reduction targets in a well-defined WLA scheme and exhibits a dynamic permit-trading framework among different sub-watersheds in the study area. Research findings gained in this paper may extend to any transferable dynamic-discharge permit (TDDP) program worldwide.
Trade and Industrial Policy Strategies (TIPS) - phase III | CRDI ...
International Development Research Centre (IDRC) Digital Library (Canada)
Établi en 1996, le réseau de chercheurs de l'organisme Trade and Industrial Policy Strategies (TIPS) souhaite fournir au gouvernement de l'Afrique du Sud, à la société civile et à la région des conseils impartiaux en matière de politiques économiques, particulièrement celles portant sur les questions commerciales et ...
Delay-area trade-off for MPRM circuits based on hybrid discrete particle swarm optimization
International Nuclear Information System (INIS)
Jiang Zhidi; Wang Zhenhai; Wang Pengjun
2013-01-01
Polarity optimization for mixed polarity Reed—Muller (MPRM) circuits is a combinatorial issue. Based on the study on discrete particle swarm optimization (DPSO) and mixed polarity, the corresponding relation between particle and mixed polarity is established, and the delay-area trade-off of large-scale MPRM circuits is proposed. Firstly, mutation operation and elitist strategy in genetic algorithm are incorporated into DPSO to further develop a hybrid DPSO (HDPSO). Then the best polarity for delay and area trade-off is searched for large-scale MPRM circuits by combining the HDPSO and a delay estimation model. Finally, the proposed algorithm is testified by MCNC Benchmarks. Experimental results show that HDPSO achieves a better convergence than DPSO in terms of search capability for large-scale MPRM circuits. (semiconductor integrated circuits)
An internet graph model based on trade-off optimization
Alvarez-Hamelin, J. I.; Schabanel, N.
2004-03-01
This paper presents a new model for the Internet graph (AS graph) based on the concept of heuristic trade-off optimization, introduced by Fabrikant, Koutsoupias and Papadimitriou in[CITE] to grow a random tree with a heavily tailed degree distribution. We propose here a generalization of this approach to generate a general graph, as a candidate for modeling the Internet. We present the results of our simulations and an analysis of the standard parameters measured in our model, compared with measurements from the physical Internet graph.
Determining an optimal supply chain strategy
Directory of Open Access Journals (Sweden)
Intaher M. Ambe
2012-11-01
Full Text Available In today’s business environment, many companies want to become efficient and flexible, but have struggled, in part, because they have not been able to formulate optimal supply chain strategies. Often this is as a result of insufficient knowledge about the costs involved in maintaining supply chains and the impact of the supply chain on their operations. Hence, these companies find it difficult to manufacture at a competitive cost and respond quickly and reliably to market demand. Mismatched strategies are the root cause of the problems that plague supply chains, and supply-chain strategies based on a one-size-fits-all strategy often fail. The purpose of this article is to suggest instruments to determine an optimal supply chain strategy. This article, which is conceptual in nature, provides a review of current supply chain strategies and suggests a framework for determining an optimal strategy.
An Algoritm for the Alocation Optimization of Trading Executions
Directory of Open Access Journals (Sweden)
Claudiu Vinte
2006-02-01
Full Text Available In this paper, I wish to propose the Integer Allocation employing Tabu Search in conjunction with Simulated Annealing Heuristics for optimizing the distribution of trading executions in investors’ accounts. There is no polynomial algorithm discovered for Integer Linear Programming (a problem which is NP-complete. Generally, the practical experience shows that large-scale integer linear programs seem as yet practically unsolvable or extremely time-consuming. The algorithm described herein proposes an alternative approach to the problem. The algorithm consists of three steps: allocate the total executed quantity proportionally on the accounts, based on the allocation instructions (pro-rata basis; construct an initial solution, distributing the executed prices; improve the solution iteratively, employing Tabu Search in conjunction with Simulated Annealing heuristics.
Optimal management strategies in variable environments: Stochastic optimal control methods
Williams, B.K.
1985-01-01
Dynamic optimization was used to investigate the optimal defoliation of salt desert shrubs in north-western Utah. Management was formulated in the context of optimal stochastic control theory, with objective functions composed of discounted or time-averaged biomass yields. Climatic variability and community patterns of salt desert shrublands make the application of stochastic optimal control both feasible and necessary. A primary production model was used to simulate shrub responses and harvest yields under a variety of climatic regimes and defoliation patterns. The simulation results then were used in an optimization model to determine optimal defoliation strategies. The latter model encodes an algorithm for finite state, finite action, infinite discrete time horizon Markov decision processes. Three questions were addressed: (i) What effect do changes in weather patterns have on optimal management strategies? (ii) What effect does the discounting of future returns have? (iii) How do the optimal strategies perform relative to certain fixed defoliation strategies? An analysis was performed for the three shrub species, winterfat (Ceratoides lanata), shadscale (Atriplex confertifolia) and big sagebrush (Artemisia tridentata). In general, the results indicate substantial differences among species in optimal control strategies, which are associated with differences in physiological and morphological characteristics. Optimal policies for big sagebrush varied less with variation in climate, reserve levels and discount rates than did either shadscale or winterfat. This was attributed primarily to the overwintering of photosynthetically active tissue and to metabolic activity early in the growing season. Optimal defoliation of shadscale and winterfat generally was more responsive to differences in plant vigor and climate, reflecting the sensitivity of these species to utilization and replenishment of carbohydrate reserves. Similarities could be seen in the influence of both
Using trading strategies to detect phase transitions in financial markets.
Forró, Z; Woodard, R; Sornette, D
2015-04-01
We show that the log-periodic power law singularity model (LPPLS), a mathematical embodiment of positive feedbacks between agents and of their hierarchical dynamical organization, has a significant predictive power in financial markets. We find that LPPLS-based strategies significantly outperform the randomized ones and that they are robust with respect to a large selection of assets and time periods. The dynamics of prices thus markedly deviate from randomness in certain pockets of predictability that can be associated with bubble market regimes. Our hybrid approach, marrying finance with the trading strategies, and critical phenomena with LPPLS, demonstrates that targeting information related to phase transitions enables the forecast of financial bubbles and crashes punctuating the dynamics of prices.
Using trading strategies to detect phase transitions in financial markets
Forró, Z.; Woodard, R.; Sornette, D.
2015-04-01
We show that the log-periodic power law singularity model (LPPLS), a mathematical embodiment of positive feedbacks between agents and of their hierarchical dynamical organization, has a significant predictive power in financial markets. We find that LPPLS-based strategies significantly outperform the randomized ones and that they are robust with respect to a large selection of assets and time periods. The dynamics of prices thus markedly deviate from randomness in certain pockets of predictability that can be associated with bubble market regimes. Our hybrid approach, marrying finance with the trading strategies, and critical phenomena with LPPLS, demonstrates that targeting information related to phase transitions enables the forecast of financial bubbles and crashes punctuating the dynamics of prices.
Mathematics, Pricing, Market Risk Management and Trading Strategies for Financial Derivatives (2/3)
CERN. Geneva; Coffey, Brian
2009-01-01
Market Trading and Risk Management of Vanilla FX Options - Measures of Market Risk - Implied Volatility - FX Risk Reversals, FX Strangles - Valuation and Risk Calculations - Risk Management - Market Trading Strategies
Emissions trading and firms' strategies. The case of power producers
International Nuclear Information System (INIS)
Rousse, O.
2005-11-01
This thesis deals with the impacts of a domestic emissions trading scheme on firms' strategies. As recent experiences of such programs (Acid Rain Program, RECLAIM Program, NOx Budget Program and the European Union Emissions Trading Scheme) concern mainly heat and power producers, we analyze especially strategies of these companies. In context of electricity market deregulation, our study takes two directions: uncertainty and competitive distortions. Concerning uncertainty, we are interested in portfolio management of emission permits, that is choice under uncertainty between buying, selling and banking permits. Concerning competitive distortions, we consider manipulations on the permits and/or products markets. Among others, we investigate interactions between a pollution market and the wholesale electricity market. From a general point of view, we show that a permits market, even competitive, gives to power producers more opportunities to act strategically on wholesale electricity markets. By this way, our study attempts to indicate when these market distortions are more likely to occur and to give some emissions market design instructions. (author)
Optimization strategies in complex systems
Bussolari, L.; Contucci, P.; Giardinà, C.; Giberti, C.; Unguendoli, F.; Vernia, C.
2003-01-01
We consider a class of combinatorial optimization problems that emerge in a variety of domains among which: condensed matter physics, theory of financial risks, error correcting codes in information transmissions, molecular and protein conformation, image restoration. We show the performances of two
Optimal Advance Selling Strategy under Price Commitment
Chenhang Zeng
2012-01-01
This paper considers a two-period model with experienced consumers and inexperienced consumers. The retailer determines both advance selling price and regular selling price at the beginning of the first period. I show that advance selling weekly dominates no advance selling, and the optimal advance selling price may be at a discount, at a premium or at the regular selling price. To help the retailer choose the optimal pricing strategy, conditions for each possible advance selling strategy to ...
Growth or reproduction: emergence of an evolutionary optimal strategy
International Nuclear Information System (INIS)
Grilli, J; Suweis, S; Maritan, A
2013-01-01
Modern ecology has re-emphasized the need for a quantitative understanding of the original ‘survival of the fittest theme’ based on analysis of the intricate trade-offs between competing evolutionary strategies that characterize the evolution of life. This is key to the understanding of species coexistence and ecosystem diversity under the omnipresent constraint of limited resources. In this work we propose an agent-based model replicating a community of interacting individuals, e.g. plants in a forest, where all are competing for the same finite amount of resources and each competitor is characterized by a specific growth–reproduction strategy. We show that such an evolution dynamics drives the system towards a stationary state characterized by an emergent optimal strategy, which in turn depends on the amount of available resources the ecosystem can rely on. We find that the share of resources used by individuals is power-law distributed with an exponent directly related to the optimal strategy. The model can be further generalized to devise optimal strategies in social and economical interacting systems dynamics. (paper)
Tank Waste Remediation System optimized processing strategy
International Nuclear Information System (INIS)
Slaathaug, E.J.; Boldt, A.L.; Boomer, K.D.; Galbraith, J.D.; Leach, C.E.; Waldo, T.L.
1996-03-01
This report provides an alternative strategy evolved from the current Hanford Site Tank Waste Remediation System (TWRS) programmatic baseline for accomplishing the treatment and disposal of the Hanford Site tank wastes. This optimized processing strategy performs the major elements of the TWRS Program, but modifies the deployment of selected treatment technologies to reduce the program cost. The present program for development of waste retrieval, pretreatment, and vitrification technologies continues, but the optimized processing strategy reuses a single facility to accomplish the separations/low-activity waste (LAW) vitrification and the high-level waste (HLW) vitrification processes sequentially, thereby eliminating the need for a separate HLW vitrification facility
Trading strategies for distribution company with stochastic distributed energy resources
Energy Technology Data Exchange (ETDEWEB)
Zhang, Chunyu; Wang, Qi; Wang, Jianhui; Korpås, Magnus; Pinson, Pierre; Østergaard, Jacob; Khodayar, Mohammad E.
2016-09-01
This paper proposes a methodology to address the trading strategies of a proactive distribution company (PDISCO) engaged in the transmission-level (TL) markets. A one-leader multi-follower bilevel model is presented to formulate the gaming framework between the PDISCO and markets. The lower-level (LL) problems include the TL day-ahead market and scenario-based real-time markets, respectively with the objectives of maximizing social welfare and minimizing operation cost. The upper-level (UL) problem is to maximize the PDISCO’s profit across these markets. The PDISCO’s strategic offers/bids interactively influence the outcomes of each market. Since the LL problems are linear and convex, while the UL problem is non-linear and non-convex, an equivalent primal–dual approach is used to reformulate this bilevel model to a solvable mathematical program with equilibrium constraints (MPEC). The effectiveness of the proposed model is verified by case studies.
Trading Strategies for Distribution Company with Stochastic Distributed Energy Resources
DEFF Research Database (Denmark)
Zhang, Chunyu; Wang, Qi; Wang, Jianhui
2016-01-01
This paper proposes a methodology to address the trading strategies of a proactive distribution company (PDISCO) engaged in the transmission-level (TL) markets. A one-leader multi-follower bilevel model is presented to formulate the gaming framework between the PDISCO and markets. The lower......-level (LL) problems include the TL day-ahead market and scenario-based real-time markets, respectively with the objectives of maximizing social welfare and minimizing operation cost. The upper-level (UL) problem is to maximize the PDISCO's prot across these markets. The PDISCO's strategic oers....../bids interactively in uence the outcomes of each market. Since the LL problems are linear and convex, while the UL problem is non-linear and non-convex, an equivalent primal-dual approach is used to reformulate this bilevel model to a solvable mathematical program with equilibrium constraints (MPEC...
The Strategies of Tofu and Fermented Soybean Cake Cooperation in Facing China-Asean Free Trade
Directory of Open Access Journals (Sweden)
Rusdarti Rusdarti
2015-12-01
Full Text Available This research was aimed to identify the internal and external factor for encountering free trade China-Asean and to find some strategic model alternative that can be applied by Primkopti Semarang to develop their business. The analysis methods used were descriptive analysis method and SWOT analysis. The result of this research showed that internal factors for cooperation’s strength for encountering free trade including soybean distributor in form of cooperation in Semarang and experienced manager to carry out the business. The weakness one was the research and development of cooperation hasn’t been optimal and the management of information system hasn’t worked well. External factors for opportunity one including the soybean buyer or main customer was cooperation members having dual identity, as for the threat including no resistance for new competitor, increasing soybean import, soybean importer has strong bargain position. Compatible strategy for cooperation implementation in encountering free trade China-Asean was market penetration strategy and product development.
Zhang, J L; Li, Y P; Huang, G H; Baetz, B W; Liu, J
2017-06-01
In this study, a Bayesian estimation-based simulation-optimization modeling approach (BESMA) is developed for identifying effluent trading strategies. BESMA incorporates nutrient fate modeling with soil and water assessment tool (SWAT), Bayesian estimation, and probabilistic-possibilistic interval programming with fuzzy random coefficients (PPI-FRC) within a general framework. Based on the water quality protocols provided by SWAT, posterior distributions of parameters can be analyzed through Bayesian estimation; stochastic characteristic of nutrient loading can be investigated which provides the inputs for the decision making. PPI-FRC can address multiple uncertainties in the form of intervals with fuzzy random boundaries and the associated system risk through incorporating the concept of possibility and necessity measures. The possibility and necessity measures are suitable for optimistic and pessimistic decision making, respectively. BESMA is applied to a real case of effluent trading planning in the Xiangxihe watershed, China. A number of decision alternatives can be obtained under different trading ratios and treatment rates. The results can not only facilitate identification of optimal effluent-trading schemes, but also gain insight into the effects of trading ratio and treatment rate on decision making. The results also reveal that decision maker's preference towards risk would affect decision alternatives on trading scheme as well as system benefit. Compared with the conventional optimization methods, it is proved that BESMA is advantageous in (i) dealing with multiple uncertainties associated with randomness and fuzziness in effluent-trading planning within a multi-source, multi-reach and multi-period context; (ii) reflecting uncertainties existing in nutrient transport behaviors to improve the accuracy in water quality prediction; and (iii) supporting pessimistic and optimistic decision making for effluent trading as well as promoting diversity of decision
Optimal control of anthracnose using mixed strategies.
Fotsa Mbogne, David Jaures; Thron, Christopher
2015-11-01
In this paper we propose and study a spatial diffusion model for the control of anthracnose disease in a bounded domain. The model is a generalization of the one previously developed in [15]. We use the model to simulate two different types of control strategies against anthracnose disease. Strategies that employ chemical fungicides are modeled using a continuous control function; while strategies that rely on cultivational practices (such as pruning and removal of mummified fruits) are modeled with a control function which is discrete in time (though not in space). For comparative purposes, we perform our analyses for a spatially-averaged model as well as the space-dependent diffusion model. Under weak smoothness conditions on parameters we demonstrate the well-posedness of both models by verifying existence and uniqueness of the solution for the growth inhibition rate for given initial conditions. We also show that the set [0, 1] is positively invariant. We first study control by impulsive strategies, then analyze the simultaneous use of mixed continuous and pulse strategies. In each case we specify a cost functional to be minimized, and we demonstrate the existence of optimal control strategies. In the case of pulse-only strategies, we provide explicit algorithms for finding the optimal control strategies for both the spatially-averaged model and the space-dependent model. We verify the algorithms for both models via simulation, and discuss properties of the optimal solutions. Copyright © 2015 Elsevier Inc. All rights reserved.
MARKET-MAKING STRATEGY IN THE SYSTEM OF ALGORITHMIC HIGH-FREQUENCY TRADING
Directory of Open Access Journals (Sweden)
A. V. Toropov
2014-01-01
Full Text Available Market maker is the most important participant of modern exchange trading, it provides the increase of market liquidity and reduces the difference between bid and ask (spread. The paper presents automatic market-making strategy for quoting of options and other kinds of financial instruments on electronic markets. Quotes are based on theoretical pricing which is a resource-intensive task. Presented algorithmic optimizations, in particular quotes caching and smoothing of underlying asset price oscillation, give the possibility up to four times boost for quote modify scenario on real market data. Mechanism of quotes caching precalculates quotes in certain diapason around current underlying price. If underlying price changes within the diapason, algorithm sends already filled message for quote modification, instead of new complex computation. Smoothing of underlying asset price oscillation prevents permanent moving of the diapason and reacts only on significant market moving. A size of caching diapason which provides optimal correlation between speed of quotes modification and resource consumption has been defined experimentally (40 elements. In case of quoting 36 options on Eurex Exchange an average delay between underlying price change and quote modification is 277 usec. The measurements were carried out on the Sun X4170 M3: CPU(s: 2xXeon 2.9GHz RAM: 128 GB server under Solaris 10 operating system. Obtained results correspond to modern market-making requirements. The developed strategy is used by big European banks and trading firms.
Optimal Pricing Strategy in Marketing Research Consulting.
Chang, Chun-Hao; Lee, Chi-Wen Jevons
1994-01-01
This paper studies the optimal pricing scheme for a monopolistic marketing research consultant who sells high-cost proprietary marketing information to her oligopolistic clients in the manufacturing industry. In designing an optimal pricing strategy, the consultant needs to fully consider the behavior of her clients, the behavior of the existing and potential competitors to her clients, and the behavior of her clients' customers. The authors show how the environment uncertainty, the capabilit...
Optimal Deterministic Investment Strategies for Insurers
Directory of Open Access Journals (Sweden)
Ulrich Rieder
2013-11-01
Full Text Available We consider an insurance company whose risk reserve is given by a Brownian motion with drift and which is able to invest the money into a Black–Scholes financial market. As optimization criteria, we treat mean-variance problems, problems with other risk measures, exponential utility and the probability of ruin. Following recent research, we assume that investment strategies have to be deterministic. This leads to deterministic control problems, which are quite easy to solve. Moreover, it turns out that there are some interesting links between the optimal investment strategies of these problems. Finally, we also show that this approach works in the Lévy process framework.
Transitions in optimal adaptive strategies for populations in fluctuating environments
Mayer, Andreas; Mora, Thierry; Rivoire, Olivier; Walczak, Aleksandra M.
2017-09-01
Biological populations are subject to fluctuating environmental conditions. Different adaptive strategies can allow them to cope with these fluctuations: specialization to one particular environmental condition, adoption of a generalist phenotype that compromises between conditions, or population-wise diversification (bet hedging). Which strategy provides the largest selective advantage in the long run depends on the range of accessible phenotypes and the statistics of the environmental fluctuations. Here, we analyze this problem in a simple mathematical model of population growth. First, we review and extend a graphical method to identify the nature of the optimal strategy when the environmental fluctuations are uncorrelated. Temporal correlations in environmental fluctuations open up new strategies that rely on memory but are mathematically challenging to study: We present analytical results to address this challenge. We illustrate our general approach by analyzing optimal adaptive strategies in the presence of trade-offs that constrain the range of accessible phenotypes. Our results extend several previous studies and have applications to a variety of biological phenomena, from antibiotic resistance in bacteria to immune responses in vertebrates.
Dynamic optimal strategies in transboundary pollution game under learning by doing
Chang, Shuhua; Qin, Weihua; Wang, Xinyu
2018-01-01
In this paper, we present a transboundary pollution game, in which emission permits trading and pollution abatement costs under learning by doing are considered. In this model, the abatement cost mainly depends on the level of pollution abatement and the experience of using pollution abatement technology. We use optimal control theory to investigate the optimal emission paths and the optimal pollution abatement strategies under cooperative and noncooperative games, respectively. Additionally, the effects of parameters on the results have been examined.
Optimization strategies for complex engineering applications
Energy Technology Data Exchange (ETDEWEB)
Eldred, M.S.
1998-02-01
LDRD research activities have focused on increasing the robustness and efficiency of optimization studies for computationally complex engineering problems. Engineering applications can be characterized by extreme computational expense, lack of gradient information, discrete parameters, non-converging simulations, and nonsmooth, multimodal, and discontinuous response variations. Guided by these challenges, the LDRD research activities have developed application-specific techniques, fundamental optimization algorithms, multilevel hybrid and sequential approximate optimization strategies, parallel processing approaches, and automatic differentiation and adjoint augmentation methods. This report surveys these activities and summarizes the key findings and recommendations.
Stochastic Optimal Wind Power Bidding Strategy in Short-Term Electricity Market
DEFF Research Database (Denmark)
Hu, Weihao; Chen, Zhe; Bak-Jensen, Birgitte
2012-01-01
Due to the fluctuating nature and non-perfect forecast of the wind power, the wind power owners are penalized for the imbalance costs of the regulation, when they trade wind power in the short-term liberalized electricity market. Therefore, in this paper a formulation of an imbalance cost...... minimization problem for trading wind power in the short-term electricity market is described, to help the wind power owners optimize their bidding strategy. Stochastic optimization and a Monte Carlo method are adopted to find the optimal bidding strategy for trading wind power in the short-term electricity...... market in order to deal with the uncertainty of the regulation price, the activated regulation of the power system and the forecasted wind power generation. The Danish short-term electricity market and a wind farm in western Denmark are chosen as study cases due to the high wind power penetration here...
Trading strategies for distribution company with stochastic distributed energy resources
International Nuclear Information System (INIS)
Zhang, Chunyu; Wang, Qi; Wang, Jianhui; Korpås, Magnus; Pinson, Pierre; Østergaard, Jacob; Khodayar, Mohammad E.
2016-01-01
Highlights: • A market framework is presented for a proactive DISCO (PDISCO). • Two-stage wholesale markets and stochastic distributed energy resources are involved. • A one-leader multi-follower bilevel model is proposed. • Continuous strategic offers and bids are achieved. - Abstract: This paper proposes a methodology to address the trading strategies of a proactive distribution company (PDISCO) engaged in the transmission-level (TL) markets. A one-leader multi-follower bilevel model is presented to formulate the gaming framework between the PDISCO and markets. The lower-level (LL) problems include the TL day-ahead market and scenario-based real-time markets, respectively with the objectives of maximizing social welfare and minimizing operation cost. The upper-level (UL) problem is to maximize the PDISCO’s profit across these markets. The PDISCO’s strategic offers/bids interactively influence the outcomes of each market. Since the LL problems are linear and convex, while the UL problem is non-linear and non-convex, an equivalent primal–dual approach is used to reformulate this bilevel model to a solvable mathematical program with equilibrium constraints (MPEC). The effectiveness of the proposed model is verified by case studies.
DEFF Research Database (Denmark)
Hansen, Kåre
2000-01-01
This paper examines differences in exhibitors who participate at international trade shows at joint booths and those who participate at individual booths. The structure, strategy, and trade show performance of exhibitors at joint booths and those at individual booths are analysed. The analysis...... implications for exhibitors at interna-tional trade shows and export marketing programmes and other marketing programmes offering services to international trade show exhibitors....... of exhibitors at the international food shows SIAL (Paris) and ANUGA (Cologne) showed several significant differences with regard to structure and strategy. However, no significant differences in the performance assessments between the two partici-pation modes were found. The findings have important...
Mixed integer evolution strategies for parameter optimization.
Li, Rui; Emmerich, Michael T M; Eggermont, Jeroen; Bäck, Thomas; Schütz, M; Dijkstra, J; Reiber, J H C
2013-01-01
Evolution strategies (ESs) are powerful probabilistic search and optimization algorithms gleaned from biological evolution theory. They have been successfully applied to a wide range of real world applications. The modern ESs are mainly designed for solving continuous parameter optimization problems. Their ability to adapt the parameters of the multivariate normal distribution used for mutation during the optimization run makes them well suited for this domain. In this article we describe and study mixed integer evolution strategies (MIES), which are natural extensions of ES for mixed integer optimization problems. MIES can deal with parameter vectors consisting not only of continuous variables but also with nominal discrete and integer variables. Following the design principles of the canonical evolution strategies, they use specialized mutation operators tailored for the aforementioned mixed parameter classes. For each type of variable, the choice of mutation operators is governed by a natural metric for this variable type, maximal entropy, and symmetry considerations. All distributions used for mutation can be controlled in their shape by means of scaling parameters, allowing self-adaptation to be implemented. After introducing and motivating the conceptual design of the MIES, we study the optimality of the self-adaptation of step sizes and mutation rates on a generalized (weighted) sphere model. Moreover, we prove global convergence of the MIES on a very general class of problems. The remainder of the article is devoted to performance studies on artificial landscapes (barrier functions and mixed integer NK landscapes), and a case study in the optimization of medical image analysis systems. In addition, we show that with proper constraint handling techniques, MIES can also be applied to classical mixed integer nonlinear programming problems.
Parallel strategy for optimal learning in perceptrons
International Nuclear Information System (INIS)
Neirotti, J P
2010-01-01
We developed a parallel strategy for learning optimally specific realizable rules by perceptrons, in an online learning scenario. Our result is a generalization of the Caticha-Kinouchi (CK) algorithm developed for learning a perceptron with a synaptic vector drawn from a uniform distribution over the N-dimensional sphere, so called the typical case. Our method outperforms the CK algorithm in almost all possible situations, failing only in a denumerable set of cases. The algorithm is optimal in the sense that it saturates Bayesian bounds when it succeeds.
The Optimal Nash Equilibrium Strategies Under Competition
Institute of Scientific and Technical Information of China (English)
孟力; 王崇喜; 汪定伟; 张爱玲
2004-01-01
This paper presented a game theoretic model to study the competition for a single investment oppertunity under uncertainty. It models the hazard rate of investment as a function of competitors' trigger level. Under uncertainty and different information structure, the option and game theory was applied to researching the optimal Nash equilibrium strategies of one or more firm. By means of Matlab software, the paper simulates a real estate developing project example and illustrates how parameter affects investment strategies. The paper's work will contribute to the present investment practice in China.
Tsao, Jung-Hsuan; Tung, Ching-Pin; Liu, Tzu-Ming
2014-05-01
Climate change will increase sharp risks to the water and food supply in coming decades. Although impact assessment and adaptation evaluation has been discussed a lot in recent years, the importance of adaptation implement should not be ignored. In Taiwan, and elsewhere, fallow is an option of adaptation strategy under climate change. Fallow would improve the water scarcity of domestic use, but the food security might be threatened. The trade-off effects of adaptation actions are just like the side effects of medicine which cannot be avoided. Thus, managing water resources with an integrated approach will be urgent. This study aims to establish a cross-sectoral framework for implementation the trade-off adaptation strategy. Not only fallow, but also other trade-off strategy like increasing the percentage of national grain self-sufficiency would be analyzed by a rational decision process. The recent percentage of grain self-sufficiency in Taiwan is around 32, which was decreasing from 53 thirty years ago. Yet, the goal of increasing grain self-sufficiency means much more water must be used in agriculture. In that way, domestic users may face the water shortage situation. Considering the conflicts between water supply and food security, the concepts from integrative negotiation are appropriate to apply. The implementation of trade-off adaptation strategies needs to start by quantifying the utility of water supply and food security were be quantified. Next, each side's bottom line can be found by BATNA (Best Alternative to a Negotiated Agreement) and ZOPA (Zone of Possible Agreement). ZOPA provides the entire possible outcomes, and BATNA ensures the efficiency of adaptation actions by moving along with Pareto frontier. Therefore, the optimal percentage of fallow and grain self-sufficiency can be determined. Furthermore, BATNA also provides the pathway step by step which can be a guideline of adaptation strategies. This framework allows analysts and stakeholder to
Optimized Strategies for Detecting Extrasolar Space Weather
Hallinan, Gregg
2018-06-01
Fully understanding the implications of space weather for the young solar system, as well as the wider population of planet-hosting stars, requires remote sensing of space weather in other stellar systems. Solar coronal mass ejections can be accompanied by bright radio bursts at low frequencies (typically measurement of the magnetic field strength of the planet, informing on whether the atmosphere of the planet can survive the intense magnetic activity of its host star. However, both stellar and planetary radio emission are highly variable and optimal strategies for detection of these emissions requires the capability to monitor 1000s of nearby stellar/planetary systems simultaneously. I will discuss optimized strategies for both ground and space-based experiments to take advantage of the highly variable nature of the radio emissions powered by extrasolar space weather to enable detection of stellar CMEs and planetary magnetospheres.
Optimization of pocket machining strategy in HSM
Msaddek, El Bechir; Bouaziz, Zoubeir; Dessein, Gilles; Baili, Maher
2012-01-01
International audience; Our two major concerns, which should be taken into consideration as soon as we start the selecting the machining parameters, are the minimization of the machining time and the maintaining of the high-speed machining machine in good state. The manufacturing strategy is one of the parameters which practically influences the time of the different geometrical forms manufacturing, as well as the machine itself. In this article, we propose an optimization methodology of the ...
Optimal strategies for pricing general insurance
Emms, P.; Haberman, S.; Savoulli, I.
2006-01-01
Optimal premium pricing policies in a competitive insurance environment are investigated using approximation methods and simulation of sample paths. The market average premium is modelled as a diffusion process, with the premium as the control function and the maximization of the expected total utility of wealth, over a finite time horizon, as the objective. In order to simplify the optimisation problem, a linear utility function is considered and two particular premium strategies are adopted...
An advanced Lithium-ion battery optimal charging strategy based on a coupled thermoelectric model
International Nuclear Information System (INIS)
Liu, Kailong; Li, Kang; Yang, Zhile; Zhang, Cheng; Deng, Jing
2017-01-01
Lithium-ion batteries are widely adopted as the power supplies for electric vehicles. A key but challenging issue is to achieve optimal battery charging, while taking into account of various constraints for safe, efficient and reliable operation. In this paper, a triple-objective function is first formulated for battery charging based on a coupled thermoelectric model. An advanced optimal charging strategy is then proposed to develop the optimal constant-current-constant-voltage (CCCV) charge current profile, which gives the best trade-off among three conflicting but important objectives for battery management. To be specific, a coupled thermoelectric battery model is first presented. Then, a specific triple-objective function consisting of three objectives, namely charging time, energy loss, and temperature rise (both the interior and surface), is proposed. Heuristic methods such as Teaching-learning-based-optimization (TLBO) and particle swarm optimization (PSO) are applied to optimize the triple-objective function, and their optimization performances are compared. The impacts of the weights for different terms in the objective function are then assessed. Experimental results show that the proposed optimal charging strategy is capable of offering desirable effective optimal charging current profiles and a proper trade-off among the conflicting objectives. Further, the proposed optimal charging strategy can be easily extended to other battery types.
Technical Analysis in Forex : A Strategy for Individual Trader in Intra-Day Trading
Linden, Miikka
2009-01-01
The goal of the thesis was to create a simple and profitable strategy for Foreign Exchange Market (forex) currency trading. Forex is an interesting international market, which is becom-ing globally more and more popular. The author has a strong interest in forex and he had no-ticed how many trading strategies are very complicated and difficult to use. The meaning was to study what kind of simple trading strategy would be profitable in forex. The target of the study was intra-day traders, who ...
Directory of Open Access Journals (Sweden)
Teplova T. V.
2014-06-01
Full Text Available Momentum-effect has many interpretations in the practice of investing and in understanding of anomalies in asset prices. We consider a Cross-Sectional momentum effects and the corresponding two medium-term (3 months or more trading strategies that are different from the trend following rules for individual assets. We tested four hypothesis deals with cross-sectional momentum effect on the Russian stock market and the possibility of building a self-financing (long-short trading strategy at three time horizon (stock market growth from 2004 until mid 2008, financial crisis and post-crisis periods. It is shown that for the Russian market cross-sectional momentum strategy with partly rebalanced portfolio maximizing portfolio return (134 stocks listed from 2004 to 2014 in the few Russian stock exchanges should be based on the three-month formation period and three-month holding period periods (3/1/3. We have identified elements of profit-maximizing momentum strategy: three time windows and determinants of assets. Monthly average return of arbitrage strategy is estimated at 1.5 % for 134 common shares. Implementation of the strategy for the post-crisis period does not allow to maximize profit. For 6-month and more investment windows it gets the advantage of reverse strategy (opening long positions in stocks with low investment results and short position for assets with high relative returns. Fundamental parameters of the issuer (size of companies like market capitalization and two measures of liquidity (trading activity and transaction costs like bid-ask spread are significant to maximize portfolio performance (we prove the growth of monthly average return ranging from 1.5 to 2.5 %. We find that size and liquidity control momentum strategy can earn positive profits in Russian stock market, larger than naïve momentum.
Directory of Open Access Journals (Sweden)
Anders Buch
2015-01-01
Full Text Available The ambition of this paper is to analyze the discursive practices of three Danish trade unions for professional and managerial staff as found in their strategy and position papers. Using discourse analytic methods, the paper analyzes, discusses, and compares the strategy papers of the three unions in order to investigate how they problematize their roles and objectives. This investigation clarifies the discursive premises of the unions and it shows how these premises restrain and afford their agendas. The overall purpose of the paper is to investigate and describe the dominant logics and rationalities that shape the documents and to point to their limits and bounds. Through an archaeological investigation, the paper critically examines the implicit and tacit naturalizations made in the documents and reveals the ideological presuppositions of the discursive practices of the authors. The paper documents how “strategic management” has become an integral part of Danish trade unions practices and the paper sets out to discuss this trend in relation to the general neo-liberal decentering of the “social” and promotion of “community” as the locus of governance. Through examples from the practices of the Danish trade unions for professionals, the paper substantiates how new technologies of governance and the subjectification of union members as “customers” tend to transform the role of the trade unions from the position of “political actors” to “service providers” in the advanced liberal societies.
E. Borgonovo; PERCOCO M
2007-01-01
This work discusses the Sensitivity Analysis (SA) of portfolio volatility ( σ_{p}) and its role in the interpretation of trading/reallocation strategies. Starting from recent findings in the SA field, we show that results obtained utilizing partial derivatives (PD) or Elasticity (E) cannot be applied to the analysis of the generic trading strategy. We show that such limitations can be overcome by making use of the Differential Importance Measure (D). We also show that, thanks to D additivity ...
Optimization Under Uncertainty for Wake Steering Strategies
Energy Technology Data Exchange (ETDEWEB)
Quick, Julian [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Annoni, Jennifer [National Renewable Energy Laboratory (NREL), Golden, CO (United States); King, Ryan N [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Dykes, Katherine L [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Fleming, Paul A [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ning, Andrew [Brigham Young University
2017-08-03
Offsetting turbines' yaw orientations from incoming wind is a powerful tool that may be leveraged to reduce undesirable wake effects on downstream turbines. First, we examine a simple two-turbine case to gain intuition as to how inflow direction uncertainty affects the optimal solution. The turbines are modeled with unidirectional inflow such that one turbine directly wakes the other, using ten rotor diameter spacing. We perform optimization under uncertainty (OUU) via a parameter sweep of the front turbine. The OUU solution generally prefers less steering. We then do this optimization for a 60-turbine wind farm with unidirectional inflow, varying the degree of inflow uncertainty and approaching this OUU problem by nesting a polynomial chaos expansion uncertainty quantification routine within an outer optimization. We examined how different levels of uncertainty in the inflow direction effect the ratio of the expected values of deterministic and OUU solutions for steering strategies in the large wind farm, assuming the directional uncertainty used to reach said OUU solution (this ratio is defined as the value of the stochastic solution or VSS).
Trade balance instability and the optimal exchange rate regime: The case of OPEC countries
Energy Technology Data Exchange (ETDEWEB)
Aljerrah, M.A.
1993-01-01
The OPEC members have experienced wide fluctuations in their trade balances. This can be attributed to several factors: (1) heavy dependence of national income and export earnings on a single primary export-oil; (2) instability of price and world demand for oil; and (3) the exchange rate regime practiced in recent years. An exchange rate policy can be used to minimize the fluctuations in trade balance, given the changes in exchange rates of major international currencies. The purpose of this study is two fold; first, examine the effects of fluctuations in trade balance on the OPEC economies, and second, propose appropriate exchange rate regime for selected OPEC members. The study is divided into two parts. The first part demonstrates the impact of trade balance changes on national income and other macroeconomic variables using a Keynesian framework. The second part involves using conventional trade models to search for the appropriate exchange rate regime to minimize the fluctuations in trade balance of each selective country. The study's findings are: first, fluctuations in trade balances had negative effects on the economics of Algeria, Kuwait, Libya, Saudi Arabia, and the United Arab Emirates. Second, the current exchange rate regime of no sample country is optimal in minimizing trade balance fluctuations. Third, in contrast to expectations, U.S. dollar peg did not stabilize the trade balance of any OPEC member. Finally, the results show that the sample OPEC economies could have enjoyed faster - though with different degree - economic growth if they had pegged their currencies to the derived optimal exchange rate regime. These optimal exchange rate regimes are: the SDR for Algeria and the United Arab Emirates, the purchasing power parity for Libya and Saudi Arabia, and the real Yen for Kuwait.
A Sequence Mining Method to Predict the Bidding Strategy of Trading Agents
Nikolaidou, Vivia; Mitkas, Pericles A.
In this work, we describe the process used in order to predict the bidding strategy of trading agents. This was done in the context of the Reverse TAC, or CAT, game of the Trading Agent Competition. In this game, a set of trading agents, buyers or sellers, are provided by the server and they trade their goods in one of the markets operated by the competing agents. Better knowledge of the strategy of the trading agents will allow a market maker to adapt its incentives and attract more agents to its own market. Our prediction was based on the time series of the traders’ past bids, taking into account the variation of each bid compared to its history. The results proved to be of satisfactory accuracy, both in the game’s context and when compared to other existing approaches.
Externalities, Border Trade and Illegal Production: An Optimal Tax Approach to Alcohol Policy
Aronsson, Thomas; Sjögren, Tomas
2005-01-01
This paper deals with optimal income and commodity taxation in an economy, where alcohol is an externality-generating consumption good. In our model, alcohol can be bought domestically, imported (via border trade) or produced illegally. Border trade implies an incentive to set the domestic alcohol tax below the marginal social damage of alcohol, and to tax (subsidize) commodities which are complementary with (substitutable for) alcohol. In addition, since leisure and alcohol consumption are g...
Crosbie, Eric; Eckford, Robert; Bialous, Stella
2018-04-21
To analyse the tobacco industry's strategy of using trade and investment agreements to prevent the global diffusion of standardised packaging (SP) of tobacco products. Review of tobacco industry documents, relevant government documents and media items. The data were triangulated and thematically analysed. Internal tobacco industry documents reveal that during the early 1990s, tobacco companies developed a multipronged trade strategy to prevent the global diffusion of progressive tobacco packaging and labelling proposals, including SP. This strategy consisted of (1) framing the health issue in terms of trade and investment, (2) detailing alleged legal violations concerning trade barriers, intellectual property and investment rights, (3) threatening legal suits and reputational damage, and (4) garnering third-party support. These efforts helped delay SP until 2010 when Australia became the first country to reintroduce SP proposals, followed by governments in the UK and New Zealand in 2012, Ireland in 2013 and France in 2014. Review of government documents and media sources in each of the five countries indicate the industry continues to employ this multipronged strategy throughout the SP policy's progression. Although this strategy is tailored towards each domestic context, the overall tobacco industry's trade strategy remains consistently focused on shifting the attention away from public health and towards the realm of trade and investment with more corporate-friendly allies. Governments seeking to implement SP need to be prepared to resist and counter the industry's multipronged trade strategy by avoiding trade diversions, exposing false industry legal and reputational claims, and monitoring third-party support. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Combined optimization model for sustainable energization strategy
Abtew, Mohammed Seid
Access to energy is a foundation to establish a positive impact on multiple aspects of human development. Both developed and developing countries have a common concern of achieving a sustainable energy supply to fuel economic growth and improve the quality of life with minimal environmental impacts. The Least Developing Countries (LDCs), however, have different economic, social, and energy systems. Prevalence of power outage, lack of access to electricity, structural dissimilarity between rural and urban regions, and traditional fuel dominance for cooking and the resultant health and environmental hazards are some of the distinguishing characteristics of these nations. Most energy planning models have been designed for developed countries' socio-economic demographics and have missed the opportunity to address special features of the poor countries. An improved mixed-integer programming energy-source optimization model is developed to address limitations associated with using current energy optimization models for LDCs, tackle development of the sustainable energization strategies, and ensure diversification and risk management provisions in the selected energy mix. The Model predicted a shift from traditional fuels reliant and weather vulnerable energy source mix to a least cost and reliable modern clean energy sources portfolio, a climb on the energy ladder, and scored multifaceted economic, social, and environmental benefits. At the same time, it represented a transition strategy that evolves to increasingly cleaner energy technologies with growth as opposed to an expensive solution that leapfrogs immediately to the cleanest possible, overreaching technologies.
Local Optimization Strategies in Urban Vehicular Mobility.
Directory of Open Access Journals (Sweden)
Pierpaolo Mastroianni
Full Text Available The comprehension of vehicular traffic in urban environments is crucial to achieve a good management of the complex processes arising from people collective motion. Even allowing for the great complexity of human beings, human behavior turns out to be subject to strong constraints--physical, environmental, social, economic--that induce the emergence of common patterns. The observation and understanding of those patterns is key to setup effective strategies to optimize the quality of life in cities while not frustrating the natural need for mobility. In this paper we focus on vehicular mobility with the aim to reveal the underlying patterns and uncover the human strategies determining them. To this end we analyze a large dataset of GPS vehicles tracks collected in the Rome (Italy district during a month. We demonstrate the existence of a local optimization of travel times that vehicle drivers perform while choosing their journey. This finding is mirrored by two additional important facts, i.e., the observation that the average vehicle velocity increases by increasing the travel length and the emergence of a universal scaling law for the distribution of travel times at fixed traveled length. A simple modeling scheme confirms this scenario opening the way to further predictions.
Kaburu, Stefano S K; Newton-Fisher, Nicholas E
2015-06-01
Across taxa, males employ a variety of mating strategies, including sexual coercion and the provision, or trading, of resources. Biological market theory (BMT) predicts that trading of commodities for mating opportunities should exist only when males cannot monopolize access to females and/or obtain mating by force, in situations where power differentials between males are low; both coercion and trading have been reported for chimpanzees ( Pan troglodytes ). Here, we investigate whether the choice of strategy depends on the variation in male power differentials, using data from two wild communities of East African chimpanzees ( Pan troglodytes schweinfurthii ): the structurally despotic Sonso community (Budongo, Uganda) and the structurally egalitarian M-group (Mahale, Tanzania). We found evidence of sexual coercion by male Sonso chimpanzees, and of trading-of grooming for mating-by M-group males; females traded sex for neither meat nor protection from male aggression. Our results suggest that the despotism-egalitarian axis influences strategy choice: male chimpanzees appear to pursue sexual coercion when power differentials are large and trading when power differentials are small and coercion consequently ineffective. Our findings demonstrate that trading and coercive strategies are not restricted to particular chimpanzee subspecies; instead, their occurrence is consistent with BMT predictions. Our study raises interesting, and as yet unanswered, questions regarding female chimpanzees' willingness to trade sex for grooming, if doing so represents a compromise to their fundamentally promiscuous mating strategy. It highlights the importance of within-species cross-group comparisons and the need for further study of the relationship between mating strategy and dominance steepness.
Diverging Trade Strategies in Latin America: An Analytical Framework
Aggarwal, Vinod K.; Espach, Ralph H.
2003-01-01
Although there is increasing divergence among the trade policies of various Latin American nations, overall the last twenty years have seen a dramatic shift away from protectionism towards liberalization. Focusing on case studies of four Latin American nations — Brazil, Mexico, Chile and Argentina — the authors use an analytical framework to explain the rationales behind divergent policies. The analytical approach used considers the combination of economic, political and strategic objectives ...
Analysis of intra-country virtual water trade strategy to alleviate water scarcity in Iran
Faramarzi, M.; Yang, H.; Mousavi, J.; Schulin, R.; Binder, C. R.; Abbaspour, K. C.
2010-08-01
Increasing water scarcity has posed a major constraint to sustain food production in many parts of the world. To study the situation at the regional level, we took Iran as an example and analyzed how an intra-country "virtual water trade strategy" (VWTS) may help improve cereal production as well as alleviate the water scarcity problem. This strategy calls, in part, for the adjustment of the structure of cropping pattern (ASCP) and interregional food trade where crop yield and crop water productivity as well as local economic and social conditions are taken into account. We constructed a systematic framework to assess ASCP at the provincial level under various driving forces and constraints. A mixed-integer, multi-objective, linear optimization model was developed and solved by linear programming. Data from 1990-2004 were used to account for yearly fluctuations of water availability and food production. Five scenarios were designed aimed at maximizing the national cereal production while meeting certain levels of wheat self-sufficiency under various water and land constraints in individual provinces. The results show that under the baseline scenario, which assumes a continuation of the existing water use and food policy at the national level, some ASCP scenarios could produce more wheat with less water. Based on different scenarios in ASCP, we calculated that 31% to 100% of the total wheat shortage in the deficit provinces could be supplied by the wheat surplus provinces. As a result, wheat deficit provinces would receive 3.5 billion m3 to 5.5 billion m3 of virtual water by importing wheat from surplus provinces.
Optimal allocation of trend following strategies
Grebenkov, Denis S.; Serror, Jeremy
2015-09-01
We consider a portfolio allocation problem for trend following (TF) strategies on multiple correlated assets. Under simplifying assumptions of a Gaussian market and linear TF strategies, we derive analytical formulas for the mean and variance of the portfolio return. We construct then the optimal portfolio that maximizes risk-adjusted return by accounting for inter-asset correlations. The dynamic allocation problem for n assets is shown to be equivalent to the classical static allocation problem for n2 virtual assets that include lead-lag corrections in positions of TF strategies. The respective roles of asset auto-correlations and inter-asset correlations are investigated in depth for the two-asset case and a sector model. In contrast to the principle of diversification suggesting to treat uncorrelated assets, we show that inter-asset correlations allow one to estimate apparent trends more reliably and to adjust the TF positions more efficiently. If properly accounted for, inter-asset correlations are not deteriorative but beneficial for portfolio management that can open new profit opportunities for trend followers. These concepts are illustrated using daily returns of three highly correlated futures markets: the E-mini S&P 500, Euro Stoxx 50 index, and the US 10-year T-note futures.
Bjordal, Andreas; Opdahl, Espen
2017-01-01
In this paper, we rigorously investigate the benefit of utilizing an active investment strategy based on momentum when investing in cryptocurrencies. We also examine how including cryptocurrencies in a more traditional asset allocation can optimize an investment portfolio. First, we create strategies with the use of exponential moving averages and simple average filters to generate a trading signal. Second, we provide evidence that the active strategies receive positive return,...
Asymptotic estimation of reactor fueling optimal strategy
International Nuclear Information System (INIS)
Simonov, V.D.
1985-01-01
The problem of improving the technical-economic factors of operating. and designed nuclear power plant blocks by developino. internal fuel cycle strategy (reactor fueling regime optimization), taking into account energy system structural peculiarities altogether, is considered. It is shown, that in search of asymptotic solutions of reactor fueling planning tasks the model of fuel energy potential (FEP) is the most ssuitable and effective. FEP represents energy which may be produced from the fuel in a reactor with real dimensions and power, but with hypothetical fresh fuel supply, regime, providing smilar burnup of all the fuel, passing through the reactor, and continuous overloading of infinitely small fuel portion under fule power, and infinitely rapid mixing of fuel in the reactor core volume. Reactor fuel run with such a standard fuel cycle may serve as FEP quantitative measure. Assessment results of optimal WWER-440 reactor fresh fuel supply periodicity are given as an example. The conclusion is drawn that with fuel enrichment x=3.3% the run which is 300 days, is economically justified, taking into account that the cost of one energy unit production is > 3 cop/KW/h
Urban and agricultural soils: conflicts and trade-offs in the optimization of ecosystem services
Setälä, H.; Bardgett, R.D.; Birkhofer, K.; Brady, M.; Byrne, L.; de Ruiter, P.C.; de Vries, F.T.; Gardi, C.; Hedlund, K.; Hemerik, L.; Hotes, S.; Liiri, M.; Mortimer, S.R.; Pavao-Zuckerman, M.; Pouyat, R.; Tsiafouli, M.; Van der Putten, W.H.
2014-01-01
[KEYWORDS: Agriculture Ecosystem services Land use Management optimization Soil Urban Trade-off] On-going human population growth and changing patterns of resource consumption are increasing global demand for ecosystem services, many of which are provided by soils. Some of these ecosystem services
Energy Efficiency - Spectral Efficiency Trade-off: A Multiobjective Optimization Approach
Amin, Osama
2015-04-23
In this paper, we consider the resource allocation problem for energy efficiency (EE) - spectral efficiency (SE) trade-off. Unlike traditional research that uses the EE as an objective function and imposes constraints either on the SE or achievable rate, we propound a multiobjective optimization approach that can flexibly switch between the EE and SE functions or change the priority level of each function using a trade-off parameter. Our dynamic approach is more tractable than the conventional approaches and more convenient to realistic communication applications and scenarios. We prove that the multiobjective optimization of the EE and SE is equivalent to a simple problem that maximizes the achievable rate/SE and minimizes the total power consumption. Then we apply the generalized framework of the resource allocation for the EE-SE trade-off to optimally allocate the subcarriers’ power for orthogonal frequency division multiplexing (OFDM) with imperfect channel estimation. Finally, we use numerical results to discuss the choice of the trade-off parameter and study the effect of the estimation error, transmission power budget and channel-to-noise ratio on the multiobjective optimization.
Energy Efficiency - Spectral Efficiency Trade-off: A Multiobjective Optimization Approach
Amin, Osama; Bedeer, Ebrahim; Ahmed, Mohamed; Dobre, Octavia
2015-01-01
In this paper, we consider the resource allocation problem for energy efficiency (EE) - spectral efficiency (SE) trade-off. Unlike traditional research that uses the EE as an objective function and imposes constraints either on the SE or achievable rate, we propound a multiobjective optimization approach that can flexibly switch between the EE and SE functions or change the priority level of each function using a trade-off parameter. Our dynamic approach is more tractable than the conventional approaches and more convenient to realistic communication applications and scenarios. We prove that the multiobjective optimization of the EE and SE is equivalent to a simple problem that maximizes the achievable rate/SE and minimizes the total power consumption. Then we apply the generalized framework of the resource allocation for the EE-SE trade-off to optimally allocate the subcarriers’ power for orthogonal frequency division multiplexing (OFDM) with imperfect channel estimation. Finally, we use numerical results to discuss the choice of the trade-off parameter and study the effect of the estimation error, transmission power budget and channel-to-noise ratio on the multiobjective optimization.
Sundara Rajan, R.; Uthayakumar, R.
2017-12-01
In this paper we develop an economic order quantity model to investigate the optimal replenishment policies for instantaneous deteriorating items under inflation and trade credit. Demand rate is a linear function of selling price and decreases negative exponentially with time over a finite planning horizon. Shortages are allowed and partially backlogged. Under these conditions, we model the retailer's inventory system as a profit maximization problem to determine the optimal selling price, optimal order quantity and optimal replenishment time. An easy-to-use algorithm is developed to determine the optimal replenishment policies for the retailer. We also provide optimal present value of profit when shortages are completely backlogged as a special case. Numerical examples are presented to illustrate the algorithm provided to obtain optimal profit. And we also obtain managerial implications from numerical examples to substantiate our model. The results show that there is an improvement in total profit from complete backlogging rather than the items being partially backlogged.
International Nuclear Information System (INIS)
Zhang, Xiang
2014-01-01
In this paper, we extend previous reference-dependence newsvendor research by incorporating both consumer trade-offs and government subsidies to evaluate the relevant influences on the optimal electric vehicle (EV) production decisions. We present the properties of the model, derive the closed-form solutions for the model given the relevant constraints, and use numerical experiments to illustrate the results. We find that subsidies, loss aversion, the performance of both EVs and internal combustion engine-powered vehicles (ICEVs), and the coefficient of variation of demand are significant factors influencing the optimal production quantity and the expected utilities of EV production. The high selling price and other high costs of ICEVs help offset the influence of loss aversion, whereas the high costs of EV enhance loss aversion. Our study enriches the literature on subsidies for EVs by establishing a behavioral model to incorporate the decision bias in terms of loss aversion at the firm level. These findings provide guiding principles for both policymakers and EV managers for making better strategies to promote EVs in the early immature market. - Highlights: • The performance of both electric vehicles (EVs) and internal combustion engine-power vehicles (ICEVs) influences the EV production decisions. • A loss averse EV manager produces less and obtains less the expected utility than a risk neutral one. • Subsidies help decrease the EV breakeven quantity, increase the optimal quantity, offset the influence of loss aversion. • Subsidies should be adjusted according to the performance of both EVs and the ICEVs, demand heterogeneity, and local conditions. • The high ICEVs costs help offset the influence of loss aversion, whereas the high EV costs enhance loss aversion
Optimal Charging of Electric Vehicles with Trading on the Intraday Electricity Market
Directory of Open Access Journals (Sweden)
Ilham Naharudinsyah
2018-06-01
Full Text Available Trading on the energy market is a possible way to reduce the electricity costs of charging electric vehicles at public charging stations. In many European countries, it is possible to trade electricity until shortly before the period of delivery on so called intraday electricity markets. In the present work, the potential for reducing the electricity costs by trading on the intraday market is investigated using the example of the German market. Based on simulations, the authors reveal that by optimizing the charging schedule together with the trading on the intraday electricity market, the costs can be reduced by around 8% compared to purchasing all the required energy from the energy supplier. By allowing the charging station operator to resell the energy to the intraday electricity market, an additional cost reduction of around 1% can be achieved. Besides the potential cost savings, the impacts of the trading unit and of the lead time of the intraday electricity market on the costs are investigated. The authors reveal that the achievable electricity costs can be strongly affected by the lead time, while the trading unit has only a minor effect on the costs.
International Nuclear Information System (INIS)
Anon.
1998-01-01
A total of 17 papers were presented at this conference, all of them devoted to a discussion of marketing strategies and price and supply outlook within the natural gas industry in North America. The presentations provided a practical and analytical look at where natural gas prices were heading. They also described winning trading and purchasing strategies. The challenges posed by the deregulation and the expected competition in the natural gas industry in North America also received much attention. tabs., figs
Optimal energy management strategy for self-reconfigurable batteries
International Nuclear Information System (INIS)
Bouchhima, Nejmeddine; Schnierle, Marc; Schulte, Sascha; Birke, Kai Peter
2017-01-01
This paper proposes a novel energy management strategy for multi-cell high voltage batteries where the current through each cell can be controlled, called self-reconfigurable batteries. An optimized control strategy further enhances the energy efficiency gained by the hardware architecture of those batteries. Currently, achieving cell equalization by using the active balancing circuits is considered as the best way to optimize the energy efficiency of the battery pack. This study demonstrates that optimizing the energy efficiency of self-reconfigurable batteries is no more strongly correlated to the cell balancing. According to the features of this novel battery architecture, the energy management strategy is formulated as nonlinear dynamic optimization problem. To solve this optimal control, an optimization algorithm that generates the optimal discharge policy for a given driving cycle is developed based on dynamic programming and code vectorization. The simulation results show that the designed energy management strategy maximizes the system efficiency across the battery lifetime over conventional approaches. Furthermore, the present energy management strategy can be implemented online due to the reduced complexity of the optimization algorithm. - Highlights: • The energy efficiency of self-reconfigurable batteries is maximized. • The energy management strategy for the battery is formulated as optimal control problem. • Developing an optimization algorithm using dynamic programming techniques and code vectorization. • Simulation studies are conducted to validate the proposed optimal strategy.
Life-history strategies of North American elk: trade-offs associated with reproduction and survival
Sabrina Morano; Kelley M. Stewart; James S. Sedinger; Christopher A. Nicolai; Marty Vavra
2013-01-01
The principle of energy allocation states that individuals should attempt to maximize fitness by allocating resources optimally among growth, maintenance, and reproduction. Such allocation may result in trade-offs between survival and reproduction, or between current and future reproduction. We used a marked population of North American elk (Cervus elaphus...
Simulation of trading strategies in the electricity market
Charkiewicz, Kamil; Nowak, Robert
2011-10-01
The main objective of the energy market existence is reduction of the total cost of production, transport and distribution of energy, and so the prices paid by terminal consumers. Energy market contains few markets that are varying on operational rules, the important segments: the Futures Contract Market and Next Day Market are analyzed in presented approach. The computer system was developed to simulate the Polish Energy Market. This system use the multi-agent approach, where each agent is the separate shared library with defined interface. The software was used to compare strategies for players in energy market, where the strategies uses auto-regression, k-nearest neighbours, neural network and mixed algorithm, to predict the next price.
DEFF Research Database (Denmark)
Steiner, Uli; Pfeiffer, Thomas
2007-01-01
pronounced at intermediate environmental conditions. Optimizing single traits generally leads to a more pronounced response of the defense traits, which implies that studying single traits leads to an overestimation of their response to predation. Behavioral defense and morphological defense compensate......Prey organisms are confronted with time and resource allocation trade-offs. Time allocation trade-offs partition time, for example, between foraging effort to acquire resources and behavioral defense. Resource allocation trade-offs partition the acquired resources between multiple traits...... for and augment each other depending on predator densities and the effectiveness of the defense mechanisms. In the presence of time constraints, the model shows peak investment into morphological and behavioral defense at intermediate resource levels....
DEFF Research Database (Denmark)
Dorn, Jochen
on Forex, interest rates and commodities. If an investor positions himself on the (volatility) market within a long/short trading framework, he typically bets on a traditional mispricing arbitrage. However as this corresponds to a call spread with equal exercise prices, this strategy alone would...
Optimization strategies for ultrasound volume registration
International Nuclear Information System (INIS)
Ijaz, Umer Zeeshan; Prager, Richard W; Gee, Andrew H; Treece, Graham M
2010-01-01
This paper considers registration of 3D ultrasound volumes acquired in multiple views for display in a single image volume. One way to acquire 3D data is to use a mechanically swept 3D probe. However, the usefulness of these probes is restricted by their limited field of view. This problem can be overcome by attaching a six-degree-of-freedom (DOF) position sensor to the probe, and displaying the information from multiple sweeps in their proper positions. However, an external six-DOF position sensor can be an inconvenience in a clinical setting. The objective of this paper is to propose a hybrid strategy that replaces the sensor with a combination of three-DOF image registration and an unobtrusive inertial sensor for measuring orientation. We examine a range of optimization algorithms and similarity measures for registration and compare them in in vitro and in vivo experiments. We register based on multiple reslice images rather than a whole voxel array. In this paper, we use a large number of reslices for improved reliability at the expense of computational speed. We have found that the Levenberg–Marquardt method is very fast but is not guaranteed to give the correct solution all the time. We conclude that normalized mutual information used in the Nelder–Mead simplex algorithm is potentially suitable for the registration task with an average execution time of around 5 min, in the majority of cases, with two restarts in a C++ implementation on a 3.0 GHz Intel Core 2 Duo CPU machine
Optimizing metapopulation sustainability through a checkerboard strategy.
Directory of Open Access Journals (Sweden)
Yossi Ben Zion
2010-01-01
Full Text Available The persistence of a spatially structured population is determined by the rate of dispersal among habitat patches. If the local dynamic at the subpopulation level is extinction-prone, the system viability is maximal at intermediate connectivity where recolonization is allowed, but full synchronization that enables correlated extinction is forbidden. Here we developed and used an algorithm for agent-based simulations in order to study the persistence of a stochastic metapopulation. The effect of noise is shown to be dramatic, and the dynamics of the spatial population differs substantially from the predictions of deterministic models. This has been validated for the stochastic versions of the logistic map, the Ricker map and the Nicholson-Bailey host-parasitoid system. To analyze the possibility of extinction, previous studies were focused on the attractiveness (Lyapunov exponent of stable solutions and the structure of their basin of attraction (dependence on initial population size. Our results suggest that these features are of secondary importance in the presence of stochasticity. Instead, optimal sustainability is achieved when decoherence is maximal. Individual-based simulations of metapopulations of different sizes, dimensions and noise types, show that the system's lifetime peaks when it displays checkerboard spatial patterns. This conclusion is supported by the results of a recently published Drosophila experiment. The checkerboard strategy provides a technique for the manipulation of migration rates (e.g., by constructing corridors in order to affect the persistence of a metapopulation. It may be used in order to minimize the risk of extinction of an endangered species, or to maximize the efficiency of an eradication campaign.
Directory of Open Access Journals (Sweden)
Sait AKMAN
2010-04-01
Full Text Available This study attempts to assess implications, of European Union’s (EU new trade strategy and its Free Trade Agreements (FTAs with third countries, on Turkey-EU relations. It analyses critics raised in the context of FTAs and puts forward that the sustainability of the relations is contingent to the satisfaction of a set of criteria.The EU shifted its trade policy from sole reliance on multilateral trade negotiations towards initiatives for bilateral and preferential agreements (PTAs under its ‘Global Europe’ strategy which was adopted in 2006, to propose its trade policy agenda and priorities in accordance with its Lisbon Strategy. WTO Doha Round is currently in deadlock and it is improbable that it will be concluded in the near future. Partly for this reason, the EU tends to implement its policy objectives constantly through a set of FTAs. Turkey has to align its trade policy to the EU’s preferential regimes, pursuant to its obligations arising from the Customs Union (CU. Hence, it has concluded so far sixteen FTAs with relevant countries. On the other hand, the intensification of critics about the FTAs process and the CU brings impediments for Turkey to commit itself to its CU obligations in the next period. Two main motives can be cited as a reason: First, the EU trade strategy obviously considers the global context within which the EU rests; and the Member States’ interests, which are subsequently reflected into its FTAs. Nevertheless, a harmonious action by Turkey becomes onerous as long as EU trade priorities diverge from Turkey’s long term trade strategy. Second reason, aside from technical aspects of the CU, can be attributed to the ‘political uncertainty’ converged around the ‘open-endedness’ of the membership process, which in turn affects the CU, Turkey’s most vital linkage to the EU, and the commitments there from.
Developing an Integrated Design Strategy for Chip Layout Optimization
Wits, Wessel Willems; Jauregui Becker, Juan Manuel; van Vliet, Frank Edward; te Riele, G.J.
2011-01-01
This paper presents an integrated design strategy for chip layout optimization. The strategy couples both electric and thermal aspects during the conceptual design phase to improve chip performances; thermal management being one of the major topics. The layout of the chip circuitry is optimized
Optimal Spatial Harvesting Strategy and Symmetry-Breaking
International Nuclear Information System (INIS)
Kurata, Kazuhiro; Shi Junping
2008-01-01
A reaction-diffusion model with logistic growth and constant effort harvesting is considered. By minimizing an intrinsic biological energy function, we obtain an optimal spatial harvesting strategy which will benefit the population the most. The symmetry properties of the optimal strategy are also discussed, and related symmetry preserving and symmetry breaking phenomena are shown with several typical examples of habitats
Trade, Foreign Direct Investment or Acquisition: Optimal Entry Modes for Multinationals
Theo Eicher; Jong Woo Kang
2004-01-01
We examine multinationalsâ€™ optimal entry modes into foreign markets as a function of market size, FDI fixed costs, tariffs and transport costs. Our results highlight why large countries are more likely to attract acquisition investment, while intermediate-sized countries may be served predominantly through trade, even in the presence of high tariffs. Small countries are most likely to experience either FDI or no entry. We also show how these results vary with the competition intensity in th...
Synthesis of Optimal Strategies Using HyTech
DEFF Research Database (Denmark)
Bouyer, Patricia; Cassez, Franck; Larsen, Kim Guldstrand
2005-01-01
Priced timed (game) automata extend timed (game) automata with costs on both locations and transitions. The problem of synthesizing an optimal winning strategy for a priced timed game under some hypotheses has been shown decidable in [P. Bouyer, F. Cassez, E. Fleury, and K.G. Larsen. Optimal...... strategies in priced timed game automata. Research Report BRICS RS-04-4, Denmark, Feb. 2004. Available at http://www.brics.dk/RS/04/4/]. In this paper, we present an algorithm for computing the optimal cost and for synthesizing an optimal strategy in case there exists one. We also describe the implementation...
Optimization Strategies for Hardware-Based Cofactorization
Loebenberger, Daniel; Putzka, Jens
We use the specific structure of the inputs to the cofactorization step in the general number field sieve (GNFS) in order to optimize the runtime for the cofactorization step on a hardware cluster. An optimal distribution of bitlength-specific ECM modules is proposed and compared to existing ones. With our optimizations we obtain a speedup between 17% and 33% of the cofactorization step of the GNFS when compared to the runtime of an unoptimized cluster.
Directory of Open Access Journals (Sweden)
Mohammad Masih Sediqi
2017-07-01
Full Text Available Afghanistan is a key country between energy surplus areas (Central Asian Republics andIran and energy deficit regions (Pakistan and India. It is in a position that can facilitate and launchregional electricity trade for the benefit of the region also derive significant gains for its own economyfrom energy imports and exports. On the other hand, Afghanistan is endowed with large renewableenergy resources (RERs, which it could exploit not only to satisfy its domestic power demand butalso to earn significant export revenue. This paper firstly explains the methodology and framework forthe power trade and then presents an optimization framework for profit maximization in the short-runtrading and cost minimization in the long-run trading. The proposed methodology is applied to a realcase between Afghanistan and Pakistan. The objective functions, parameters, variables and constraintsare described for both optimization models. System sizing, simulation and optimization are carriedout using genetic algorithm (GA technique. The results in the short-run model represent optimalityof about 2654 MW electricity export from Afghanistan to Pakistan during summer. Moreover, resultsderived from running long-run model depict that by utilizing its RERs such as solar, wind and hydro,Afghanistan can not only meet its power demand but also can export to Pakistan during its deficitperiods and gain remarkable energy profits.
Particle swarm optimization based optimal bidding strategy in an ...
African Journals Online (AJOL)
In an electricity market generating companies and large consumers need suitable bidding models to maximize their profits. Therefore, each supplier and large consumer will bid strategically for choosing the bidding coefficients to counter the competitors bidding strategy. In this paper, bidding strategy problem modeled as an ...
An optimal control model for reducing and trading of carbon emissions
Guo, Huaying; Liang, Jin
2016-03-01
A stochastic optimal control model of reducing and trading for carbon emissions is established in this paper. With considerations of reducing the carbon emission growth and the price of the allowances in the market, an optimal policy is searched to have the minimum total costs to achieve the agreement of emission reduction targets. The model turns to a two-dimension HJB equation problem. By the methods of reducing dimension and Cole-Hopf transformation, a semi-closed form solution of the corresponding HJB problem under some assumptions is obtained. For more general cases, the numerical calculations, analysis and comparisons are presented.
Optimal control of LQG problem with an explicit trade-off between mean and variance
Qian, Fucai; Xie, Guo; Liu, Ding; Xie, Wenfang
2011-12-01
For discrete-time linear-quadratic Gaussian (LQG) control problems, a utility function on the expectation and the variance of the conventional performance index is considered. The utility function is viewed as an overall objective of the system and can perform the optimal trade-off between the mean and the variance of performance index. The nonlinear utility function is first converted into an auxiliary parameters optimisation problem about the expectation and the variance. Then an optimal closed-loop feedback controller for the nonseparable mean-variance minimisation problem is designed by nonlinear mathematical programming. Finally, simulation results are given to verify the algorithm's effectiveness obtained in this article.
Optimization strategies for discrete multi-material stiffness optimization
DEFF Research Database (Denmark)
Hvejsel, Christian Frier; Lund, Erik; Stolpe, Mathias
2011-01-01
Design of composite laminated lay-ups are formulated as discrete multi-material selection problems. The design problem can be modeled as a non-convex mixed-integer optimization problem. Such problems are in general only solvable to global optimality for small to moderate sized problems. To attack...... which numerically confirm the sought properties of the new scheme in terms of convergence to a discrete solution....
Directory of Open Access Journals (Sweden)
Jun Yang
2015-08-01
Full Text Available The carbon emissions trading market and direct power purchases by large consumers are two promising directions of power system development. To trace the carbon emission flow in the power grid, the theory of carbon emission flow is improved by allocating power loss to the load side. Based on the improved carbon emission flow theory, an optimal dispatch model is proposed to optimize the cost of both large consumers and the power grid, which will benefit from the carbon emissions trading market. Moreover, to better simulate reality, the direct purchase of power by large consumers is also considered in this paper. The OPF (optimal power flow method is applied to solve the problem. To evaluate our proposed optimal dispatch strategy, an IEEE 30-bus system is used to test the performance. The effects of the price of carbon emissions and the price of electricity from normal generators and low-carbon generators with regards to the optimal dispatch are analyzed. The simulation results indicate that the proposed strategy can significantly reduce both the operation cost of the power grid and the power utilization cost of large consumers.
An Equivalent Emission Minimization Strategy for Causal Optimal Control of Diesel Engines
Directory of Open Access Journals (Sweden)
Stephan Zentner
2014-02-01
Full Text Available One of the main challenges during the development of operating strategies for modern diesel engines is the reduction of the CO2 emissions, while complying with ever more stringent limits for the pollutant emissions. The inherent trade-off between the emissions of CO2 and pollutants renders a simultaneous reduction difficult. Therefore, an optimal operating strategy is sought that yields minimal CO2 emissions, while holding the cumulative pollutant emissions at the allowed level. Such an operating strategy can be obtained offline by solving a constrained optimal control problem. However, the final-value constraint on the cumulated pollutant emissions prevents this approach from being adopted for causal control. This paper proposes a framework for causal optimal control of diesel engines. The optimization problem can be solved online when the constrained minimization of the CO2 emissions is reformulated as an unconstrained minimization of the CO2 emissions and the weighted pollutant emissions (i.e., equivalent emissions. However, the weighting factors are not known a priori. A method for the online calculation of these weighting factors is proposed. It is based on the Hamilton–Jacobi–Bellman (HJB equation and a physically motivated approximation of the optimal cost-to-go. A case study shows that the causal control strategy defined by the online calculation of the equivalence factor and the minimization of the equivalent emissions is only slightly inferior to the non-causal offline optimization, while being applicable to online control.
Fetal DNA: strategies for optimal recovery
Legler, Tobias J.; Heermann, Klaus-Hinrich; Liu, Zhong; Soussan, Aicha Ait; van der Schoot, C. Ellen
2008-01-01
For fetal DNA extraction, in principle each DNA extraction method can be used; however, because most methods have been optimized for genomic DNA from leucocytes, we describe here the methods that have been optimized for the extraction of fetal DNA from maternal plasma and validated for this purpose
Strategies for Optimal Design of Structural Systems
DEFF Research Database (Denmark)
Enevoldsen, I.; Sørensen, John Dalsgaard
1992-01-01
Reliability-based design of structural systems is considered. Especially systems where the reliability model is a series system of parallel systems are analysed. A sensitivity analysis for this class of problems is presented. Direct and sequential optimization procedures to solve the optimization...
An optimal tuning strategy for tidal turbines.
Vennell, Ross
2016-11-01
Tuning wind and tidal turbines is critical to maximizing their power output. Adopting a wind turbine tuning strategy of maximizing the output at any given time is shown to be an extremely poor strategy for large arrays of tidal turbines in channels. This 'impatient-tuning strategy' results in far lower power output, much higher structural loads and greater environmental impacts due to flow reduction than an existing 'patient-tuning strategy' which maximizes the power output averaged over the tidal cycle. This paper presents a 'smart patient tuning strategy', which can increase array output by up to 35% over the existing strategy. This smart strategy forgoes some power generation early in the half tidal cycle in order to allow stronger flows to develop later in the cycle. It extracts enough power from these stronger flows to produce more power from the cycle as a whole than the existing strategy. Surprisingly, the smart strategy can often extract more power without increasing maximum structural loads on the turbines, while also maintaining stronger flows along the channel. This paper also shows that, counterintuitively, for some tuning strategies imposing a cap on turbine power output to limit loads can increase a turbine's average power output.
Study on the Optimal Charging Strategy for Lithium-Ion Batteries Used in Electric Vehicles
Directory of Open Access Journals (Sweden)
Shuo Zhang
2014-10-01
Full Text Available The charging method of lithium-ion batteries used in electric vehicles (EVs significantly affects its commercial application. This paper aims to make three contributions to the existing literature. (1 In order to achieve an efficient charging strategy for lithium-ion batteries with shorter charging time and lower charring loss, the trade-off problem between charging loss and charging time has been analyzed in details through the dynamic programing (DP optimization algorithm; (2 To reduce the computation time consumed during the optimization process, we have proposed a database based optimization approach. After off-line calculation, the simulation results can be applied to on-line charge; (3 The novel database-based DP method is proposed and the simulation results illustrate that this method can effectively find the suboptimal charging strategies under a certain balance between the charging loss and charging time.
Particle swarm optimization based optimal bidding strategy in an ...
African Journals Online (AJOL)
user
A considerable amount of work has also been reported on the game theory applications ... probability distribution function (Song et al, 1999) and as a continuous ..... compared with GA and Monte Carlo method, therefore the bidding strategies.
Systematic Trading: Calibration Advances through Machine Learning
Alvarez Teleña, S.
2015-01-01
Systematic trading in finance uses computer models to define trade goals, risk controls and rules that can execute trade orders in a methodical way. This thesis investigates how performance in systematic trading can be crucially enhanced by both i) persistently reducing the bid-offer spread quoted by the trader through optimized and realistically backtested strategies and ii) improving the out-of-sample robustness of the strategy selected through the injection of theory into the typically dat...
Mathematics, Pricing, Market Risk Management and Trading Strategies for Financial Derivatives (1/3)
CERN. Geneva; Coffey, Brian
2009-01-01
Abstract: An introduction to the mathematics and practicalities of market trading and risk management for financial derivatives, the course will focus on examples from the short-term and long term Foreign Exchange (FX) and Interest Rate (IR) derivatives markets. Topics: - Government Bonds and IR Curves - Stochastic FX, Black-Scholes Vanilla FX Options and Martingales - Risk Management and Market Trading for Vanilla FX Options, Market Implied Volatility, Valuation and Risk Management, Market Trading Strategies - Stochastic IR Curves and Implied Volatility, IR Derivatives - Long Term FX Options: Interaction of Stochastic FX and Stochastic IR Vanilla Foreign Exchange (FX) Options - $ Government Bonds, Interest Rate (IR) Curves, Continuous IR - Domestic ($) and Foreign (Yen) Government Bonds, IR curves - Stochastic Spot FX, Forward FX: Ito processes for $ and Yen Investors - Black-Scholes Vanilla FX Options, Connection to Heat/Diffusion Equation - Stochastic Differential Equations with Mart...
Optimal portfolio strategies under a shortfall constraint
African Journals Online (AJOL)
we make precise the optimal control problem to be solved. .... is closely related to the concept of Value-at-Risk, but overcomes some of the conceptual .... We adapt a dynamic programming approach to solve the HJB equation associated with.
Optimal Pricing Strategy for New Products
Trichy V. Krishnan; Frank M. Bass; Dipak C. Jain
1999-01-01
Robinson and Lakhani (1975) initiated a long research stream in marketing when they used the Bass model (1969) to develop optimal pricing path for a new product. A careful analysis of the extant literature reveals that the research predominantly suggests that the optimal price path should be largely based on the sales growth pattern. However, in the real world we rarely find new products that have such pricing pattern. We observe either a monotonically declining pricing pattern or an increase...
An optimal tuning strategy for tidal turbines
2016-01-01
Tuning wind and tidal turbines is critical to maximizing their power output. Adopting a wind turbine tuning strategy of maximizing the output at any given time is shown to be an extremely poor strategy for large arrays of tidal turbines in channels. This ‘impatient-tuning strategy’ results in far lower power output, much higher structural loads and greater environmental impacts due to flow reduction than an existing ‘patient-tuning strategy’ which maximizes the power output averaged over the tidal cycle. This paper presents a ‘smart patient tuning strategy’, which can increase array output by up to 35% over the existing strategy. This smart strategy forgoes some power generation early in the half tidal cycle in order to allow stronger flows to develop later in the cycle. It extracts enough power from these stronger flows to produce more power from the cycle as a whole than the existing strategy. Surprisingly, the smart strategy can often extract more power without increasing maximum structural loads on the turbines, while also maintaining stronger flows along the channel. This paper also shows that, counterintuitively, for some tuning strategies imposing a cap on turbine power output to limit loads can increase a turbine’s average power output. PMID:27956870
Investment Strategies Optimization based on a SAX-GA Methodology
Canelas, António M L; Horta, Nuno C G
2013-01-01
This book presents a new computational finance approach combining a Symbolic Aggregate approXimation (SAX) technique with an optimization kernel based on genetic algorithms (GA). While the SAX representation is used to describe the financial time series, the evolutionary optimization kernel is used in order to identify the most relevant patterns and generate investment rules. The proposed approach considers several different chromosomes structures in order to achieve better results on the trading platform The methodology presented in this book has great potential on investment markets.
Power consumption optimization strategy for wireless networks
DEFF Research Database (Denmark)
Cornean, Horia; Kumar, Sanjay; Marchetti, Nicola
2011-01-01
in order to reduce the total power consumption in a multi cellular network. We present an algorithm for power optimization under no interference and in presence of interference conditions, targeting to maximize the network capacity. The convergence of the algorithm is guaranteed if the interference...
Customs Service Modernization: Impact of New Trade Compliance Strategy Needs to Be Assessed.
1999-12-01
The Mod Act fundamentally altered the relationship between importers and Customs by shifting from Customs to the importer the legal responsibility...New Trade Compliance Strategy B-280470 • account management : Customs ’ approach to managing its work through accounts (importing companies) rather...assessment, account management , and Customs ’ responses to noncompliant importers have been implemented but have not yet reached many of the intended
Social strategy games in communicating trade-offs between mitigation and adaptation in cities
DEFF Research Database (Denmark)
Juhola, Sirkku; Driscoll, Patrick Arthur; Suarez, Pablo
2013-01-01
and mitigation strategies and what kinds of negative and positive synergies can be identified between them. This paper explores how social games can help people to understand the trade-offs between mitigation and adaptation measures in an urban environment and examines the possibilities of using social gaming...... as a research method. Data was collected from Denmark, Finland and the US through organized gaming sessions. The conclusion of the study is that social games are a promising method to understand complex planning problems....
Intelligent fault recognition strategy based on adaptive optimized multiple centers
Zheng, Bo; Li, Yan-Feng; Huang, Hong-Zhong
2018-06-01
For the recognition principle based optimized single center, one important issue is that the data with nonlinear separatrix cannot be recognized accurately. In order to solve this problem, a novel recognition strategy based on adaptive optimized multiple centers is proposed in this paper. This strategy recognizes the data sets with nonlinear separatrix by the multiple centers. Meanwhile, the priority levels are introduced into the multi-objective optimization, including recognition accuracy, the quantity of optimized centers, and distance relationship. According to the characteristics of various data, the priority levels are adjusted to ensure the quantity of optimized centers adaptively and to keep the original accuracy. The proposed method is compared with other methods, including support vector machine (SVM), neural network, and Bayesian classifier. The results demonstrate that the proposed strategy has the same or even better recognition ability on different distribution characteristics of data.
Long-run savings and investment strategy optimization.
Gerrard, Russell; Guillén, Montserrat; Nielsen, Jens Perch; Pérez-Marín, Ana M
2014-01-01
We focus on automatic strategies to optimize life cycle savings and investment. Classical optimal savings theory establishes that, given the level of risk aversion, a saver would keep the same relative amount invested in risky assets at any given time. We show that, when optimizing lifecycle investment, performance and risk assessment have to take into account the investor's risk aversion and the maximum amount the investor could lose, simultaneously. When risk aversion and maximum possible loss are considered jointly, an optimal savings strategy is obtained, which follows from constant rather than relative absolute risk aversion. This result is fundamental to prove that if risk aversion and the maximum possible loss are both high, then holding a constant amount invested in the risky asset is optimal for a standard lifetime saving/pension process and outperforms some other simple strategies. Performance comparisons are based on downside risk-adjusted equivalence that is used in our illustration.
Long-Run Savings and Investment Strategy Optimization
Directory of Open Access Journals (Sweden)
Russell Gerrard
2014-01-01
Full Text Available We focus on automatic strategies to optimize life cycle savings and investment. Classical optimal savings theory establishes that, given the level of risk aversion, a saver would keep the same relative amount invested in risky assets at any given time. We show that, when optimizing lifecycle investment, performance and risk assessment have to take into account the investor’s risk aversion and the maximum amount the investor could lose, simultaneously. When risk aversion and maximum possible loss are considered jointly, an optimal savings strategy is obtained, which follows from constant rather than relative absolute risk aversion. This result is fundamental to prove that if risk aversion and the maximum possible loss are both high, then holding a constant amount invested in the risky asset is optimal for a standard lifetime saving/pension process and outperforms some other simple strategies. Performance comparisons are based on downside risk-adjusted equivalence that is used in our illustration.
Optimal inspection strategies for offshore structural systems
DEFF Research Database (Denmark)
Faber, M. H.; Sorensen, J. D.; Kroon, I. B.
1992-01-01
a mathematical framework for the estimation of the failure and repair costs a.ssociated with systems failure. Further a strategy for selecting the components to inspect based on decision tree analysis is suggested. Methods and analysis schemes are illustrated by a simple example....
You, Yu-cong; Yi, Lu-xia
2017-11-01
From the perspective of energy supply-side reform, this paper, by conducting an empirical study on foreign trade enterprises, conducts a research on the cross-role effect of optimizing the resources allocation and enhancing the energy efficiency. Methodologically, this paper creatively introduces the HILE's probabilistic structured property into Granger causality test analysis, forming an HILE-Granger (H-G) model, so as to empirically estimate both the short-term and long-term causal relationship effects between the energy efficiency and resources allocation. Conclusion is drawn that optimization of resources allocation is positively proportional with the energy efficiency enhancement. This paper is to provide a decision-making reference for the supply side reform strategy of foreign trade enterprises under the background of green energy economy.
Control strategy optimization of HVAC plants
Energy Technology Data Exchange (ETDEWEB)
Facci, Andrea Luigi; Zanfardino, Antonella [Department of Engineering, University of Napoli “Parthenope” (Italy); Martini, Fabrizio [Green Energy Plus srl (Italy); Pirozzi, Salvatore [SIAT Installazioni spa (Italy); Ubertini, Stefano [School of Engineering (DEIM) University of Tuscia (Italy)
2015-03-10
In this paper we present a methodology to optimize the operating conditions of heating, ventilation and air conditioning (HVAC) plants to achieve a higher energy efficiency in use. Semi-empiric numerical models of the plant components are used to predict their performances as a function of their set-point and the environmental and occupied space conditions. The optimization is performed through a graph-based algorithm that finds the set-points of the system components that minimize energy consumption and/or energy costs, while matching the user energy demands. The resulting model can be used with systems of almost any complexity, featuring both HVAC components and energy systems, and is sufficiently fast to make it applicable to real-time setting.
Control strategy optimization of HVAC plants
International Nuclear Information System (INIS)
Facci, Andrea Luigi; Zanfardino, Antonella; Martini, Fabrizio; Pirozzi, Salvatore; Ubertini, Stefano
2015-01-01
In this paper we present a methodology to optimize the operating conditions of heating, ventilation and air conditioning (HVAC) plants to achieve a higher energy efficiency in use. Semi-empiric numerical models of the plant components are used to predict their performances as a function of their set-point and the environmental and occupied space conditions. The optimization is performed through a graph-based algorithm that finds the set-points of the system components that minimize energy consumption and/or energy costs, while matching the user energy demands. The resulting model can be used with systems of almost any complexity, featuring both HVAC components and energy systems, and is sufficiently fast to make it applicable to real-time setting
Optimal Licensing Strategy: Royalty or Fixed Fee?
Andrea Fosfuri; Esther Roca
2004-01-01
Licensing a cost-reducing innovation through a royalty has been shown to be superior to licensing by means of a fixed fee for an incumbent licensor. This note shows that this result relies crucially on the assumption that the incumbent licensor can sell its cost-reducing inno-vation to all industry players. If, for any reason, only some competitors could be reached through a licensing contract, then a fixed fee might be optimally chosen.
DEFF Research Database (Denmark)
Wang, Qi
Distributed energy resources (DERs), such as distributed generation (DG) and demand response (DR), have been recognized worldwide as valuable resources. High integration of DG and DR in the distribution network inspires a potential deregulated environment for the distribution company (DISCO...... in the presented DL market and transact with TL real-time market. A one-leader multi-follower-type bi-level model is proposed to indicate the PDISCO's trading strategies. To participate in the TL real-time market, a methodology is presented to derive continuous bidding/offering strategies for a PDISCO. A bi...
Optimized Power Dispatch Strategy for Offshore Wind Farms
DEFF Research Database (Denmark)
Hou, Peng; Hu, Weihao; Zhang, Baohua
2016-01-01
which are related to electrical system topology. This paper proposed an optimized power dispatch strategy (OPD) for minimizing the levelized production cost (LPC) of a wind farm. Particle swarm optimization (PSO) is employed to obtain final solution for the optimization problem. Both regular shape......Maximizing the power production of offshore wind farms using proper control strategy has become an important issue for wind farm operators. However, the power transmitted to the onshore substation (OS) is not only related to the power production of each wind turbine (WT) but also the power losses...... and irregular shape wind farm are chosen for the case study. The proposed dispatch strategy is compared with two other control strategies. The simulation results show the effectiveness of the proposed strategy....
Sleep As A Strategy For Optimizing Performance.
Yarnell, Angela M; Deuster, Patricia
2016-01-01
Recovery is an essential component of maintaining, sustaining, and optimizing cognitive and physical performance during and after demanding training and strenuous missions. Getting sufficient amounts of rest and sleep is key to recovery. This article focuses on sleep and discusses (1) why getting sufficient sleep is important, (2) how to optimize sleep, and (3) tools available to help maximize sleep-related performance. Insufficient sleep negatively impacts safety and readiness through reduced cognitive function, more accidents, and increased military friendly-fire incidents. Sufficient sleep is linked to better cognitive performance outcomes, increased vigor, and better physical and athletic performance as well as improved emotional and social functioning. Because Special Operations missions do not always allow for optimal rest or sleep, the impact of reduced rest and sleep on readiness and mission success should be minimized through appropriate preparation and planning. Preparation includes periods of "banking" or extending sleep opportunities before periods of loss, monitoring sleep by using tools like actigraphy to measure sleep and activity, assessing mental effectiveness, exploiting strategic sleep opportunities, and consuming caffeine at recommended doses to reduce fatigue during periods of loss. Together, these efforts may decrease the impact of sleep loss on mission and performance. 2016.
Optimal Dynamic Advertising Strategy Under Age-Specific Market Segmentation
Krastev, Vladimir
2011-12-01
We consider the model proposed by Faggian and Grosset for determining the advertising efforts and goodwill in the long run of a company under age segmentation of consumers. Reducing this model to optimal control sub problems we find the optimal advertising strategy and goodwill.
A strategy for optimizing item-pool management
Ariel, A.; van der Linden, Willem J.; Veldkamp, Bernard P.
2006-01-01
Item-pool management requires a balancing act between the input of new items into the pool and the output of tests assembled from it. A strategy for optimizing item-pool management is presented that is based on the idea of a periodic update of an optimal blueprint for the item pool to tune item
International Nuclear Information System (INIS)
Boonchuay, Chanwit; Ongsakul, Weerakorn
2011-01-01
In this paper, an optimal risky bidding strategy for a generating company (GenCo) by self-organising hierarchical particle swarm optimisation with time-varying acceleration coefficients (SPSO-TVAC) is proposed. A significant risk index based on mean-standard deviation ratio (MSR) is maximised to provide the optimal bid prices and quantities. The Monte Carlo (MC) method is employed to simulate rivals' behaviour in competitive environment. Non-convex operating cost functions of thermal generating units and minimum up/down time constraints are taken into account. The proposed bidding strategy is implemented in a multi-hourly trading in a uniform price spot market and compared to other particle swarm optimisation (PSO). Test results indicate that the proposed SPSO-TVAC approach can provide a higher MSR than the other PSO methods. It is potentially applicable to risk management of profit variation of GenCo in spot market.
Aggregators’ Optimal Bidding Strategy in Sequential Day-Ahead and Intraday Electricity Spot Markets
Directory of Open Access Journals (Sweden)
Xiaolin Ayón
2017-04-01
Full Text Available This paper proposes a probabilistic optimization method that produces optimal bidding curves to be submitted by an aggregator to the day-ahead electricity market and the intraday market, considering the flexible demand of his customers (based in time dependent resources such as batteries and shiftable demand and taking into account the possible imbalance costs as well as the uncertainty of forecasts (market prices, demand, and renewable energy sources (RES generation. The optimization strategy aims to minimize the total cost of the traded energy over a whole day, taking into account the intertemporal constraints. The proposed formulation leads to the solution of different linear optimization problems, following the natural temporal sequence of electricity spot markets. Intertemporal constraints regarding time dependent resources are fulfilled through a scheduling process performed after the day-ahead market clearing. Each of the different problems is of moderate dimension and requires short computation times. The benefits of the proposed strategy are assessed comparing the payments done by an aggregator over a sample period of one year following different deterministic and probabilistic strategies. Results show that probabilistic strategy reports better benefits for aggregators participating in power markets.
Many-objective optimization and visual analytics reveal key trade-offs for London's water supply
Matrosov, Evgenii S.; Huskova, Ivana; Kasprzyk, Joseph R.; Harou, Julien J.; Lambert, Chris; Reed, Patrick M.
2015-12-01
In this study, we link a water resource management simulator to multi-objective search to reveal the key trade-offs inherent in planning a real-world water resource system. We consider new supplies and demand management (conservation) options while seeking to elucidate the trade-offs between the best portfolios of schemes to satisfy projected water demands. Alternative system designs are evaluated using performance measures that minimize capital and operating costs and energy use while maximizing resilience, engineering and environmental metrics, subject to supply reliability constraints. Our analysis shows many-objective evolutionary optimization coupled with state-of-the art visual analytics can help planners discover more diverse water supply system designs and better understand their inherent trade-offs. The approach is used to explore future water supply options for the Thames water resource system (including London's water supply). New supply options include a new reservoir, water transfers, artificial recharge, wastewater reuse and brackish groundwater desalination. Demand management options include leakage reduction, compulsory metering and seasonal tariffs. The Thames system's Pareto approximate portfolios cluster into distinct groups of water supply options; for example implementing a pipe refurbishment program leads to higher capital costs but greater reliability. This study highlights that traditional least-cost reliability constrained design of water supply systems masks asset combinations whose benefits only become apparent when more planning objectives are considered.
Blackjack in Holland Casino's : Basic, optimal and winning strategies
van der Genugten, B.B.
1995-01-01
This paper considers the cardgame Blackjack according to the rules of Holland Casino's in the Netherlands. Expected gains of strategies are derived with simulation and also with analytic tools. New effiency concepts based on the gains of the basic and the optimal strategy are introduced. A general
Tsung-Hsun Lu; Yi-Chi Chen; Yu-Chin Hsu
2014-01-01
We ask what determines the profitability of candlestick patterns. Is it the definition of trend and/or the holding strategy that one uses in candlestick charting analysis? To answer this, we conduct a systematic investigation by considering three definitions of trend and four holding strategies. Based on the DJIA components data, we find that eight three-day reversal patterns with a Caginalp-Laurent holding strategy are profitable after we account for data-snooping bias. We also find that our...
Optimal contract for a fund manager, with capital injections and endogenous trading constraints
Nadtochiy, Sergey; Zariphopoulou, Thaleia
2018-01-01
In this paper, we construct a solution to the optimal contract problem for delegated portfolio management of the fist-best (risk-sharing) type. The novelty of our result is (i) in the robustness of the optimal contract with respect to perturbations of the wealth process (interpreted as capital injections), and (ii) in the more general form of principals objective function, which is allowed to depend directly on the agents strategy, as opposed to being a function of the generated wealth only. ...
TRADING-OFF CONSTRAINTS IN THE PUMP SCHEDULING OPTIMIZATION OF WATER DISTRIBUTION NETWORKS
Directory of Open Access Journals (Sweden)
Gencer Genço\\u011Flu
2016-01-01
Full Text Available Pumps are one of the essential components of water supply systems. Depending of the topography, a water supply system may completely rely on pumping. They may consume non-negligible amount of water authorities' budgets during operation. Besides their energy costs, maintaining the healthiness of pumping systems is another concern for authorities. This study represents a multi-objective optimization method for pump scheduling problem. The optimization objective contains hydraulic and operational constraints. Switching of pumps and usage of electricity tariff are assumed to be key factors for operational reliability and energy consumption and costs of pumping systems. The local optimals for systems operational reliability, energy consumptions and energy costs are investigated resulting from trading-off pump switch and electricity tariff constraints within given set of boundary conditions. In the study, a custom made program is employed that combines genetic algorithm based optimization module with hydraulic network simulation software -EPANET. Developed method is applied on the case study network; N8-3 pressure zone of the Northern Supply of Ankara (Turkey Water Distribution Network. This work offers an efficient method for water authorities aiming to optimize pumping schedules considering expenditures and operational reliability mutually.
A new inertia weight control strategy for particle swarm optimization
Zhu, Xianming; Wang, Hongbo
2018-04-01
Particle Swarm Optimization is a member of swarm intelligence algorithms, which is inspired by the behavior of bird flocks. The inertia weight, one of the most important parameters of PSO, is crucial for PSO, for it balances the performance of exploration and exploitation of the algorithm. This paper proposes a new inertia weight control strategy and PSO with this new strategy is tested by four benchmark functions. The results shows that the new strategy provides the PSO with better performance.
International Nuclear Information System (INIS)
Salari, Ehsan; Craft, David; Wala, Jeremiah
2012-01-01
To formulate and solve the fluence-map merging procedure of the recently-published VMAT treatment-plan optimization method, called vmerge, as a bi-criteria optimization problem. Using an exact merging method rather than the previously-used heuristic, we are able to better characterize the trade-off between the delivery efficiency and dose quality. vmerge begins with a solution of the fluence-map optimization problem with 180 equi-spaced beams that yields the ‘ideal’ dose distribution. Neighboring fluence maps are then successively merged, meaning that they are added together and delivered as a single map. The merging process improves the delivery efficiency at the expense of deviating from the initial high-quality dose distribution. We replace the original merging heuristic by considering the merging problem as a discrete bi-criteria optimization problem with the objectives of maximizing the treatment efficiency and minimizing the deviation from the ideal dose. We formulate this using a network-flow model that represents the merging problem. Since the problem is discrete and thus non-convex, we employ a customized box algorithm to characterize the Pareto frontier. The Pareto frontier is then used as a benchmark to evaluate the performance of the standard vmerge algorithm as well as two other similar heuristics. We test the exact and heuristic merging approaches on a pancreas and a prostate cancer case. For both cases, the shape of the Pareto frontier suggests that starting from a high-quality plan, we can obtain efficient VMAT plans through merging neighboring fluence maps without substantially deviating from the initial dose distribution. The trade-off curves obtained by the various heuristics are contrasted and shown to all be equally capable of initial plan simplifications, but to deviate in quality for more drastic efficiency improvements. This work presents a network optimization approach to the merging problem. Contrasting the trade-off curves of the
Salari, Ehsan; Wala, Jeremiah; Craft, David
2012-09-07
To formulate and solve the fluence-map merging procedure of the recently-published VMAT treatment-plan optimization method, called VMERGE, as a bi-criteria optimization problem. Using an exact merging method rather than the previously-used heuristic, we are able to better characterize the trade-off between the delivery efficiency and dose quality. VMERGE begins with a solution of the fluence-map optimization problem with 180 equi-spaced beams that yields the 'ideal' dose distribution. Neighboring fluence maps are then successively merged, meaning that they are added together and delivered as a single map. The merging process improves the delivery efficiency at the expense of deviating from the initial high-quality dose distribution. We replace the original merging heuristic by considering the merging problem as a discrete bi-criteria optimization problem with the objectives of maximizing the treatment efficiency and minimizing the deviation from the ideal dose. We formulate this using a network-flow model that represents the merging problem. Since the problem is discrete and thus non-convex, we employ a customized box algorithm to characterize the Pareto frontier. The Pareto frontier is then used as a benchmark to evaluate the performance of the standard VMERGE algorithm as well as two other similar heuristics. We test the exact and heuristic merging approaches on a pancreas and a prostate cancer case. For both cases, the shape of the Pareto frontier suggests that starting from a high-quality plan, we can obtain efficient VMAT plans through merging neighboring fluence maps without substantially deviating from the initial dose distribution. The trade-off curves obtained by the various heuristics are contrasted and shown to all be equally capable of initial plan simplifications, but to deviate in quality for more drastic efficiency improvements. This work presents a network optimization approach to the merging problem. Contrasting the trade-off curves of the merging
Noise-dependent optimal strategies for quantum metrology
Huang, Zixin; Macchiavello, Chiara; Maccone, Lorenzo
2018-03-01
For phase estimation using qubits, we show that for some noise channels, the optimal entanglement-assisted strategy depends on the noise level. We note that there is a nontrivial crossover between the parallel-entangled strategy and the ancilla-assisted strategy: in the former the probes are all entangled; in the latter the probes are entangled with a noiseless ancilla but not among themselves. The transition can be explained by the fact that separable states are more robust against noise and therefore are optimal in the high-noise limit, but they are in turn outperformed by ancilla-assisted ones.
Optimal intermittent search strategies: smelling the prey
International Nuclear Information System (INIS)
Revelli, J A; Wio, H S; Rojo, F; Budde, C E
2010-01-01
We study the kinetics of the search of a single fixed target by a searcher/walker that performs an intermittent random walk, characterized by different states of motion. In addition, we assume that the walker has the ability to detect the scent left by the prey/target in its surroundings. Our results, in agreement with intuition, indicate that the prey's survival probability could be strongly reduced (increased) if the predator is attracted (or repelled) by the trace left by the prey. We have also found that, for a positive trace (the predator is guided towards the prey), increasing the inhomogeneity's size reduces the prey's survival probability, while the optimal value of α (the parameter that regulates intermittency) ceases to exist. The agreement between theory and numerical simulations is excellent.
Optimal intermittent search strategies: smelling the prey
Energy Technology Data Exchange (ETDEWEB)
Revelli, J A; Wio, H S [Instituto de Fisica de Cantabria, Universidad de Cantabria and CSIC, E-39005 Santander (Spain); Rojo, F; Budde, C E [Fa.M.A.F., Universidad Nacional de Cordoba, Ciudad Universitaria, X5000HUA Cordoba (Argentina)
2010-05-14
We study the kinetics of the search of a single fixed target by a searcher/walker that performs an intermittent random walk, characterized by different states of motion. In addition, we assume that the walker has the ability to detect the scent left by the prey/target in its surroundings. Our results, in agreement with intuition, indicate that the prey's survival probability could be strongly reduced (increased) if the predator is attracted (or repelled) by the trace left by the prey. We have also found that, for a positive trace (the predator is guided towards the prey), increasing the inhomogeneity's size reduces the prey's survival probability, while the optimal value of {alpha} (the parameter that regulates intermittency) ceases to exist. The agreement between theory and numerical simulations is excellent.
Zhang, J.; Lei, X.; Liu, P.; Wang, H.; Li, Z.
2017-12-01
Flood control operation of multi-reservoir systems such as parallel reservoirs and hybrid reservoirs often suffer from complex interactions and trade-off among tributaries and the mainstream. The optimization of such systems is computationally intensive due to nonlinear storage curves, numerous constraints and complex hydraulic connections. This paper aims to derive the optimal flood control operating rules based on the trade-off among tributaries and the mainstream using a new algorithm known as weighted non-dominated sorting genetic algorithm II (WNSGA II). WNSGA II could locate the Pareto frontier in non-dominated region efficiently due to the directed searching by weighted crowding distance, and the results are compared with those of conventional operating rules (COR) and single objective genetic algorithm (GA). Xijiang river basin in China is selected as a case study, with eight reservoirs and five flood control sections within four tributaries and the mainstream. Furthermore, the effects of inflow uncertainty have been assessed. Results indicate that: (1) WNSGA II could locate the non-dominated solutions faster and provide better Pareto frontier than the traditional non-dominated sorting genetic algorithm II (NSGA II) due to the weighted crowding distance; (2) WNSGA II outperforms COR and GA on flood control in the whole basin; (3) The multi-objective operating rules from WNSGA II deal with the inflow uncertainties better than COR. Therefore, the WNSGA II can be used to derive stable operating rules for large-scale reservoir systems effectively and efficiently.
Optimal Inspection and Maintenance Strategies for Structural Systems
DEFF Research Database (Denmark)
Sommer, A. M.
The aim of this thesis is to give an overview of conventional and optimal reliability-based inspection and maintenance strategies and to examine for specific structures how the cost can be reduced and/or the safety can be improved by using optimal reliability-based inspection strategies....... For structures with several almost similar components it is suggested that individual inspection strategies should be determined for each component or a group of components based on the reliability of the actual component. The benefit of this procedure is assessed in connection with the structures considered....... Furthermore, in relation to the calculations performed the intention is to modify an existing program for determination of optimal inspection strategies. The main purpose of inspection and maintenance of structural systems is to prevent or delay damage or deterioration to protect people, environment...
Mahata, Gour Chandra
2015-09-01
In practice, the supplier often offers the retailers a trade credit period and the retailer in turn provides a trade credit period to her/his customer to stimulate sales and reduce inventory. From the retailer's perspective, granting trade credit not only increases sales and revenue but also increases opportunity cost (i.e., the capital opportunity loss during credit period) and default risk (i.e., the percentage that the customer will not be able to pay off his/her debt obligations). Hence, how to determine credit period is increasingly recognized as an important strategy to increase retailer's profitability. Also, the selling items such as fruits, fresh fishes, gasoline, photographic films, pharmaceuticals and volatile liquids deteriorate continuously due to evaporation, obsolescence and spoilage. In this paper, we propose an economic order quantity model for the retailer where (1) the supplier provides an up-stream trade credit and the retailer also offers a down-stream trade credit, (2) the retailer's down-stream trade credit to the buyer not only increases sales and revenue but also opportunity cost and default risk, and (3) the selling items are perishable. Under these conditions, we model the retailer's inventory system as a profit maximization problem to determine the retailer's optimal replenishment decisions under the supply chain management. We then show that the retailer's optimal credit period and cycle time not only exist but also are unique. We deduce some previously published results of other researchers as special cases. Finally, we use some numerical examples to illustrate the theoretical results.
Trading strategies modeling in Colombian power market using artificial intelligence techniques
International Nuclear Information System (INIS)
Moreno, Julian
2009-01-01
The aim of this paper is to present a model based on fuzzy logic and machine learning in order to maximize the profits of Colombian energy trade agents according to their risk profile. The model has two parts, the first one is a fuzzy expert system that gives a recommendation about the trade strategy these agents should follow, and whose definition depends mainly on market conditions. The second one is a reinforced learning mechanism with which the agents 'learn' when they perceive the consequences of their actions, so they modify such actions looking for a reward not just in short but also in long-term. The whole model is validated using actual data as well as a simulation approach using synthetic time series for some relevant variables as hydraulic availability, energy pool price and bilateral contracts price. (author)
Trading strategies modeling in Colombian power market using artificial intelligence techniques
Energy Technology Data Exchange (ETDEWEB)
Moreno, Julian [Escuela de Sistemas, Universidad Nacional de Colombia, Carrera 80 No. 65-223 Bloque M8A Medellin (Colombia)
2009-03-15
The aim of this paper is to present a model based on fuzzy logic and machine learning in order to maximize the profits of Colombian energy trade agents according to their risk profile. The model has two parts, the first one is a fuzzy expert system that gives a recommendation about the trade strategy these agents should follow, and whose definition depends mainly on market conditions. The second one is a reinforced learning mechanism with which the agents 'learn' when they perceive the consequences of their actions, so they modify such actions looking for a reward not just in short but also in long-term. The whole model is validated using actual data as well as a simulation approach using synthetic time series for some relevant variables as hydraulic availability, energy pool price and bilateral contracts price. (author)
Directory of Open Access Journals (Sweden)
Wenzhong Guo
2014-09-01
Full Text Available Mobile security is one of the most fundamental problems in Wireless Sensor Networks (WSNs. The data transmission path will be compromised for some disabled nodes. To construct a secure and reliable network, designing an adaptive route strategy which optimizes energy consumption and network lifetime of the aggregation cost is of great importance. In this paper, we address the reliable data aggregation route problem for WSNs. Firstly, to ensure nodes work properly, we propose a data aggregation route algorithm which improves the energy efficiency in the WSN. The construction process achieved through discrete particle swarm optimization (DPSO saves node energy costs. Then, to balance the network load and establish a reliable network, an adaptive route algorithm with the minimal energy and the maximum lifetime is proposed. Since it is a non-linear constrained multi-objective optimization problem, in this paper we propose a DPSO with the multi-objective fitness function combined with the phenotype sharing function and penalty function to find available routes. Experimental results show that compared with other tree routing algorithms our algorithm can effectively reduce energy consumption and trade off energy consumption and network lifetime.
A proposal of optimal sampling design using a modularity strategy
Simone, A.; Giustolisi, O.; Laucelli, D. B.
2016-08-01
In real water distribution networks (WDNs) are present thousands nodes and optimal placement of pressure and flow observations is a relevant issue for different management tasks. The planning of pressure observations in terms of spatial distribution and number is named sampling design and it was faced considering model calibration. Nowadays, the design of system monitoring is a relevant issue for water utilities e.g., in order to manage background leakages, to detect anomalies and bursts, to guarantee service quality, etc. In recent years, the optimal location of flow observations related to design of optimal district metering areas (DMAs) and leakage management purposes has been faced considering optimal network segmentation and the modularity index using a multiobjective strategy. Optimal network segmentation is the basis to identify network modules by means of optimal conceptual cuts, which are the candidate locations of closed gates or flow meters creating the DMAs. Starting from the WDN-oriented modularity index, as a metric for WDN segmentation, this paper proposes a new way to perform the sampling design, i.e., the optimal location of pressure meters, using newly developed sampling-oriented modularity index. The strategy optimizes the pressure monitoring system mainly based on network topology and weights assigned to pipes according to the specific technical tasks. A multiobjective optimization minimizes the cost of pressure meters while maximizing the sampling-oriented modularity index. The methodology is presented and discussed using the Apulian and Exnet networks.
Optimal reactor strategy for commercializing fast breeder reactors
International Nuclear Information System (INIS)
Yamaji, Kenji; Nagano, Koji
1988-01-01
In this paper, a fuel cycle optimization model developed for analyzing the condition of selecting fast breeder reactors in the optimal reactor strategy is described. By dividing the period of planning, 1966-2055, into nine ten-year periods, the model was formulated as a compact linear programming model. With the model, the best mix of reactor types as well as the optimal timing of reprocessing spent fuel from LWRs to minimize the total cost were found. The results of the analysis are summarized as follows. Fast breeder reactors could be introduced in the optimal strategy when they can economically compete with LWRs with 30 year storage of spent fuel. In order that fast breeder reactors monopolize the new reactor market after the achievement of their technical availability, their capital cost should be less than 0.9 times as much as that of LWRs. When a certain amount of reprocessing commitment is assumed, the condition of employing fast breeder reactors in the optimal strategy is mitigated. In the optimal strategy, reprocessing is done just to meet plutonium demand, and the storage of spent fuel is selected to adjust the mismatch of plutonium production and utilization. The price hike of uranium ore facilitates the commercial adoption of fast breeder reactors. (Kako, I.)
Optimal Portfolio Strategy under Rolling Economic Maximum Drawdown Constraints
Directory of Open Access Journals (Sweden)
Xiaojian Yu
2014-01-01
Full Text Available This paper deals with the problem of optimal portfolio strategy under the constraints of rolling economic maximum drawdown. A more practical strategy is developed by using rolling Sharpe ratio in computing the allocation proportion in contrast to existing models. Besides, another novel strategy named “REDP strategy” is further proposed, which replaces the rolling economic drawdown of the portfolio with the rolling economic drawdown of the risky asset. The simulation tests prove that REDP strategy can ensure the portfolio to satisfy the drawdown constraint and outperforms other strategies significantly. An empirical comparison research on the performances of different strategies is carried out by using the 23-year monthly data of SPTR, DJUBS, and 3-month T-bill. The investment cases of single risky asset and two risky assets are both studied in this paper. Empirical results indicate that the REDP strategy successfully controls the maximum drawdown within the given limit and performs best in both return and risk.
Directory of Open Access Journals (Sweden)
Yang Sun
2018-01-01
Full Text Available Using Pareto optimization in Multi-Objective Reinforcement Learning (MORL leads to better learning results for network defense games. This is particularly useful for network security agents, who must often balance several goals when choosing what action to take in defense of a network. If the defender knows his preferred reward distribution, the advantages of Pareto optimization can be retained by using a scalarization algorithm prior to the implementation of the MORL. In this paper, we simulate a network defense scenario by creating a multi-objective zero-sum game and using Pareto optimization and MORL to determine optimal solutions and compare those solutions to different scalarization approaches. We build a Pareto Defense Strategy Selection Simulator (PDSSS system for assisting network administrators on decision-making, specifically, on defense strategy selection, and the experiment results show that the Satisficing Trade-Off Method (STOM scalarization approach performs better than linear scalarization or GUESS method. The results of this paper can aid network security agents attempting to find an optimal defense policy for network security games.
The end of a successful stage. Fta's in Chile's trade strategy
Dingemans, Alfonso
2016-01-01
La estrategia comercial chilena, basada en mejorar el acceso a los mercados internacionales se considera exitosa. Pero aunque el crecimiento económico de los últimos treinta años es impresionante, no se logró diversificar la estructura productiva. Se abre una nueva etapa donde la estrategia comercial se debe enfocar en la innovación, para lo cual se requiere revaluar el papel del Estado en el mercado y abandonar las políticas estrictamente horizontales. Chile’s trade strategy, based on imp...
Drechsler, Martin
2017-02-01
Auctions have been proposed as alternatives to payments for environmental services when spatial interactions and costs are better known to landowners than to the conservation agency (asymmetric information). Recently, an auction scheme was proposed that delivers optimal conservation in the sense that social welfare is maximized. I examined the social welfare and the budget efficiency delivered by this scheme, where social welfare represents the difference between the monetized ecological benefit and the conservation cost incurred to the landowners and budget efficiency is defined as maximizing the ecological benefit for a given conservation budget. For the analysis, I considered a stylized landscape with land patches that can be used for agriculture or conservation. The ecological benefit was measured by an objective function that increases with increasing number and spatial aggregation of conserved land patches. I compared the social welfare and the budget efficiency of the auction scheme with an agglomeration payment, a policy scheme that considers spatial interactions and that was proposed recently. The auction delivered a higher level of social welfare than the agglomeration payment. However, the agglomeration payment was more efficient budgetarily than the auction, so the comparative performances of the 2 schemes depended on the chosen policy criterion-social welfare or budget efficiency. Both policy criteria are relevant for conservation. Which one should be chosen depends on the problem at hand, for example, whether social preferences should be taken into account in the decision of how much money to invest in conservation or whether the available conservation budget is strictly limited. © 2016 Society for Conservation Biology.
Roy, S. G.; Gold, A.; Uchida, E.; McGreavy, B.; Smith, S. M.; Wilson, K.; Blachly, B.; Newcomb, A.; Hart, D.; Gardner, K.
2017-12-01
Dam removal has become a cornerstone of environmental restoration practice in the United States. One outcome of dam removal that has received positive attention is restored access to historic habitat for sea-run fisheries, providing a crucial gain in ecosystem resilience. But dams also provide stakeholders with valuable services, and uncertain socio-ecological outcomes can arise if there is not careful consideration of the basin scale trade offs caused by dam removal. In addition to fisheries, dam removals can significantly affect landscape nutrient flux, municipal water storage, recreational use of lakes and rivers, property values, hydroelectricity generation, the cultural meaning of dams, and many other river-based ecosystem services. We use a production possibility frontiers approach to explore dam decision scenarios and opportunities for trading between ecosystem services that are positively or negatively affected by dam removal in New England. Scenarios that provide efficient trade off potentials are identified using a multiobjective genetic algorithm. Our results suggest that for many river systems, there is a significant potential to increase the value of fisheries and other ecosystem services with minimal dam removals, and further increases are possible by including decisions related to dam operations and physical modifications. Run-of-river dams located near the head of tide are often found to be optimal for removal due to low hydroelectric capacity and high impact on fisheries. Conversely, dams with large impoundments near a river's headwaters can be less optimal for dam removal because their value as nitrogen sinks often outweighs the potential value for fisheries. Hydropower capacity is negatively impacted by dam removal but there are opportunities to meet or exceed lost capacity by upgrading preserved hydropower dams. Improving fish passage facilities for dams that are critical for safety or water storage can also reduce impacts on fisheries. Our
Optimal generator bidding strategies for power and ancillary services
Morinec, Allen G.
As the electric power industry transitions to a deregulated market, power transactions are made upon price rather than cost. Generator companies are interested in maximizing their profits rather than overall system efficiency. A method to equitably compensate generation providers for real power, and ancillary services such as reactive power and spinning reserve, will ensure a competitive market with an adequate number of suppliers. Optimizing the generation product mix during bidding is necessary to maximize a generator company's profits. The objective of this research work is to determine and formulate appropriate optimal bidding strategies for a generation company in both the energy and ancillary services markets. These strategies should incorporate the capability curves of their generators as constraints to define the optimal product mix and price offered in the day-ahead and real time spot markets. In order to achieve such a goal, a two-player model was composed to simulate market auctions for power generation. A dynamic game methodology was developed to identify Nash Equilibria and Mixed-Strategy Nash Equilibria solutions as optimal generation bidding strategies for two-player non-cooperative variable-sum matrix games with incomplete information. These games integrated the generation product mix of real power, reactive power, and spinning reserve with the generators's capability curves as constraints. The research includes simulations of market auctions, where strategies were tested for generators with different unit constraints, costs, types of competitors, strategies, and demand levels. Studies on the capability of large hydrogen cooled synchronous generators were utilized to derive useful equations that define the exact shape of the capability curve from the intersections of the arcs defined by the centers and radial vectors of the rotor, stator, and steady-state stability limits. The available reactive reserve and spinning reserve were calculated given a
Application of optimal interation strategies to diffusion theory calculations
International Nuclear Information System (INIS)
Jones, R.B.
1978-01-01
The geometric interpretation of optimal (minimum computational time) iteration strategies is applied to one- and two-group, two-dimensional diffusion-theory calculations. The method is a ''spectral/time balance'' technique which weighs the convergence enhancement of the inner iteration procedure with that of the outer iteration loop and the time required to reconstruct the source. The diffusion-theory option of the discrete-ordinates transport code DOT3.5 was altered to incorporate the theoretical inner/outer decision logic. For the two-dimensional configuration considered, the optimal strategies reduced the total number of iterations performed for a given error criterion
Optimization Under Uncertainty for Wake Steering Strategies: Preprint
Energy Technology Data Exchange (ETDEWEB)
Quick, Julian [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Annoni, Jennifer [National Renewable Energy Laboratory (NREL), Golden, CO (United States); King, Ryan N [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Dykes, Katherine L [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Fleming, Paul A [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ning, Andrew [Brigham Young University
2017-05-01
Wind turbines in a wind power plant experience significant power losses because of aerodynamic interactions between turbines. One control strategy to reduce these losses is known as 'wake steering,' in which upstream turbines are yawed to direct wakes away from downstream turbines. Previous wake steering research has assumed perfect information, however, there can be significant uncertainty in many aspects of the problem, including wind inflow and various turbine measurements. Uncertainty has significant implications for performance of wake steering strategies. Consequently, the authors formulate and solve an optimization under uncertainty (OUU) problem for finding optimal wake steering strategies in the presence of yaw angle uncertainty. The OUU wake steering strategy is demonstrated on a two-turbine test case and on the utility-scale, offshore Princess Amalia Wind Farm. When we accounted for yaw angle uncertainty in the Princess Amalia Wind Farm case, inflow-direction-specific OUU solutions produced between 0% and 1.4% more power than the deterministically optimized steering strategies, resulting in an overall annual average improvement of 0.2%. More importantly, the deterministic optimization is expected to perform worse and with more downside risk than the OUU result when realistic uncertainty is taken into account. Additionally, the OUU solution produces fewer extreme yaw situations than the deterministic solution.
Networks that optimize a trade-off between efficiency and dynamical resilience
International Nuclear Information System (INIS)
Brede, Markus; Vries, Bert J.M. de
2009-01-01
In this Letter we study networks that have been optimized to realize a trade-off between communication efficiency and dynamical resilience. While the first is related to the average shortest pathlength, we argue that the second can be measured by the largest eigenvalue of the adjacency matrix of the network. Best efficiency is realized in star-like configurations, while enhanced resilience is related to the avoidance of short loops and degree homogeneity. Thus crucially, very efficient networks are not resilient while very resilient networks lack in efficiency. Networks that realize a trade-off between both limiting cases exhibit core-periphery structures, where the average degree of core nodes decreases but core size increases as the weight is gradually shifted from a strong requirement for efficiency and limited resilience towards a smaller requirement for efficiency and a strong demand for resilience. We argue that both, efficiency and resilience are important requirements for network design and highlight how networks can be constructed that allow for both.
Optimal football strategies: AC Milan versus FC Barcelona
Papahristodoulou, Christos
2012-01-01
In a recent UEFA Champions League game between AC Milan and FC Barcelona, played in Italy (final score 2-3), the collected match statistics, classified into four offensive and two defensive strategies, were in favour of FC Barcelona (by 13 versus 8 points). The aim of this paper is to examine to what extent the optimal game strategies derived from some deterministic, possibilistic, stochastic and fuzzy LP models would improve the payoff of AC Milan at the cost of FC Barcelona.
Directory of Open Access Journals (Sweden)
S. R. Singh
2014-01-01
Full Text Available Trade credit is the most succeeding economic phenomenon which is used by the supplier for encouraging the retailers to buy more quantity. In this article, a mathematical model with stock dependent demand and deterioration is developed to investigate the retailer’s optimal inventory policy under the scheme of permissible delay in payment. It is assumed that defective items are produced during the production process and delay period is progressive. The objective is to minimize the total average cost of the system. To exemplify hypothesis of the proposed model numerical examples and sensitivity analysis are provided. Finally, the convexities of the cost functions and the effects of changing parameters are represented through the graphs.
Fears and Strategies: The EU, China and their Free Trade Agreements in East Asia
Directory of Open Access Journals (Sweden)
Maria Garcia
2010-11-01
Full Text Available The stalemate at the WTO Doha Round sparked a new wave of bilateral preferential and free trade agreements (FTAs. Nowhere has this been more evident than in the Asia Pacific region. Whilst there are economic reasons for FTAs, these are less efficient and more complex than multilateral agreements and most have had fairly small economic impacts. This paper compares the strategies of a newcomer to the FTA arena, China, and the actor with the most cumulative FTAs, the EU. It ponders on the different reasons informing their strategies and on how these may be affecting each other. It also considers the role of competitive fears and competitive diffusion in the formulation of their policies.
Directory of Open Access Journals (Sweden)
Liang Liu
2015-04-01
Full Text Available Water emission trading (WET is promising in sustainable development strategy. However, low participation impedes its development. We develop an evolutionary game model of two enterprise populations’ dynamics and stability in the decision-making behavior process. Due to the different perceived value of certain permits, enterprises choose H strategy (bidding for permit or D strategy (not bidding. External factors are simplified according to three categories: rH-bidding related cost, G-price and F-penalty. Participation increase equals reaching point (H,H in the model and is treated as an evolutionarily stable strategy (ESS. We build a system dynamics model on AnyLogic 7.1.1 to simulate the aforementioned game and draw four conclusions: (1 to reach ESS more quickly, we need to minimize the bidding related cost rH and price G, but regulate the heavy penalty F; (2 an ESS can be significantly transformed, such as from (D,D to (H,H by regulating rH, G and F accordingly; (3 the initial choice of strategy is essential to the final result; (4 if participation seems stable but unsatisfying, it is important to check whether it is a saddle point and adjust external factors accordingly. The findings benefit both water management practice and further research.
Directory of Open Access Journals (Sweden)
Teplova T. V.
2014-09-01
Full Text Available Momentum-effect has many interpretations in the practice of investing and in understanding of anomalies in asset prices. We consider a Cross-Sectional momentum effects and the corresponding two medium-term (3 months or more trading strategies that are different from the trend following rules for individual assets. We tested four hypothesis deals with cross-sectional momentum effect on the Russian stock market and the possibility of building a self-financing (long-short trading strategy at three time horizon (stock market growth from 2004 until mid-2008, financial crisis and post-crisis periods. It is shown that for the Russian market cross-sectional momentum strategy with partly rebalanced portfolio maximizing portfolio return (134 stocks listed from 2004 to 2014 in the few Russian stock exchanges should be based on the three-month formation period and three-month holding period periods (3/1/3. We have identified elements of profit-maximizing momentum strategy: three time windows and determinants of assets. Monthly average return of arbitrage strategy is estimated at 1.5 % for 134 common shares. Implementation of the strategy for the post-crisis period does not allow to maximize profit. For 6 month and more investment windows it gets the advantage of reverse strategy (opening long positions in stocks with low investment results and short position for assets with high relative returns. Fundamental parameters of the issuer (size of companies like market capitalization and two measures of liquidity (trading activity and transaction costs like bid-ask spread are significant to maximize portfolio performance (we prove the growth of monthly average return ranging from 1.5 to 2.5 %. We find that size and liquidity control momentum strategy can earn positive profits in Russian stock market, larger than naïve momentum.
Optimal decentralized valley-filling charging strategy for electric vehicles
International Nuclear Information System (INIS)
Zhang, Kangkang; Xu, Liangfei; Ouyang, Minggao; Wang, Hewu; Lu, Languang; Li, Jianqiu; Li, Zhe
2014-01-01
Highlights: • An implementable charging strategy is developed for electric vehicles connected to a grid. • A two-dimensional pricing scheme is proposed to coordinate charging behaviors. • The strategy effectively works in decentralized way but achieves the systematic valley filling. • The strategy allows device-level charging autonomy, and does not require a bidirectional communication/control network. • The strategy can self-correct when confronted with adverse factors. - Abstract: Uncoordinated charging load of electric vehicles (EVs) increases the peak load of the power grid, thereby increasing the cost of electricity generation. The valley-filling charging scenario offers a cheaper alternative. This study proposes a novel decentralized valley-filling charging strategy, in which a day-ahead pricing scheme is designed by solving a minimum-cost optimization problem. The pricing scheme can be broadcasted to EV owners, and the individual charging behaviors can be indirectly coordinated. EV owners respond to the pricing scheme by autonomously optimizing their individual charge patterns. This device-level response induces a valley-filling effect in the grid at the system level. The proposed strategy offers three advantages: coordination (by the valley-filling effect), practicality (no requirement for a bidirectional communication/control network between the grid and EV owners), and autonomy (user control of EV charge patterns). The proposed strategy is validated in simulations of typical scenarios in Beijing, China. According to the results, the strategy (1) effectively achieves the valley-filling charging effect at 28% less generation cost than the uncoordinated charging strategy, (2) is robust to several potential affecters of the valley-filling effect, such as (system-level) inaccurate parameter estimation and (device-level) response capability and willingness (which cause less than 2% deviation in the minimal generation cost), and (3) is compatible with
Multi-objective optimization of cellular scanning strategy in selective laser melting
DEFF Research Database (Denmark)
Ahrari, Ali; Deb, Kalyanmoy; Mohanty, Sankhya
2017-01-01
The scanning strategy for selective laser melting - an additive manufacturing process - determines the temperature fields during the manufacturing process, which in turn affects residual stresses and distortions, two of the main sources of process-induced defects. The goal of this study is to dev......The scanning strategy for selective laser melting - an additive manufacturing process - determines the temperature fields during the manufacturing process, which in turn affects residual stresses and distortions, two of the main sources of process-induced defects. The goal of this study......, the problem is a combination of combinatorial and choice optimization, which makes the problem difficult to solve. On a process simulation domain consisting of 32 cells, our multi-objective evolutionary method is able to find a set of trade-off solutions for the defined conflicting objectives, which cannot...
DEFF Research Database (Denmark)
Izosimov, Viacheslav; Pop, Paul; Eles, Petru
2012-01-01
In this article, we propose a strategy for the synthesis of fault-tolerant schedules and for the mapping of fault-tolerant applications. Our techniques handle transparency/performance trade-offs and use the faultoccurrence information to reduce the overhead due to fault tolerance. Processes...... and messages are statically scheduled, and we use process reexecution for recovering from multiple transient faults. We propose a finegrained transparent recovery, where the property of transparency can be selectively applied to processes and messages. Transparency hides the recovery actions in a selected part...... of the application so that they do not affect the schedule of other processes and messages. While leading to longer schedules, transparent recovery has the advantage of both improved debuggability and less memory needed to store the faulttolerant schedules....
Directory of Open Access Journals (Sweden)
Craig George Leslie Hopf
2015-12-01
Full Text Available This paper’s primary alternative hypothesis is Ha: profitable exchange-traded horserace betting fund with deterministic payoff exists for acceptable institutional portfolio return—risk. The primary hypothesis challenges the semi-strong efficient market hypothesis applied to horse race wagering. An optimal deterministic betting model (DBM is derived from the existing stochastic model fundamentals, mathematical pooling principles, and new theorem. The exchange-traded betting fund (ETBF is derived from force of interest first principles. An ETBF driven by DBM processes conjointly defines the research’s betting strategy. Alpha is excess return above financial benchmark, and invokes betting strategy alpha that is composed of model alpha and fund alpha. The results and analysis from statistical testing of a global stratified data sample of three hundred galloper horse races accepted at the ninety-five percent confidence-level positive betting strategy alpha, to endorse an exchange-traded horse race betting fund with deterministic payoff into financial market.
A Competitive and Experiential Assignment in Search Engine Optimization Strategy
Clarke, Theresa B.; Clarke, Irvine, III
2014-01-01
Despite an increase in ad spending and demand for employees with expertise in search engine optimization (SEO), methods for teaching this important marketing strategy have received little coverage in the literature. Using Bloom's cognitive goals hierarchy as a framework, this experiential assignment provides a process for educators who may be new…
Optimal portfolio strategies under a shortfall constraint | Akume ...
African Journals Online (AJOL)
We impose dynamically, a shortfall constraint in terms of Tail Conditional Expectation on the portfolio selection problem in continuous time, in order to obtain optimal strategies. The nancial market is assumed to comprise n risky assets driven by geometric Brownian motion and one risk-free asset. The method of Lagrange ...
Optimal energy management strategy for battery powered electric vehicles
International Nuclear Information System (INIS)
Xi, Jiaqi; Li, Mian; Xu, Min
2014-01-01
Highlights: • The power usage for battery-powered electrical vehicles with in-wheel motors is maximized. • The battery and motor dynamics are examined emphasized on the power conversion and utilization. • The optimal control strategy is derived and verified by simulations. • An analytic expression of the optimal operating point is obtained. - Abstract: Due to limited energy density of batteries, energy management has always played a critical role in improving the overall energy efficiency of electric vehicles. In this paper, a key issue within the energy management problem will be carefully tackled, i.e., maximizing the power usage of batteries for battery-powered electrical vehicles with in-wheel motors. To this end, the battery and motor dynamics will be thoroughly examined with particular emphasis on the power conversion and power utilization. The optimal control strategy will then be derived based on the analysis. One significant contribution of this work is that an analytic expression for the optimal operating point in terms of the component and environment parameters can be obtained. Owing to this finding, the derived control strategy is also rendered a simple structure for real-time implementation. Simulation results demonstrate that the proposed strategy works both adaptively and robustly under different driving scenarios
Validation of optimization strategies using the linear structured production chains
Kusiak, Jan; Morkisz, Paweł; Oprocha, Piotr; Pietrucha, Wojciech; Sztangret, Łukasz
2017-06-01
Different optimization strategies applied to sequence of several stages of production chains were validated in this paper. Two benchmark problems described by ordinary differential equations (ODEs) were considered. A water tank and a passive CR-RC filter were used as the exemplary objects described by the first and the second order differential equations, respectively. Considered in the work optimization problems serve as the validators of strategies elaborated by the Authors. However, the main goal of research is selection of the best strategy for optimization of two real metallurgical processes which will be investigated in an on-going projects. The first problem will be the oxidizing roasting process of zinc sulphide concentrate where the sulphur from the input concentrate should be eliminated and the minimal concentration of sulphide sulphur in the roasted products has to be achieved. Second problem will be the lead refining process consisting of three stages: roasting to the oxide, oxide reduction to metal and the oxidizing refining. Strategies, which appear the most effective in considered benchmark problems will be candidates for optimization of the mentioned above industrial processes.
An optimal inspection strategy for randomly failing equipment
International Nuclear Information System (INIS)
Chelbi, Anis; Ait-Kadi, Daoud
1999-01-01
This paper addresses the problem of generating optimal inspection strategies for randomly failing equipment where imminent failure is not obvious and can only be detected through inspection. Inspections are carried out following a condition-based procedure. The equipment is replaced if it has failed or if it shows imminent signs of failure. The latter state is indicated by measuring certain predetermined control parameters during inspection. Costs are associated with inspection, idle time and preventive or corrective actions. An optimal inspection strategy is defined as the inspection sequence minimizing the expected total cost per time unit over an infinite span. A mathematical model and a numerical algorithm are developed to generate an optimal inspection sequence. As a practical example, the model is applied to provide a machine tool operator with a time sequence for inspecting the cutting tool. The tool life time distribution and the trend of one control parameter defining its actual condition are supposed to be known
Optimal Energy Control Strategy Design for a Hybrid Electric Vehicle
Directory of Open Access Journals (Sweden)
Yuan Zou
2013-01-01
Full Text Available A heavy-duty parallel hybrid electric truck is modeled, and its optimal energy control is studied in this paper. The fundamental architecture of the parallel hybrid electric truck is modeled feed-forwardly, together with necessary dynamic features of subsystem or components. Dynamic programming (DP technique is adopted to find the optimal control strategy including the gear-shifting sequence and the power split between the engine and the motor subject to a battery SOC-sustaining constraint. Improved control rules are extracted from the DP-based control solution, forming near-optimal control strategies. Simulation results demonstrate that a significant improvement on the fuel economy can be achieved in the heavy-duty vehicle cycle from the natural driving statistics.
Online gaming for learning optimal team strategies in real time
Hudas, Gregory; Lewis, F. L.; Vamvoudakis, K. G.
2010-04-01
This paper first presents an overall view for dynamical decision-making in teams, both cooperative and competitive. Strategies for team decision problems, including optimal control, zero-sum 2-player games (H-infinity control) and so on are normally solved for off-line by solving associated matrix equations such as the Riccati equation. However, using that approach, players cannot change their objectives online in real time without calling for a completely new off-line solution for the new strategies. Therefore, in this paper we give a method for learning optimal team strategies online in real time as team dynamical play unfolds. In the linear quadratic regulator case, for instance, the method learns the Riccati equation solution online without ever solving the Riccati equation. This allows for truly dynamical team decisions where objective functions can change in real time and the system dynamics can be time-varying.
Artificial root foraging optimizer algorithm with hybrid strategies
Directory of Open Access Journals (Sweden)
Yang Liu
2017-02-01
Full Text Available In this work, a new plant-inspired optimization algorithm namely the hybrid artificial root foraging optimizion (HARFO is proposed, which mimics the iterative root foraging behaviors for complex optimization. In HARFO model, two innovative strategies were developed: one is the root-to-root communication strategy, which enables the individual exchange information with each other in different efficient topologies that can essentially improve the exploration ability; the other is co-evolution strategy, which can structure the hierarchical spatial population driven by evolutionary pressure of multiple sub-populations that ensure the diversity of root population to be well maintained. The proposed algorithm is benchmarked against four classical evolutionary algorithms on well-designed test function suites including both classical and composition test functions. Through the rigorous performance analysis that of all these tests highlight the significant performance improvement, and the comparative results show the superiority of the proposed algorithm.
Energy Technology Data Exchange (ETDEWEB)
Leimbach, Marian [Potsdam-Institut fuer Klimafolgenforschung e.V., Potsdam (Germany); Eisenack, Klaus [Oldenburg Univ. (Germany). Dept. of Economics and Statistics
2008-11-15
In this paper we present an algorithm that deals with trade interactions within a multi-region model. In contrast to traditional approaches this algorithm is able to handle spillover externalities. Technological spillovers are expected to foster the diffusion of new technologies, which helps to lower the cost of climate change mitigation. We focus on technological spillovers which are due to capital trade. The algorithm of finding a pareto-optimal solution in an intertemporal framework is embedded in a decomposed optimization process. The paper analyzes convergence and equilibrium properties of this algorithm. In the final part of the paper, we apply the algorithm to investigate possible impacts of technological spillovers. While benefits of technological spillovers are significant for the capital-importing region, benefits for the capital-exporting region depend on the type of regional disparities and the resulting specialization and terms-of-trade effects. (orig.)
Directory of Open Access Journals (Sweden)
Huan-huan Li
2015-01-01
Full Text Available Wind power has the characteristics of randomness and intermittence, which influences power system safety and stable operation. To alleviate the effect of wind power grid connection and improve power system’s wind power consumptive capability, this paper took emission trading and energy storage system into consideration and built an optimization model for thermal-wind power system and energy storage systems collaborative scheduling. A simulation based on 10 thermal units and wind farms with 2800 MW installed capacity verified the correctness of the models put forward by this paper. According to the simulation results, the introduction of carbon emission trading can improve wind power consumptive capability and cut down the average coal consumption per unit of power. The introduction of energy storage system can smooth wind power output curve and suppress power fluctuations. The optimization effects achieve the best when both of carbon emission trading and energy storage system work at the same time.
Directory of Open Access Journals (Sweden)
Juanjuan Qin
2014-01-01
Full Text Available This paper investigates the optimal replenishment policy for the retailer with the ramp type demand and demand dependent production rate involving the trade credit financing, which is not reported in the literatures. First, the two inventory models are developed under the above situation. Second, the algorithms are given to optimize the replenishment cycle time and the order quantity for the retailer. Finally, the numerical examples are carried out to illustrate the optimal solutions and the sensitivity analysis is performed. The results show that if the value of production rate is small, the retailer will lower the frequency of putting the orders to cut down the order cost; if the production rate is high, the demand dependent production rate has no effect on the optimal decisions. When the trade credit is less than the growth stage time, the retailer will shorten the replenishment cycle; when it is larger than the breakpoint of the demand, within the maturity stage of the products, the trade credit has no effect on the optimal order cycle and the optimal order quantity.
Takahashi, Kenta; Hara, Ryoichi; Kita, Hiroyuki; Hasegawa, Jun
In recent years, as the deregulation in electric power industry has advanced in many countries, a spot market trading of electricity has been done. Generation companies are allowed to purchase the electricity through the electric power market and supply electric power for their bilateral customers. Under this circumstance, it is important for the generation companies to procure the required electricity with cheaper cost to increase their profit. The market price is volatile since it is determined by bidding between buyer and seller. The pumped storage power plant, one of the storage facilities is promising against such volatile market price since it can produce a profit by purchasing electricity with lower-price and selling it with higher-price. This paper discusses the optimal operation of the pumped storage power plants considering bidding strategy to an uncertain spot market. The volatilities in market price and demand are represented by the Vasicek model in our estimation. This paper also discusses the allocation of operational reserve to the pumped storage power plant.
On the robust optimization to the uncertain vaccination strategy problem
International Nuclear Information System (INIS)
Chaerani, D.; Anggriani, N.; Firdaniza
2014-01-01
In order to prevent an epidemic of infectious diseases, the vaccination coverage needs to be minimized and also the basic reproduction number needs to be maintained below 1. This means that as we get the vaccination coverage as minimum as possible, thus we need to prevent the epidemic to a small number of people who already get infected. In this paper, we discuss the case of vaccination strategy in term of minimizing vaccination coverage, when the basic reproduction number is assumed as an uncertain parameter that lies between 0 and 1. We refer to the linear optimization model for vaccination strategy that propose by Becker and Starrzak (see [2]). Assuming that there is parameter uncertainty involved, we can see Tanner et al (see [9]) who propose the optimal solution of the problem using stochastic programming. In this paper we discuss an alternative way of optimizing the uncertain vaccination strategy using Robust Optimization (see [3]). In this approach we assume that the parameter uncertainty lies within an ellipsoidal uncertainty set such that we can claim that the obtained result will be achieved in a polynomial time algorithm (as it is guaranteed by the RO methodology). The robust counterpart model is presented
On the robust optimization to the uncertain vaccination strategy problem
Energy Technology Data Exchange (ETDEWEB)
Chaerani, D., E-mail: d.chaerani@unpad.ac.id; Anggriani, N., E-mail: d.chaerani@unpad.ac.id; Firdaniza, E-mail: d.chaerani@unpad.ac.id [Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Padjadjaran Indonesia, Jalan Raya Bandung Sumedang KM 21 Jatinangor Sumedang 45363 (Indonesia)
2014-02-21
In order to prevent an epidemic of infectious diseases, the vaccination coverage needs to be minimized and also the basic reproduction number needs to be maintained below 1. This means that as we get the vaccination coverage as minimum as possible, thus we need to prevent the epidemic to a small number of people who already get infected. In this paper, we discuss the case of vaccination strategy in term of minimizing vaccination coverage, when the basic reproduction number is assumed as an uncertain parameter that lies between 0 and 1. We refer to the linear optimization model for vaccination strategy that propose by Becker and Starrzak (see [2]). Assuming that there is parameter uncertainty involved, we can see Tanner et al (see [9]) who propose the optimal solution of the problem using stochastic programming. In this paper we discuss an alternative way of optimizing the uncertain vaccination strategy using Robust Optimization (see [3]). In this approach we assume that the parameter uncertainty lies within an ellipsoidal uncertainty set such that we can claim that the obtained result will be achieved in a polynomial time algorithm (as it is guaranteed by the RO methodology). The robust counterpart model is presented.
Generating optimized stochastic power management strategies for electric car components
Energy Technology Data Exchange (ETDEWEB)
Fruth, Matthias [TraceTronic GmbH, Dresden (Germany); Bastian, Steve [Technische Univ. Dresden (Germany)
2012-11-01
With the increasing prevalence of electric vehicles, reducing the power consumption of car components becomes a necessity. For the example of a novel traffic-light assistance system, which makes speed recommendations based on the expected length of red-light phases, power-management strategies are used to control under which conditions radio communication, positioning systems and other components are switched to low-power (e.g. sleep) or high-power (e.g. idle/busy) states. We apply dynamic power management, an optimization technique well-known from other domains, in order to compute energy-optimal power-management strategies, sometimes resulting in these strategies being stochastic. On the example of the traffic-light assistant, we present a MATLAB/Simulink-implemented framework for the generation, simulation and formal analysis of optimized power-management strategies, which is based on this technique. We study capabilities and limitations of this approach and sketch further applications in the automotive domain. (orig.)
Impact of information cost and switching of trading strategies in an artificial stock market
Liu, Yi-Fang; Zhang, Wei; Xu, Chao; Vitting Andersen, Jørgen; Xu, Hai-Chuan
2014-08-01
This paper studies the switching of trading strategies and its effect on the market volatility in a continuous double auction market. We describe the behavior when some uninformed agents, who we call switchers, decide whether or not to pay for information before they trade. By paying for the information they behave as informed traders. First we verify that our model is able to reproduce some of the stylized facts in real financial markets. Next we consider the relationship between switching and the market volatility under different structures of investors. We find that there exists a positive relationship between the market volatility and the percentage of switchers. We therefore conclude that the switchers are a destabilizing factor in the market. However, for a given fixed percentage of switchers, the proportion of switchers that decide to buy information at a given moment of time is negatively related to the current market volatility. In other words, if more agents pay for information to know the fundamental value at some time, the market volatility will be lower. This is because the market price is closer to the fundamental value due to information diffusion between switchers.
An optimization strategy for a biokinetic model of inhaled radionuclides
International Nuclear Information System (INIS)
Shyr, L.J.; Griffith, W.C.; Boecker, B.B.
1991-01-01
Models for material disposition and dosimetry involve predictions of the biokinetics of the material among compartments representing organs and tissues in the body. Because of a lack of human data for most toxicants, many of the basic data are derived by modeling the results obtained from studies using laboratory animals. Such a biomathematical model is usually developed by adjusting the model parameters to make the model predictions match the measured retention and excretion data visually. The fitting process can be very time-consuming for a complicated model, and visual model selections may be subjective and easily biased by the scale or the data used. Due to the development of computerized optimization methods, manual fitting could benefit from an automated process. However, for a complicated model, an automated process without an optimization strategy will not be efficient, and may not produce fruitful results. In this paper, procedures for, and implementation of, an optimization strategy for a complicated mathematical model is demonstrated by optimizing a biokinetic model for 144Ce in fused aluminosilicate particles inhaled by beagle dogs. The optimized results using SimuSolv were compared to manual fitting results obtained previously using the model simulation software GASP. Also, statistical criteria provided by SimuSolv, such as likelihood function values, were used to help or verify visual model selections
Control strategies for wind farm power optimization: LES study
Ciri, Umberto; Rotea, Mario; Leonardi, Stefano
2017-11-01
Turbines in wind farms operate in off-design conditions as wake interactions occur for particular wind directions. Advanced wind farm control strategies aim at coordinating and adjusting turbine operations to mitigate power losses in such conditions. Coordination is achieved by controlling on upstream turbines either the wake intensity, through the blade pitch angle or the generator torque, or the wake direction, through yaw misalignment. Downstream turbines can be adapted to work in waked conditions and limit power losses, using the blade pitch angle or the generator torque. As wind conditions in wind farm operations may change significantly, it is difficult to determine and parameterize the variations of the coordinated optimal settings. An alternative is model-free control and optimization of wind farms, which does not require any parameterization and can track the optimal settings as conditions vary. In this work, we employ a model-free optimization algorithm, extremum-seeking control, to find the optimal set-points of generator torque, blade pitch and yaw angle for a three-turbine configuration. Large-Eddy Simulations are used to provide a virtual environment to evaluate the performance of the control strategies under realistic, unsteady incoming wind. This work was supported by the National Science Foundation, Grants No. 1243482 (the WINDINSPIRE project) and IIP 1362033 (I/UCRC WindSTAR). TACC is acknowledged for providing computational time.
Directory of Open Access Journals (Sweden)
Grosul Viktoriya A.
2013-11-01
Full Text Available The article justifies a necessity of strategic management of marketing potential of retail trade enterprises. The article develops a general structural and logic scheme of the process of strategic management of the marketing potential of a trade enterprise taking into account specific features of the trade industry. It establishes that the main key issue in the theory of strategic management is argumentation of selection of the basic strategy of development of a subject of economy. It justifies a scientific and methodical approach to selection of the basic strategy of development of a trade enterprise in the process of management of the marketing potential, main stages of which are: assessment of the level of loyalty of external marketing environment; identification of marketing stratagems; and selection of the enterprise development strategy. The article offers to use the model of marketing stratagem, the components of which are policy of management of the marketing potential, strategic market position of the enterprise and level of loyalty of external marketing environment. The article develops an interactive strategic cube of formation of the complex of marketing stratagems on the basis of use of which marketing stratagems for various trade networks of the Kharkiv region are identified and strategies of their further development are justified.
Bio-Mimic Optimization Strategies in Wireless Sensor Networks: A Survey
Adnan, Md. Akhtaruzzaman; Razzaque, Mohammd Abdur; Ahmed, Ishtiaque; Isnin, Ismail Fauzi
2014-01-01
For the past 20 years, many authors have focused their investigations on wireless sensor networks. Various issues related to wireless sensor networks such as energy minimization (optimization), compression schemes, self-organizing network algorithms, routing protocols, quality of service management, security, energy harvesting, etc., have been extensively explored. The three most important issues among these are energy efficiency, quality of service and security management. To get the best possible results in one or more of these issues in wireless sensor networks optimization is necessary. Furthermore, in number of applications (e.g., body area sensor networks, vehicular ad hoc networks) these issues might conflict and require a trade-off amongst them. Due to the high energy consumption and data processing requirements, the use of classical algorithms has historically been disregarded. In this context contemporary researchers started using bio-mimetic strategy-based optimization techniques in the field of wireless sensor networks. These techniques are diverse and involve many different optimization algorithms. As far as we know, most existing works tend to focus only on optimization of one specific issue of the three mentioned above. It is high time that these individual efforts are put into perspective and a more holistic view is taken. In this paper we take a step in that direction by presenting a survey of the literature in the area of wireless sensor network optimization concentrating especially on the three most widely used bio-mimetic algorithms, namely, particle swarm optimization, ant colony optimization and genetic algorithm. In addition, to stimulate new research and development interests in this field, open research issues, challenges and future research directions are highlighted. PMID:24368702
Bio-mimic optimization strategies in wireless sensor networks: a survey.
Adnan, Md Akhtaruzzaman; Abdur Razzaque, Mohammd; Ahmed, Ishtiaque; Isnin, Ismail Fauzi
2013-12-24
For the past 20 years, many authors have focused their investigations on wireless sensor networks. Various issues related to wireless sensor networks such as energy minimization (optimization), compression schemes, self-organizing network algorithms, routing protocols, quality of service management, security, energy harvesting, etc., have been extensively explored. The three most important issues among these are energy efficiency, quality of service and security management. To get the best possible results in one or more of these issues in wireless sensor networks optimization is necessary. Furthermore, in number of applications (e.g., body area sensor networks, vehicular ad hoc networks) these issues might conflict and require a trade-off amongst them. Due to the high energy consumption and data processing requirements, the use of classical algorithms has historically been disregarded. In this context contemporary researchers started using bio-mimetic strategy-based optimization techniques in the field of wireless sensor networks. These techniques are diverse and involve many different optimization algorithms. As far as we know, most existing works tend to focus only on optimization of one specific issue of the three mentioned above. It is high time that these individual efforts are put into perspective and a more holistic view is taken. In this paper we take a step in that direction by presenting a survey of the literature in the area of wireless sensor network optimization concentrating especially on the three most widely used bio-mimetic algorithms, namely, particle swarm optimization, ant colony optimization and genetic algorithm. In addition, to stimulate new research and development interests in this field, open research issues, challenges and future research directions are highlighted.
Automatic CT simulation optimization for radiation therapy: A general strategy.
Li, Hua; Yu, Lifeng; Anastasio, Mark A; Chen, Hsin-Chen; Tan, Jun; Gay, Hiram; Michalski, Jeff M; Low, Daniel A; Mutic, Sasa
2014-03-01
In radiation therapy, x-ray computed tomography (CT) simulation protocol specifications should be driven by the treatment planning requirements in lieu of duplicating diagnostic CT screening protocols. The purpose of this study was to develop a general strategy that allows for automatically, prospectively, and objectively determining the optimal patient-specific CT simulation protocols based on radiation-therapy goals, namely, maintenance of contouring quality and integrity while minimizing patient CT simulation dose. The authors proposed a general prediction strategy that provides automatic optimal CT simulation protocol selection as a function of patient size and treatment planning task. The optimal protocol is the one that delivers the minimum dose required to provide a CT simulation scan that yields accurate contours. Accurate treatment plans depend on accurate contours in order to conform the dose to actual tumor and normal organ positions. An image quality index, defined to characterize how simulation scan quality affects contour delineation, was developed and used to benchmark the contouring accuracy and treatment plan quality within the predication strategy. A clinical workflow was developed to select the optimal CT simulation protocols incorporating patient size, target delineation, and radiation dose efficiency. An experimental study using an anthropomorphic pelvis phantom with added-bolus layers was used to demonstrate how the proposed prediction strategy could be implemented and how the optimal CT simulation protocols could be selected for prostate cancer patients based on patient size and treatment planning task. Clinical IMRT prostate treatment plans for seven CT scans with varied image quality indices were separately optimized and compared to verify the trace of target and organ dosimetry coverage. Based on the phantom study, the optimal image quality index for accurate manual prostate contouring was 4.4. The optimal tube potentials for patient sizes
Automatic CT simulation optimization for radiation therapy: A general strategy
Energy Technology Data Exchange (ETDEWEB)
Li, Hua, E-mail: huli@radonc.wustl.edu; Chen, Hsin-Chen; Tan, Jun; Gay, Hiram; Michalski, Jeff M.; Mutic, Sasa [Department of Radiation Oncology, Washington University, St. Louis, Missouri 63110 (United States); Yu, Lifeng [Department of Radiology, Mayo Clinic, Rochester, Minnesota 55905 (United States); Anastasio, Mark A. [Department of Biomedical Engineering, Washington University, St. Louis, Missouri 63110 (United States); Low, Daniel A. [Department of Radiation Oncology, University of California Los Angeles, Los Angeles, California 90095 (United States)
2014-03-15
Purpose: In radiation therapy, x-ray computed tomography (CT) simulation protocol specifications should be driven by the treatment planning requirements in lieu of duplicating diagnostic CT screening protocols. The purpose of this study was to develop a general strategy that allows for automatically, prospectively, and objectively determining the optimal patient-specific CT simulation protocols based on radiation-therapy goals, namely, maintenance of contouring quality and integrity while minimizing patient CT simulation dose. Methods: The authors proposed a general prediction strategy that provides automatic optimal CT simulation protocol selection as a function of patient size and treatment planning task. The optimal protocol is the one that delivers the minimum dose required to provide a CT simulation scan that yields accurate contours. Accurate treatment plans depend on accurate contours in order to conform the dose to actual tumor and normal organ positions. An image quality index, defined to characterize how simulation scan quality affects contour delineation, was developed and used to benchmark the contouring accuracy and treatment plan quality within the predication strategy. A clinical workflow was developed to select the optimal CT simulation protocols incorporating patient size, target delineation, and radiation dose efficiency. An experimental study using an anthropomorphic pelvis phantom with added-bolus layers was used to demonstrate how the proposed prediction strategy could be implemented and how the optimal CT simulation protocols could be selected for prostate cancer patients based on patient size and treatment planning task. Clinical IMRT prostate treatment plans for seven CT scans with varied image quality indices were separately optimized and compared to verify the trace of target and organ dosimetry coverage. Results: Based on the phantom study, the optimal image quality index for accurate manual prostate contouring was 4.4. The optimal tube
Egg number-egg size: an important trade-off in parasite life history strategies.
Cavaleiro, Francisca I; Santos, Maria J
2014-03-01
Parasites produce from just a few to many eggs of variable size, but our understanding of the factors driving variation in these two life history traits at the intraspecific level is still very fragmentary. This study evaluates the importance of performing multilevel analyses on egg number and egg size, while characterising parasite life history strategies. A total of 120 ovigerous females of Octopicola superba (Copepoda: Octopicolidae) (one sample (n=30) per season) were characterised with respect to different body dimensions (total length; genital somite length) and measures of reproductive effort (fecundity; mean egg diameter; total reproductive effort; mean egg sac length). While endoparasites are suggested to follow both an r- and K-strategy simultaneously, the evidence found in this and other studies suggests that environmental conditions force ectoparasites into one of the two alternatives. The positive and negative skewness of the distributions of fecundity and mean egg diameter, respectively, suggest that O. superba is mainly a K-strategist (i.e. produces a relatively small number of large, well provisioned eggs). Significant sample differences were recorded concomitantly for all body dimensions and measures of reproductive effort, while a general linear model detected a significant influence of season*parasite total length in both egg number and size. This evidence suggests adaptive phenotypic plasticity in body dimensions and size-mediated changes in egg production. Seasonal changes in partitioning of resources between egg number and size resulted in significant differences in egg sac length but not in total reproductive effort. Evidence for a trade-off between egg number and size was found while controlling for a potential confounding effect of parasite total length. However, this trade-off became apparent only at high fecundity levels, suggesting a state of physiological exhaustion. Copyright © 2014 Australian Society for Parasitology Inc. Published
Waterpipe industry products and marketing strategies: analysis of an industry trade exhibition.
Jawad, Mohammed; Nakkash, Rima T; Hawkins, Ben; Akl, Elie A
2015-12-01
Understanding product development and marketing strategies of transnational tobacco companies (TTCs) has been of vital importance in developing an effective tobacco control policy. However, comparatively little is known of the waterpipe tobacco industry, which TTCs have recently entered. This study aimed to gain an understanding of waterpipe tobacco products and marketing strategies by visiting a waterpipe trade exhibition. In April 2014, the first author attended an international waterpipe trade exhibition, recording descriptions of products and collecting all available marketing items. We described the purpose and function of all products, and performed a thematic analysis of messages in marketing material. We classified waterpipe products into four categories and noted product variation within categories. Electronic waterpipe products (which mimic electronic cigarettes) rarely appeared on waterpipe tobacco marketing material, but were displayed just as widely. Claims of reduced harm, safety and quality were paramount on marketing materials, regardless of whether they were promoting consumption products (tobacco, tobacco substitutes), electronic waterpipes or accessories. Waterpipe products are diverse in nature and are marketed as healthy and safe products. Furthermore, the development of electronic waterpipe products appears to be closely connected with the electronic cigarette industry, rather than the waterpipe tobacco manufacturers. Tobacco control policy must evolve to take account of the vast and expanding array of waterpipe products, and potentially also charcoal products developed for waterpipe smokers. We recommend that tobacco substitutes be classified as tobacco products. Continued surveillance of the waterpipe industry is warranted. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/
Directory of Open Access Journals (Sweden)
Wen Jiang
2016-01-01
Full Text Available Climate change is mainly caused by excessive emissions of carbon dioxide and other greenhouse gases. In order to reduce carbon emissions, cap and trade policy is implemented by governments in many countries, which has significant impacts on the decisions of companies at all levels of the low carbon supply chain. This paper investigates the decision-making and coordination of a low carbon supply chain consisting of a low carbon manufacturer who produces one product and is allowed to invest in green technology to reduce carbon emissions in production and a retailer who faces stochastic demands formed by homogeneous strategic customers. We investigate the optimal production, pricing, carbon trading, and green technology investment strategies of the low carbon supply chain in centralized (including Rational Expected Equilibrium scenario and quantity commitment scenario and decentralized settings. It is demonstrated that quantity commitment strategy can improve the profit of the low carbon supply chain with strategic customer behavior. We also show that the performance of decentralized supply chain is lower than that of quantity commitment scenario. We prove that the low carbon supply chain cannot be coordinated by revenue sharing contract but by revenue sharing-cost sharing contract.
Eye Movements Reveal Optimal Strategies for Analogical Reasoning.
Vendetti, Michael S; Starr, Ariel; Johnson, Elizabeth L; Modavi, Kiana; Bunge, Silvia A
2017-01-01
Analogical reasoning refers to the process of drawing inferences on the basis of the relational similarity between two domains. Although this complex cognitive ability has been the focus of inquiry for many years, most models rely on measures that cannot capture individuals' thought processes moment by moment. In the present study, we used participants' eye movements to investigate reasoning strategies in real time while solving visual propositional analogy problems (A:B::C:D). We included both a semantic and a perceptual lure on every trial to determine how these types of distracting information influence reasoning strategies. Participants spent more time fixating the analogy terms and the target relative to the other response choices, and made more saccades between the A and B items than between any other items. Participants' eyes were initially drawn to perceptual lures when looking at response choices, but they nonetheless performed the task accurately. We used participants' gaze sequences to classify each trial as representing one of three classic analogy problem solving strategies and related strategy usage to analogical reasoning performance. A project-first strategy, in which participants first extrapolate the relation between the AB pair and then generalize that relation for the C item, was both the most commonly used strategy as well as the optimal strategy for solving visual analogy problems. These findings provide new insight into the role of strategic processing in analogical problem solving.
Eye Movements Reveal Optimal Strategies for Analogical Reasoning
Directory of Open Access Journals (Sweden)
Michael S. Vendetti
2017-06-01
Full Text Available Analogical reasoning refers to the process of drawing inferences on the basis of the relational similarity between two domains. Although this complex cognitive ability has been the focus of inquiry for many years, most models rely on measures that cannot capture individuals' thought processes moment by moment. In the present study, we used participants' eye movements to investigate reasoning strategies in real time while solving visual propositional analogy problems (A:B::C:D. We included both a semantic and a perceptual lure on every trial to determine how these types of distracting information influence reasoning strategies. Participants spent more time fixating the analogy terms and the target relative to the other response choices, and made more saccades between the A and B items than between any other items. Participants' eyes were initially drawn to perceptual lures when looking at response choices, but they nonetheless performed the task accurately. We used participants' gaze sequences to classify each trial as representing one of three classic analogy problem solving strategies and related strategy usage to analogical reasoning performance. A project-first strategy, in which participants first extrapolate the relation between the AB pair and then generalize that relation for the C item, was both the most commonly used strategy as well as the optimal strategy for solving visual analogy problems. These findings provide new insight into the role of strategic processing in analogical problem solving.
Optimal swimming strategies in mate searching pelagic copepods
DEFF Research Database (Denmark)
Kiørboe, Thomas
2008-01-01
Male copepods must swim to find females, but swimming increases the risk of meeting predators and is expensive in terms of energy expenditure. Here I address the trade-offs between gains and risks and the question of how much and how fast to swim using simple models that optimise the number...... of lifetime mate encounters. Radically different swimming strategies are predicted for different feeding behaviours, and these predictions are tested experimentally using representative species. In general, male swimming speeds and the difference in swimming speeds between the genders are predicted...... and observed to increase with increasing conflict between mate searching and feeding. It is high in ambush feeders, where searching (swimming) and feeding are mutually exclusive and low in species, where the matured males do not feed at all. Ambush feeding males alternate between stationary ambush feeding...
Optimal intervention strategies for cholera outbreak by education and chlorination
Bakhtiar, Toni
2016-01-01
This paper discusses the control of infectious diseases in the framework of optimal control approach. A case study on cholera control was studied by considering two control strategies, namely education and chlorination. We distinct the former control into one regarding person-to-person behaviour and another one concerning person-to-environment conduct. Model are divided into two interacted populations: human population which follows an SIR model and pathogen population. Pontryagin maximum principle was applied in deriving a set of differential equations which consists of dynamical and adjoin systems as optimality conditions. Then, the fourth order Runge-Kutta method was exploited to numerically solve the equation system. An illustrative example was provided to assess the effectiveness of the control strategies toward a set of control scenarios.
Energy Technology Data Exchange (ETDEWEB)
Oliveira, Francisco Alexandre de; Paiva, Anderson Paulo de; Lima, Jose Wanderley Marangon; Balestrassi, Pedro Paulo; Mendes, Rona Rinston Amaury [Federal Univ. of Itajuba, Minas Gerais (Brazil)
2011-01-15
Deregulation of the electricity sector has given rise to several approaches to defining optimal portfolios of energy contracts. Financial tools - requiring substantial adjustments - are usually used to determine risk and return. This article presents a novel approach to adjusting the conditional value at risk (CVaR) metric to the mix of contracts on the energy markets; the approach uses Mixture Design of Experiments (MDE). In this kind of experimental strategy, the design factors are treated as proportions in a mixture system considered quite adequate for treating portfolios in general. Instead of using traditional linear programming, the concept of desirability function is here used to combine the multi-response, nonlinear objective functions for mean with the variance of a specific portfolio obtained through MDE. The maximization of the desirability function is implied in the portfolio optimization, generating an efficient recruitment frontier. This approach offers three main contributions: it includes risk aversion in the optimization routine, it assesses interaction between contracts, and it lessens the computational effort required to solve the constrained nonlinear optimization problem. A case study based on the Brazilian energy market is used to illustrate the proposal. The numerical results verify the proposal's adequacy. (author)
International Nuclear Information System (INIS)
Oliveira, Francisco Alexandre de; Paiva, Anderson Paulo de; Lima, Jose Wanderley Marangon; Balestrassi, Pedro Paulo; Mendes, Rona Rinston Amaury
2011-01-01
Deregulation of the electricity sector has given rise to several approaches to defining optimal portfolios of energy contracts. Financial tools - requiring substantial adjustments - are usually used to determine risk and return. This article presents a novel approach to adjusting the conditional value at risk (CVaR) metric to the mix of contracts on the energy markets; the approach uses Mixture Design of Experiments (MDE). In this kind of experimental strategy, the design factors are treated as proportions in a mixture system considered quite adequate for treating portfolios in general. Instead of using traditional linear programming, the concept of desirability function is here used to combine the multi-response, nonlinear objective functions for mean with the variance of a specific portfolio obtained through MDE. The maximization of the desirability function is implied in the portfolio optimization, generating an efficient recruitment frontier. This approach offers three main contributions: it includes risk aversion in the optimization routine, it assesses interaction between contracts, and it lessens the computational effort required to solve the constrained nonlinear optimization problem. A case study based on the Brazilian energy market is used to illustrate the proposal. The numerical results verify the proposal's adequacy. (author)
DEFF Research Database (Denmark)
Baldini, Mattia; Klinge Jacobsen, Henrik
2016-01-01
the improvements made in the energy saving field. Indeed, little attention has been paid to implement energy efficiency measures, which has resulted in scenarios where expedients for a wise use of energy (e.g. energy savings and renewables share) are unbalanced. The aim of this paper is to review and evaluate...... international experiences on finding the optimal trade-off between efficiency improvements and additional renewable energy supply. A critical review of each technique, focusing on purposes, methodology and outcomes, is provided along with a review of tools adopted for the analyses. The models are categorized...... trade-off between renewables and energy efficiency measures in energy-systems under different objectives....
International Nuclear Information System (INIS)
2001-04-01
The concept of a trade and sustainability agenda for the Americas is explained and a historical account of the process of making this concept a reality is discussed in a background paper for the Hemispheric Trade and Sustainability Symposium held on April 18, 2001 in Quebec City. The Symposium was held in conjunction with the Third Summit of the Americas, where heads of 34 American nations discussed ways and means to encourage hemispheric cooperation. The object of the Symposium was to provide a constructive, policy-oriented, and knowledge-based open forum for dialogue on trade and sustainability issues; to identify policy options that can be mutually beneficial to trade, environment and development, and to increase public support for trade liberalisation in the Americas. The strategy aims to build a sustainable FTAA through the identification of a series of environmental provisions to be incorporated in the Agreement; strengthen environmental cooperation in the Americas, especially in trade-sensitive, or trade-related sectors, and create a high level hemispheric expert group on trade and sustainability for continuous and constructive dialogue with civil society and industry on these issues. The backgrounder provides a precis of the fundamental aspect of building a sustainable FTAA, explains the origin of the prevailing fear of unilateral environment-related trade sanctions by the United States, the fear of protectionist measures by Canada and the United States based on environmental provisions in the FTAA, and the fear that higher environmental standards and regulations would undermine the competitiveness of Latin American and Caribbean businesses. The paper attempts to dispel these fears by explaining the mechanism envisaged to be predominant in creating the triple-win strategy, namely impact assessment, transparency, participation and dispute resolution processes. The eventual agreement should also mention sustainable development as an overarching objective of
Turbine Control Strategies for Wind Farm Power Optimization
DEFF Research Database (Denmark)
Mirzaei, Mahmood; Göçmen Bozkurt, Tuhfe; Giebel, Gregor
2015-01-01
In recent decades there has been increasing interest in green energies, of which wind energy is the most important one. In order to improve the competitiveness of the wind power plants, there are ongoing researches to decrease cost per energy unit and increase the efficiency of wind turbines...... and wind farms. One way of achieving these goals is to optimize the power generated by a wind farm. One optimization method is to choose appropriate operating points for the individual wind turbines in the farm. We have made three models of a wind farm based on three difference control strategies...... the generated power by changing the power reference of the individual wind turbines. We use the optimization setup to compare power production of the wind farm models. This paper shows that for the most frequent wind velocities (below and around the rated values), the generated powers of the wind farms...
Integrated testing strategies can be optimal for chemical risk classification.
Raseta, Marko; Pitchford, Jon; Cussens, James; Doe, John
2017-08-01
There is an urgent need to refine strategies for testing the safety of chemical compounds. This need arises both from the financial and ethical costs of animal tests, but also from the opportunities presented by new in-vitro and in-silico alternatives. Here we explore the mathematical theory underpinning the formulation of optimal testing strategies in toxicology. We show how the costs and imprecisions of the various tests, and the variability in exposures and responses of individuals, can be assembled rationally to form a Markov Decision Problem. We compute the corresponding optimal policies using well developed theory based on Dynamic Programming, thereby identifying and overcoming some methodological and logical inconsistencies which may exist in the current toxicological testing. By illustrating our methods for two simple but readily generalisable examples we show how so-called integrated testing strategies, where information of different precisions from different sources is combined and where different initial test outcomes lead to different sets of future tests, can arise naturally as optimal policies. Copyright © 2017 Elsevier Inc. All rights reserved.
Optimal sampling strategies for detecting zoonotic disease epidemics.
Directory of Open Access Journals (Sweden)
Jake M Ferguson
2014-06-01
Full Text Available The early detection of disease epidemics reduces the chance of successful introductions into new locales, minimizes the number of infections, and reduces the financial impact. We develop a framework to determine the optimal sampling strategy for disease detection in zoonotic host-vector epidemiological systems when a disease goes from below detectable levels to an epidemic. We find that if the time of disease introduction is known then the optimal sampling strategy can switch abruptly between sampling only from the vector population to sampling only from the host population. We also construct time-independent optimal sampling strategies when conducting periodic sampling that can involve sampling both the host and the vector populations simultaneously. Both time-dependent and -independent solutions can be useful for sampling design, depending on whether the time of introduction of the disease is known or not. We illustrate the approach with West Nile virus, a globally-spreading zoonotic arbovirus. Though our analytical results are based on a linearization of the dynamical systems, the sampling rules appear robust over a wide range of parameter space when compared to nonlinear simulation models. Our results suggest some simple rules that can be used by practitioners when developing surveillance programs. These rules require knowledge of transition rates between epidemiological compartments, which population was initially infected, and of the cost per sample for serological tests.
Optimal sampling strategies for detecting zoonotic disease epidemics.
Ferguson, Jake M; Langebrake, Jessica B; Cannataro, Vincent L; Garcia, Andres J; Hamman, Elizabeth A; Martcheva, Maia; Osenberg, Craig W
2014-06-01
The early detection of disease epidemics reduces the chance of successful introductions into new locales, minimizes the number of infections, and reduces the financial impact. We develop a framework to determine the optimal sampling strategy for disease detection in zoonotic host-vector epidemiological systems when a disease goes from below detectable levels to an epidemic. We find that if the time of disease introduction is known then the optimal sampling strategy can switch abruptly between sampling only from the vector population to sampling only from the host population. We also construct time-independent optimal sampling strategies when conducting periodic sampling that can involve sampling both the host and the vector populations simultaneously. Both time-dependent and -independent solutions can be useful for sampling design, depending on whether the time of introduction of the disease is known or not. We illustrate the approach with West Nile virus, a globally-spreading zoonotic arbovirus. Though our analytical results are based on a linearization of the dynamical systems, the sampling rules appear robust over a wide range of parameter space when compared to nonlinear simulation models. Our results suggest some simple rules that can be used by practitioners when developing surveillance programs. These rules require knowledge of transition rates between epidemiological compartments, which population was initially infected, and of the cost per sample for serological tests.
Optimal Time-Space Trade-Offs for Non-Comparison-Based Sorting
DEFF Research Database (Denmark)
Pagh, Rasmus; Pagter, Jacob Illeborg
2002-01-01
We study the problem of sorting n integers of w bits on a unit-cost RAM with word size w, and in particular consider the time-space trade-off (product of time and space in bits) for this problem. For comparison-based algorithms, the time-space complexity is known to be Θ(n2). A result of Beame...... shows that the lower bound also holds for non-comparison-based algorithms, but no algorithm has met this for time below the comparison-based Ω(nlgn) lower bound.We show that if sorting within some time bound &Ttilde; is possible, then time T = O(&Ttilde; + nlg* n) can be achieved with high probability...... using space S = O(n2/T + w), which is optimal. Given a deterministic priority queue using amortized time t(n) per operation and space nO(1), we provide a deterministic algorithm sorting in time T = O(n(t(n) + lg* n)) with S = O(n2/T + w). Both results require that w ≤ n1-Ω(1). Using existing priority...
Directory of Open Access Journals (Sweden)
Kukrika Milan
2008-01-01
Full Text Available This article gives a simple and brief scope of structure and usage of location-allocation models in territory planning of retail network, trying to show the main shortage of some given models and the primary direction of their future improving. We give an inspection of theirs main usage and give an explanation of basic factors that models take in consideration during the process of demand allocation. Location-allocation models are an important segment of development of spatial retail network optimization process. Their future improvement is going towards their approximation and integration with spatial-interaction models. In this way, much better methodology of planning and directing spatial development of trade general. Methodology which we have used in this research paper is based on the literature and research projects in the area. Using this methodology in analyzing parts of Serbian territory through usage of location-allocation models, showed the need for creating special software for calculating matrix with recursions. Considering the fact that the integration of location-allocation models with GIS still didn't occur, all the results acquired during the calculation of methaformula has been brought into ArcGIS 9.2 software and presented as maps.
Directory of Open Access Journals (Sweden)
Narinder Singh
2018-03-01
Full Text Available The quest for an efficient nature-inspired optimization technique has continued over the last few decades. In this paper, a hybrid nature-inspired optimization technique has been proposed. The hybrid algorithm has been constructed using Mean Grey Wolf Optimizer (MGWO and Whale Optimizer Algorithm (WOA. We have utilized the spiral equation of Whale Optimizer Algorithm for two procedures in the Hybrid Approach GWO (HAGWO algorithm: (i firstly, we used the spiral equation in Grey Wolf Optimizer algorithm for balance between the exploitation and the exploration process in the new hybrid approach; and (ii secondly, we also applied this equation in the whole population in order to refrain from the premature convergence and trapping in local minima. The feasibility and effectiveness of the hybrid algorithm have been tested by solving some standard benchmarks, XOR, Baloon, Iris, Breast Cancer, Welded Beam Design, Pressure Vessel Design problems and comparing the results with those obtained through other metaheuristics. The solutions prove that the newly existing hybrid variant has higher stronger stability, faster convergence rate and computational accuracy than other nature-inspired metaheuristics on the maximum number of problems and can successfully resolve the function of constrained nonlinear optimization in reality.
VI International Workshop on Nature Inspired Cooperative Strategies for Optimization
Otero, Fernando; Masegosa, Antonio
2014-01-01
Biological and other natural processes have always been a source of inspiration for computer science and information technology. Many emerging problem solving techniques integrate advanced evolution and cooperation strategies, encompassing a range of spatio-temporal scales for visionary conceptualization of evolutionary computation. This book is a collection of research works presented in the VI International Workshop on Nature Inspired Cooperative Strategies for Optimization (NICSO) held in Canterbury, UK. Previous editions of NICSO were held in Granada, Spain (2006 & 2010), Acireale, Italy (2007), Tenerife, Spain (2008), and Cluj-Napoca, Romania (2011). NICSO 2013 and this book provides a place where state-of-the-art research, latest ideas and emerging areas of nature inspired cooperative strategies for problem solving are vigorously discussed and exchanged among the scientific community. The breadth and variety of articles in this book report on nature inspired methods and applications such as Swarm In...
Nuclear Power Plant Outage Optimization Strategy. 2016 Edition
International Nuclear Information System (INIS)
2016-10-01
This publication is an update of IAEA-TECDOC-1315, Nuclear Power Plant Outage Optimisation Strategy, which was published in 2002, and aims to communicate good outage management practices in a manner that can be used by operators and utilities in Member States. Nuclear power plant outage management is a key factor for safe and economic nuclear power plant performance. This publication discusses plant outage strategy and how this strategy is actually implemented. The main areas that are important for outage optimization that were identified by the utilities and government organizations participating in this report are: 1) organization and management; 2) outage planning and preparation; 3) outage execution; 4) safety outage review; and 5) counter measures to avoid the extension of outages and to facilitate the work in forced outages. Good outage management practices cover many different areas of work and this publication aims to communicate these good practices in a way that they can be used effectively by operators and utilities
International Nuclear Information System (INIS)
Oliver, Mike; Jensen, Michael; Chen, Jeff; Wong, Eugene
2009-01-01
Intensity-modulated arc therapy (IMAT) is a rotational variant of intensity-modulated radiation therapy (IMRT) that can be implemented with or without angular dose rate variation. The purpose of this study is to assess optimization strategies and initial conditions using a leaf position optimization (LPO) algorithm altered for variable dose rate IMAT. A concave planning target volume (PTV) with a central cylindrical organ at risk (OAR) was used in this study. The initial IMAT arcs were approximated by multiple static beams at 5 deg. angular increments where multi-leaf collimator (MLC) leaf positions were determined from the beam's eye view to irradiate the PTV but avoid the OAR. For the optimization strategy, two arcs with arc ranges of 280 deg. and 150 deg. were employed and plans were created using LPO alone, variable dose rate optimization (VDRO) alone, simultaneous LPO and VDRO and sequential combinations of these strategies. To assess the MLC initialization effect, three single 360 deg. arc plans with different initial MLC configurations were generated using the simultaneous LPO and VDRO. The effect of changing optimization degrees of freedom was investigated by employing 3 deg., 5 deg. and 10 deg. angular sampling intervals for the two 280 deg., two 150 deg. and single arc plans using LPO and VDRO. The objective function value, a conformity index, a dose homogeneity index, mean dose to OAR and normal tissues were computed and used to evaluate the treatment plans. This study shows that the best optimization strategy for a concave target is to use simultaneous MLC LPO and VDRO. We found that the optimization result is sensitive to the choice of initial MLC aperture shapes suggesting that an LPO-based IMAT plan may not be able to overcome local minima for this geometry. In conclusion, simultaneous MLC leaf position and VDRO are needed with the most appropriate initial conditions (MLC positions, arc ranges and number of arcs) for IMAT.
Study on Stochastic Optimal Electric Power Procurement Strategies with Uncertain Market Prices
Sakchai, Siripatanakulkhajorn; Saisho, Yuichi; Fujii, Yasumasa; Yamaji, Kenji
The player in deregulated electricity markets can be categorized into three groups of GENCO (Generator Companies), TRNASCO (Transmission Companies), DISCO (Distribution Companies). This research focuses on the role of Distribution Companies, which purchase electricity from market at randomly fluctuating prices, and provide it to their customers at given fixed prices. Therefore Distribution companies have to take the risk stemming from price fluctuation of electricity instead of the customers. This entails the necessity to develop a certain method to make an optimal strategy for electricity procurement. In such a circumstance, this research has the purpose for proposing the mathematical method based on stochastic dynamic programming to evaluate the value of a long-term bilateral contract of electricity trade, and also a project of combination of the bilateral contract and power generation with their own generators for procuring electric power in deregulated market.
Clemente, C J; Wilson, R S
2015-12-01
The ability for prey to escape a pursuing predator is dependent both on the prey's speed away from the threat and on their ability to rapidly change directions, or maneuverability. Given that the biomechanical trade-off between speed and maneuverability limits the simultaneous maximization of both performance traits, animals should not select their fastest possible speeds when running away from a pursuing predator but rather a speed that maximizes the probability of successful escape. We explored how variation in the relationship between speed and maneuverability-or the shape of the trade-off-affects the optimal choice of speed for escaping predators. We used tablet-based games that simulated interactions between predators and prey (human subjects acting as predators attempting to capture "prey" moving across a screen). By defining a specific relationship between speed and maneuverability, we could test the survival of each of the possible behavioral choices available to this phenotype, i.e., the best combination of speed and maneuverability for prey fitness, based on their ability to escape. We found that the shape of the trade-off function affected the prey's optimal speed for success in escaping, the prey's maximum performance in escaping, and the breadth of speeds over which the prey's performance was high. The optimal speed for escape varied only when the trade-off between speed and maneuverability was non-linear. Phenotypes possessing trade-off functions for which maneuverability was only compromised at high speeds exhibited lower optimal speeds. Phenotypes that exhibited greater increases in maneuverability for any decrease in speed were more likely to have broader ranges of performance, meaning that individuals could attain their maximum performance across a broader range of speeds. We also found that there was a differential response of the subject's learning to these different components of locomotion. With increased experience through repeated trials
Particle Swarm Optimization With Interswarm Interactive Learning Strategy.
Qin, Quande; Cheng, Shi; Zhang, Qingyu; Li, Li; Shi, Yuhui
2016-10-01
The learning strategy in the canonical particle swarm optimization (PSO) algorithm is often blamed for being the primary reason for loss of diversity. Population diversity maintenance is crucial for preventing particles from being stuck into local optima. In this paper, we present an improved PSO algorithm with an interswarm interactive learning strategy (IILPSO) by overcoming the drawbacks of the canonical PSO algorithm's learning strategy. IILPSO is inspired by the phenomenon in human society that the interactive learning behavior takes place among different groups. Particles in IILPSO are divided into two swarms. The interswarm interactive learning (IIL) behavior is triggered when the best particle's fitness value of both the swarms does not improve for a certain number of iterations. According to the best particle's fitness value of each swarm, the softmax method and roulette method are used to determine the roles of the two swarms as the learning swarm and the learned swarm. In addition, the velocity mutation operator and global best vibration strategy are used to improve the algorithm's global search capability. The IIL strategy is applied to PSO with global star and local ring structures, which are termed as IILPSO-G and IILPSO-L algorithm, respectively. Numerical experiments are conducted to compare the proposed algorithms with eight popular PSO variants. From the experimental results, IILPSO demonstrates the good performance in terms of solution accuracy, convergence speed, and reliability. Finally, the variations of the population diversity in the entire search process provide an explanation why IILPSO performs effectively.
Cost-effectiveness analysis of optimal strategy for tumor treatment
International Nuclear Information System (INIS)
Pang, Liuyong; Zhao, Zhong; Song, Xinyu
2016-01-01
We propose and analyze an antitumor model with combined immunotherapy and chemotherapy. Firstly, we explore the treatment effects of single immunotherapy and single chemotherapy, respectively. Results indicate that neither immunotherapy nor chemotherapy alone are adequate to cure a tumor. Hence, we apply optimal theory to investigate how the combination of immunotherapy and chemotherapy should be implemented, for a certain time period, in order to reduce the number of tumor cells, while minimizing the implementation cost of the treatment strategy. Secondly, we establish the existence of the optimality system and use Pontryagin’s Maximum Principle to characterize the optimal levels of the two treatment measures. Furthermore, we calculate the incremental cost-effectiveness ratios to analyze the cost-effectiveness of all possible combinations of the two treatment measures. Finally, numerical results show that the combination of immunotherapy and chemotherapy is the most cost-effective strategy for tumor treatment, and able to eliminate the entire tumor with size 4.470 × 10"8 in a year.
Energy Optimal Control Strategy of PHEV Based on PMP Algorithm
Directory of Open Access Journals (Sweden)
Tiezhou Wu
2017-01-01
Full Text Available Under the global voice of “energy saving” and the current boom in the development of energy storage technology at home and abroad, energy optimal control of the whole hybrid electric vehicle power system, as one of the core technologies of electric vehicles, is bound to become a hot target of “clean energy” vehicle development and research. This paper considers the constraints to the performance of energy storage system in Parallel Hybrid Electric Vehicle (PHEV, from which lithium-ion battery frequently charges/discharges, PHEV largely consumes energy of fuel, and their are difficulty in energy recovery and other issues in a single cycle; the research uses lithium-ion battery combined with super-capacitor (SC, which is hybrid energy storage system (Li-SC HESS, working together with internal combustion engine (ICE to drive PHEV. Combined with PSO-PI controller and Li-SC HESS internal power limited management approach, the research proposes the PHEV energy optimal control strategy. It is based on revised Pontryagin’s minimum principle (PMP algorithm, which establishes the PHEV vehicle simulation model through ADVISOR software and verifies the effectiveness and feasibility. Finally, the results show that the energy optimization control strategy can improve the instantaneity of tracking PHEV minimum fuel consumption track, implement energy saving, and prolong the life of lithium-ion batteries and thereby can improve hybrid energy storage system performance.
Optimal knockout strategies in genome-scale metabolic networks using particle swarm optimization.
Nair, Govind; Jungreuthmayer, Christian; Zanghellini, Jürgen
2017-02-01
Knockout strategies, particularly the concept of constrained minimal cut sets (cMCSs), are an important part of the arsenal of tools used in manipulating metabolic networks. Given a specific design, cMCSs can be calculated even in genome-scale networks. We would however like to find not only the optimal intervention strategy for a given design but the best possible design too. Our solution (PSOMCS) is to use particle swarm optimization (PSO) along with the direct calculation of cMCSs from the stoichiometric matrix to obtain optimal designs satisfying multiple objectives. To illustrate the working of PSOMCS, we apply it to a toy network. Next we show its superiority by comparing its performance against other comparable methods on a medium sized E. coli core metabolic network. PSOMCS not only finds solutions comparable to previously published results but also it is orders of magnitude faster. Finally, we use PSOMCS to predict knockouts satisfying multiple objectives in a genome-scale metabolic model of E. coli and compare it with OptKnock and RobustKnock. PSOMCS finds competitive knockout strategies and designs compared to other current methods and is in some cases significantly faster. It can be used in identifying knockouts which will force optimal desired behaviors in large and genome scale metabolic networks. It will be even more useful as larger metabolic models of industrially relevant organisms become available.
Optimal Bidding Strategy for Renewable Microgrid with Active Network Management
Directory of Open Access Journals (Sweden)
Seung Wan Kim
2016-01-01
Full Text Available Active Network Management (ANM enables a microgrid to optimally dispatch the active/reactive power of its Renewable Distributed Generation (RDG and Battery Energy Storage System (BESS units in real time. Thus, a microgrid with high penetration of RDGs can handle their uncertainties and variabilities to achieve the stable operation using ANM. However, the actual power flow in the line connecting the main grid and microgrid may deviate significantly from the day-ahead bids if the bids are determined without consideration of the real-time adjustment through ANM, which will lead to a substantial imbalance cost. Therefore, this study proposes a formulation for obtaining an optimal bidding which reflects the change of power flow in the connecting line by real-time adjustment using ANM. The proposed formulation maximizes the expected profit of the microgrid considering various network and physical constraints. The effectiveness of the proposed bidding strategy is verified through the simulations with a 33-bus test microgrid. The simulation results show that the proposed bidding strategy improves the expected operating profit by reducing the imbalance cost to a greater degree compared to the basic bidding strategy without consideration of ANM.
Cost Effectiveness Analysis of Optimal Malaria Control Strategies in Kenya
Directory of Open Access Journals (Sweden)
Gabriel Otieno
2016-03-01
Full Text Available Malaria remains a leading cause of mortality and morbidity among the children under five and pregnant women in sub-Saharan Africa, but it is preventable and controllable provided current recommended interventions are properly implemented. Better utilization of malaria intervention strategies will ensure the gain for the value for money and producing health improvements in the most cost effective way. The purpose of the value for money drive is to develop a better understanding (and better articulation of costs and results so that more informed, evidence-based choices could be made. Cost effectiveness analysis is carried out to inform decision makers on how to determine where to allocate resources for malaria interventions. This study carries out cost effective analysis of one or all possible combinations of the optimal malaria control strategies (Insecticide Treated Bednets—ITNs, Treatment, Indoor Residual Spray—IRS and Intermittent Preventive Treatment for Pregnant Women—IPTp for the four different transmission settings in order to assess the extent to which the intervention strategies are beneficial and cost effective. For the four different transmission settings in Kenya the optimal solution for the 15 strategies and their associated effectiveness are computed. Cost-effective analysis using Incremental Cost Effectiveness Ratio (ICER was done after ranking the strategies in order of the increasing effectiveness (total infections averted. The findings shows that for the endemic regions the combination of ITNs, IRS, and IPTp was the most cost-effective of all the combined strategies developed in this study for malaria disease control and prevention; for the epidemic prone areas is the combination of the treatment and IRS; for seasonal areas is the use of ITNs plus treatment; and for the low risk areas is the use of treatment only. Malaria transmission in Kenya can be minimized through tailor-made intervention strategies for malaria control
Optimizing strategy software for repetitive construction projects within multi-mode resources
Directory of Open Access Journals (Sweden)
Remon Fayek Aziz
2013-09-01
Full Text Available Estimating tender data for specific project is the most essential part in construction areas as of contractor’s view such as: proposed project duration with corresponding gross value and cash flows. This paper focuses on how to calculate tender data using Optimizing Strategy Software (OSS for repetitive construction projects with identical activity’s duration in case of single number of crew such as: project duration, project/bid price, project maximum working capital, and project net present value of the studied project. A simplified multi-objective optimization software (OSS will be presented that creates best tender data to contractor compared with more feasible options generated from multi-mode resources in a given project. OSS is intended to give more scenarios which provide practical support for typical construction contractors who need to optimize resource utilization in order to minimize project duration, project/bid price, and project maximum working capital while maximizing its net present value simultaneously. OSS is designed by java programing code system to provide a number of new and unique capabilities, including: (1 Ranking the obtained optimal plans according to a set of planner specified weights representing the relative importance of duration, price, maximum working capital and net present value in the analyzed project; (2 Visualizing and viewing the generated optimal trade-off; and (3 Providing seamless integration with available project management calculations. In order to provide the aforementioned capabilities of OSS, the system is implemented and developed in four main modules: (1 A user interface module; (2 A database module; (3 A running module; (4 A connecting module. At the end of the paper, an illustrative example will be presented to demonstrate and verify the applications of the proposed software (OSS to an optimization expressway of repetitive construction project.
Testing of Strategies for the Acceleration of the Cost Optimization
Energy Technology Data Exchange (ETDEWEB)
Ponciroli, Roberto [Argonne National Lab. (ANL), Argonne, IL (United States); Vilim, Richard B. [Argonne National Lab. (ANL), Argonne, IL (United States)
2017-08-31
The general problem addressed in the Nuclear-Renewable Hybrid Energy System (N-R HES) project is finding the optimum economical dispatch (ED) and capacity planning solutions for the hybrid energy systems. In the present test-problem configuration, the N-R HES unit is composed of three electrical power-generating components, i.e. the Balance of Plant (BOP), the Secondary Energy Source (SES), and the Energy Storage (ES). In addition, there is an Industrial Process (IP), which is devoted to hydrogen generation. At this preliminary stage, the goal is to find the power outputs of each one of the N-R HES unit components (BOP, SES, ES) and the IP hydrogen production level that maximizes the unit profit by simultaneously satisfying individual component operational constraints. The optimization problem is meant to be solved in the Risk Analysis Virtual Environment (RAVEN) framework. The dynamic response of the N-R HES unit components is simulated by using dedicated object-oriented models written in the Modelica modeling language. Though this code coupling provides for very accurate predictions, the ensuing optimization problem is characterized by a very large number of solution variables. To ease the computational burden and to improve the path to a converged solution, a method to better estimate the initial guess for the optimization problem solution was developed. The proposed approach led to the definition of a suitable Monte Carlo-based optimization algorithm (called the preconditioner), which provides an initial guess for the optimal N-R HES power dispatch and the optimal installed capacity for each one of the unit components. The preconditioner samples a set of stochastic power scenarios for each one of the N-R HES unit components, and then for each of them the corresponding value of a suitably defined cost function is evaluated. After having simulated a sufficient number of power histories, the configuration which ensures the highest profit is selected as the optimal
Wellman, Michael
2011-01-01
Automated trading in electronic markets is one of the most common and consequential applications of autonomous software agents. Design of effective trading strategies requires thorough understanding of how market mechanisms operate, and appreciation of strategic issues that commonly manifest in trading scenarios. Drawing on research in auction theory and artificial intelligence, this book presents core principles of strategic reasoning that apply to market situations. The author illustrates trading strategy choices through examples of concrete market environments, such as eBay, as well as abst
Issues and Strategies in Solving Multidisciplinary Optimization Problems
Patnaik, Surya
2013-01-01
Optimization research at NASA Glenn Research Center has addressed the design of structures, aircraft and airbreathing propulsion engines. The accumulated multidisciplinary design activity is collected under a testbed entitled COMETBOARDS. Several issues were encountered during the solution of the problems. Four issues and the strategies adapted for their resolution are discussed. This is followed by a discussion on analytical methods that is limited to structural design application. An optimization process can lead to an inefficient local solution. This deficiency was encountered during design of an engine component. The limitation was overcome through an augmentation of animation into optimization. Optimum solutions obtained were infeasible for aircraft and airbreathing propulsion engine problems. Alleviation of this deficiency required a cascading of multiple algorithms. Profile optimization of a beam produced an irregular shape. Engineering intuition restored the regular shape for the beam. The solution obtained for a cylindrical shell by a subproblem strategy converged to a design that can be difficult to manufacture. Resolution of this issue remains a challenge. The issues and resolutions are illustrated through a set of problems: Design of an engine component, Synthesis of a subsonic aircraft, Operation optimization of a supersonic engine, Design of a wave-rotor-topping device, Profile optimization of a cantilever beam, and Design of a cylindrical shell. This chapter provides a cursory account of the issues. Cited references provide detailed discussion on the topics. Design of a structure can also be generated by traditional method and the stochastic design concept. Merits and limitations of the three methods (traditional method, optimization method and stochastic concept) are illustrated. In the traditional method, the constraints are manipulated to obtain the design and weight is back calculated. In design optimization, the weight of a structure becomes the
Dynamic Trading with Predictable Returns and Transaction Costs
DEFF Research Database (Denmark)
Garleanu, Nicolae; Heje Pedersen, Lasse
We derive a closed-form optimal dynamic portfolio policy when trading is costly and security returns are predictable by signals with dierent mean-reversion speeds.The optimal strategy is characterized by two principles: 1) aim in front of the target and 2) trade partially towards the current aim...
Dynamic Trading with Predictable Returns and Transaction Costs
DEFF Research Database (Denmark)
Gârleanu, Nicolae; Heje Pedersen, Lasse
2013-01-01
We derive a closed-form optimal dynamic portfolio policy when trading is costly and security returns are predictable by signals with different mean-reversion speeds. The optimal strategy is characterized by two principles: (1) aim in front of the target, and (2) trade partially toward the current...
Strategies for Optimizing Algal Biology for Enhanced Biomass Production
Energy Technology Data Exchange (ETDEWEB)
Barry, Amanda N.; Starkenburg, Shawn R.; Sayre, Richard T., E-mail: rsayre@newmexicoconsortium.org [Los Alamos National Laboratory, New Mexico Consortium, Los Alamos, NM (United States)
2015-02-02
One of the most environmentally sustainable ways to produce high-energy density (oils) feed stocks for the production of liquid transportation fuels is from biomass. Photosynthetic carbon capture combined with biomass combustion (point source) and subsequent carbon capture and sequestration has also been proposed in the intergovernmental panel on climate change report as one of the most effective and economical strategies to remediate atmospheric greenhouse gases. To maximize photosynthetic carbon capture efficiency and energy-return-on-investment, we must develop biomass production systems that achieve the greatest yields with the lowest inputs. Numerous studies have demonstrated that microalgae have among the greatest potentials for biomass production. This is in part due to the fact that all alga cells are photoautotrophic, they have active carbon concentrating mechanisms to increase photosynthetic productivity, and all the biomass is harvestable unlike plants. All photosynthetic organisms, however, convert only a fraction of the solar energy they capture into chemical energy (reduced carbon or biomass). To increase aerial carbon capture rates and biomass productivity, it will be necessary to identify the most robust algal strains and increase their biomass production efficiency often by genetic manipulation. We review recent large-scale efforts to identify the best biomass producing strains and metabolic engineering strategies to improve aerial productivity. These strategies include optimization of photosynthetic light-harvesting antenna size to increase energy capture and conversion efficiency and the potential development of advanced molecular breeding techniques. To date, these strategies have resulted in up to twofold increases in biomass productivity.
Strategies for Optimizing Algal Biology for Enhanced Biomass Production
International Nuclear Information System (INIS)
Barry, Amanda N.; Starkenburg, Shawn R.; Sayre, Richard T.
2015-01-01
One of the most environmentally sustainable ways to produce high-energy density (oils) feed stocks for the production of liquid transportation fuels is from biomass. Photosynthetic carbon capture combined with biomass combustion (point source) and subsequent carbon capture and sequestration has also been proposed in the intergovernmental panel on climate change report as one of the most effective and economical strategies to remediate atmospheric greenhouse gases. To maximize photosynthetic carbon capture efficiency and energy-return-on-investment, we must develop biomass production systems that achieve the greatest yields with the lowest inputs. Numerous studies have demonstrated that microalgae have among the greatest potentials for biomass production. This is in part due to the fact that all alga cells are photoautotrophic, they have active carbon concentrating mechanisms to increase photosynthetic productivity, and all the biomass is harvestable unlike plants. All photosynthetic organisms, however, convert only a fraction of the solar energy they capture into chemical energy (reduced carbon or biomass). To increase aerial carbon capture rates and biomass productivity, it will be necessary to identify the most robust algal strains and increase their biomass production efficiency often by genetic manipulation. We review recent large-scale efforts to identify the best biomass producing strains and metabolic engineering strategies to improve aerial productivity. These strategies include optimization of photosynthetic light-harvesting antenna size to increase energy capture and conversion efficiency and the potential development of advanced molecular breeding techniques. To date, these strategies have resulted in up to twofold increases in biomass productivity.
Multi-Objective Optimization of a Hybrid ESS Based on Optimal Energy Management Strategy for LHDs
Directory of Open Access Journals (Sweden)
Jiajun Liu
2017-10-01
Full Text Available Energy storage systems (ESS play an important role in the performance of mining vehicles. A hybrid ESS combining both batteries (BTs and supercapacitors (SCs is one of the most promising solutions. As a case study, this paper discusses the optimal hybrid ESS sizing and energy management strategy (EMS of 14-ton underground load-haul-dump vehicles (LHDs. Three novel contributions are added to the relevant literature. First, a multi-objective optimization is formulated regarding energy consumption and the total cost of a hybrid ESS, which are the key factors of LHDs, and a battery capacity degradation model is used. During the process, dynamic programming (DP-based EMS is employed to obtain the optimal energy consumption and hybrid ESS power profiles. Second, a 10-year life cycle cost model of a hybrid ESS for LHDs is established to calculate the total cost, including capital cost, operating cost, and replacement cost. According to the optimization results, three solutions chosen from the Pareto front are compared comprehensively, and the optimal one is selected. Finally, the optimal and battery-only options are compared quantitatively using the same objectives, and the hybrid ESS is found to be a more economical and efficient option.
Directory of Open Access Journals (Sweden)
Mikić Neven
2015-01-01
Full Text Available Real business environment opens up many possibilities of business conduct, so that appropriate strategies, compatible with multicriteria requirements of the environment, potentially lead to the realization of the set goal. Adequate schedule and the optimal combination of available resources are possible to establish by a mathematical formalization in terms of the theoretical model that connects business outcomes with a cause or a probability of their occurrence. Exactly research of the possibility of using and applying the results of theoretical models in solving the specific tasks in regard to expressing relations of initial assumptions related to selection of the optimal operating strategy, is the initial motive of this paper. The theoretical models, which describe the real problem, can be analysed analytically or by simulation, depending on its complexity and the variables type, which describe it. The model should provide achieving the managing balance through the model correction of the available operational resources, increasing in that way also the capacity of decision-making system in terms of futuristic knowledge insufficiency. The research results should show that the simulation model apply, in this particular example, enables to a company significant increase of business efficiency level, more complex utilization of the capacities, increase of the competitiveness, etc.
Hopmann, Ch.; Windeck, C.; Kurth, K.; Behr, M.; Siegbert, R.; Elgeti, S.
2014-05-01
The rheological design of profile extrusion dies is one of the most challenging tasks in die design. As no analytical solution is available, the quality and the development time for a new design highly depend on the empirical knowledge of the die manufacturer. Usually, prior to start production several time-consuming, iterative running-in trials need to be performed to check the profile accuracy and the die geometry is reworked. An alternative are numerical flow simulations. These simulations enable to calculate the melt flow through a die so that the quality of the flow distribution can be analyzed. The objective of a current research project is to improve the automated optimization of profile extrusion dies. Special emphasis is put on choosing a convenient starting geometry and parameterization, which enable for possible deformations. In this work, three commonly used design features are examined with regard to their influence on the optimization results. Based on the results, a strategy is derived to select the most relevant areas of the flow channels for the optimization. For these characteristic areas recommendations are given concerning an efficient parameterization setup that still enables adequate deformations of the flow channel geometry. Exemplarily, this approach is applied to a L-shaped profile with different wall thicknesses. The die is optimized automatically and simulation results are qualitatively compared with experimental results. Furthermore, the strategy is applied to a complex extrusion die of a floor skirting profile to prove the universal adaptability.
Optimization of fuel cycle strategies with constraints on uranium availability
International Nuclear Information System (INIS)
Silvennoinen, P.; Vira, J.; Westerberg, R.
1982-01-01
Optimization of nuclear reactor and fuel cycle strategies is studied under the influence of reduced availability of uranium. The analysis is separated in two distinct steps. First, the global situation is considered within given high and low projections of the installed capacity up to the year 2025. Uranium is regarded as an exhaustible resource whose production cost would increase proportionally to increasing cumulative exploitation. Based on the estimates obtained for the uranium cost, a global strategy is derived by splitting the installed capacity between light water reactor (LWR) once-through, LWR recycle, and fast breeder reactor (FBR) alternatives. In the second phase, the nuclear program of an individual utility is optimized within the constraints imposed from the global scenario. Results from the global scenarios indicate that in a reference case the uranium price would triple by the year 2000, and the price escalation would continue throughout the planning period. In a pessimistic growth scenario where the global nuclear capacity would not exceed 600 GW(electric) in 2025, the uranium price would almost double by 2000. In both global scenarios, FBRs would be introduced, in the reference case after 2000 and in the pessimistic case after 2010. In spite of the increases in the uranium prices, the levelized power production cost would increase only by 45% up to 2025 in the utility case provided that the plutonium is incinerated as a substitute fuel
Web malware spread modelling and optimal control strategies
Liu, Wanping; Zhong, Shouming
2017-02-01
The popularity of the Web improves the growth of web threats. Formulating mathematical models for accurate prediction of malicious propagation over networks is of great importance. The aim of this paper is to understand the propagation mechanisms of web malware and the impact of human intervention on the spread of malicious hyperlinks. Considering the characteristics of web malware, a new differential epidemic model which extends the traditional SIR model by adding another delitescent compartment is proposed to address the spreading behavior of malicious links over networks. The spreading threshold of the model system is calculated, and the dynamics of the model is theoretically analyzed. Moreover, the optimal control theory is employed to study malware immunization strategies, aiming to keep the total economic loss of security investment and infection loss as low as possible. The existence and uniqueness of the results concerning the optimality system are confirmed. Finally, numerical simulations show that the spread of malware links can be controlled effectively with proper control strategy of specific parameter choice.
Using Chemical Reaction Kinetics to Predict Optimal Antibiotic Treatment Strategies.
Abel Zur Wiesch, Pia; Clarelli, Fabrizio; Cohen, Ted
2017-01-01
Identifying optimal dosing of antibiotics has proven challenging-some antibiotics are most effective when they are administered periodically at high doses, while others work best when minimizing concentration fluctuations. Mechanistic explanations for why antibiotics differ in their optimal dosing are lacking, limiting our ability to predict optimal therapy and leading to long and costly experiments. We use mathematical models that describe both bacterial growth and intracellular antibiotic-target binding to investigate the effects of fluctuating antibiotic concentrations on individual bacterial cells and bacterial populations. We show that physicochemical parameters, e.g. the rate of drug transmembrane diffusion and the antibiotic-target complex half-life are sufficient to explain which treatment strategy is most effective. If the drug-target complex dissociates rapidly, the antibiotic must be kept constantly at a concentration that prevents bacterial replication. If antibiotics cross bacterial cell envelopes slowly to reach their target, there is a delay in the onset of action that may be reduced by increasing initial antibiotic concentration. Finally, slow drug-target dissociation and slow diffusion out of cells act to prolong antibiotic effects, thereby allowing for less frequent dosing. Our model can be used as a tool in the rational design of treatment for bacterial infections. It is easily adaptable to other biological systems, e.g. HIV, malaria and cancer, where the effects of physiological fluctuations of drug concentration are also poorly understood.
Survey Strategy Optimization for the Atacama Cosmology Telescope
De Bernardis, F.; Stevens, J. R.; Hasselfield, M.; Alonso, D.; Bond, J. R.; Calabrese, E.; Choi, S. K.; Crowley, K. T.; Devlin, M.; Wollack, E. J.
2016-01-01
In recent years there have been significant improvements in the sensitivity and the angular resolution of the instruments dedicated to the observation of the Cosmic Microwave Background (CMB). ACTPol is the first polarization receiver for the Atacama Cosmology Telescope (ACT) and is observing the CMB sky with arcmin resolution over approximately 2000 square degrees. Its upgrade, Advanced ACTPol (AdvACT), will observe the CMB in five frequency bands and over a larger area of the sky. We describe the optimization and implementation of the ACTPol and AdvACT surveys. The selection of the observed fields is driven mainly by the science goals, that is, small angular scale CMB measurements, B-mode measurements and cross-correlation studies. For the ACTPol survey we have observed patches of the southern galactic sky with low galactic foreground emissions which were also chosen to maximize the overlap with several galaxy surveys to allow unique cross-correlation studies. A wider field in the northern galactic cap ensured significant additional overlap with the BOSS spectroscopic survey. The exact shapes and footprints of the fields were optimized to achieve uniform coverage and to obtain cross-linked maps by observing the fields with different scan directions. We have maximized the efficiency of the survey by implementing a close to 24-hour observing strategy, switching between daytime and nighttime observing plans and minimizing the telescope idle time. We describe the challenges represented by the survey optimization for the significantly wider area observed by AdvACT, which will observe roughly half of the low-foreground sky. The survey strategies described here may prove useful for planning future ground-based CMB surveys, such as the Simons Observatory and CMB Stage IV surveys.
Success and failure of technical trading strategies in the cocoa futures market
Boswijk, P.; Griffioen, G.A.W.; Hommes, C.
2001-01-01
A large set of 5350 trend following technical trading rules is applied to LIFFE and CSCE cocoa futures prices, and to the Pound-Dollar exchange rate, in the period 1983:1-1997:6. We find that 72% of the trading rules generates positive profits, even when correcting for transaction and borrowing
Sequentially optimized reconstruction strategy: A meta-strategy for perimetry testing.
Directory of Open Access Journals (Sweden)
Şerife Seda Kucur
Full Text Available Perimetry testing is an automated method to measure visual function and is heavily used for diagnosing ophthalmic and neurological conditions. Its working principle is to sequentially query a subject about perceived light using different brightness levels at different visual field locations. At a given location, this query-patient-feedback process is expected to converge at a perceived sensitivity, such that a shown stimulus intensity is observed and reported 50% of the time. Given this inherently time-intensive and noisy process, fast testing strategies are necessary in order to measure existing regions more effectively and reliably. In this work, we present a novel meta-strategy which relies on the correlative nature of visual field locations in order to strongly reduce the necessary number of locations that need to be examined. To do this, we sequentially determine locations that most effectively reduce visual field estimation errors in an initial training phase. We then exploit these locations at examination time and show that our approach can easily be combined with existing perceived sensitivity estimation schemes to speed up the examinations. Compared to state-of-the-art strategies, our approach shows marked performance gains with a better accuracy-speed trade-off regime for both mixed and sub-populations.
International Nuclear Information System (INIS)
Cox, G.; Beresford, N.A.; Alvarez-Farizo, B.; Oughton, D.; Kis, Z.; Eged, K.; Thorring, H.; Hunt, J.; Wright, S.; Barnett, C.L.; Gil, J.M.; Howard, B.J.; Crout, N.M.J.
2005-01-01
A spatially implemented model designed to assist the identification of optimal countermeasure strategies for radioactively contaminated regions is described. Collective and individual ingestion doses for people within the affected area are estimated together with collective exported ingestion dose. A range of countermeasures are incorporated within the model, and environmental restrictions have been included as appropriate. The model evaluates the effectiveness of a given combination of countermeasures through a cost function which balances the benefit obtained through the reduction in dose with the cost of implementation. The optimal countermeasure strategy is the combination of individual countermeasures (and when and where they are implemented) which gives the lowest value of the cost function. The model outputs should not be considered as definitive solutions, rather as interactive inputs to the decision making process. As a demonstration the model has been applied to a hypothetical scenario in Cumbria (UK). This scenario considered a published nuclear power plant accident scenario with a total deposition of 1.7 x 10 14 , 1.2 x 10 13 , 2.8 x 10 10 and 5.3 x 10 9 Bq for Cs-137, Sr-90, Pu-239/240 and Am-241, respectively. The model predicts that if no remediation measures were implemented the resulting collective dose would be approximately 36 000 person-Sv (predominantly from 137 Cs) over a 10-year period post-deposition. The optimal countermeasure strategy is predicted to avert approximately 33 000 person-Sv at a cost of approximately pound 160 million. The optimal strategy comprises a mixture of ploughing, AFCF (ammonium-ferric hexacyano-ferrate) administration, potassium fertiliser application, clean feeding of livestock and food restrictions. The model recommends specific areas within the contaminated area and time periods where these measures should be implemented
Directory of Open Access Journals (Sweden)
Jixiang Fan
2015-09-01
Full Text Available In this paper, a map-based optimal energy management strategy is proposed to improve the consumption economy of a plug-in parallel hybrid electric vehicle. In the design of the maps, which provide both the torque split between engine and motor and the gear shift, not only the current vehicle speed and power demand, but also the optimality based on the predicted trajectory of vehicle dynamics are considered. To seek the optimality, the equivalent consumption, which trades off the fuel and electricity usages, is chosen as the cost function. Moreover, in order to decrease the model errors in the process of optimization conducted in the discrete time domain, the variational integrator is employed to calculate the evolution of the vehicle dynamics. To evaluate the proposed energy management strategy, the simulation results performed on a professional GT-Suit simulator are demonstrated and the comparison to a real-time optimization method is also given to show the advantage of the proposed off-line optimization approach.
Directory of Open Access Journals (Sweden)
Chaiwat Wilasang
2016-01-01
Full Text Available Avian influenza virus subtype H5N1 is endemic to Southeast Asia. In Thailand, avian influenza viruses continue to cause large poultry stock losses. The spread of the disease has a serious impact on poultry production especially among rural households with backyard chickens. The movements and activities of chicken traders result in the spread of the disease through traditional trade networks. In this study, we investigate the dynamics of avian influenza in the traditional trade network in Phitsanulok Province, Thailand. We also propose an individual-based model with intervention strategies to control the spread of the disease. We found that the dynamics of the disease mainly depend on the transmission probability and the virus inactivation period. This study also illustrates the appropriate virus disinfection period and the target for intervention strategies on traditional trade network. The results suggest that good hygiene and cleanliness among household traders and trader of trader areas and ensuring that any equipment used is clean can lead to a decrease in transmission and final epidemic size. These results may be useful to epidemiologists, researchers, and relevant authorities in understanding the spread of avian influenza through traditional trade networks.
Robust approximate optimal guidance strategies for aeroassisted orbital transfer missions
Ilgen, Marc R.
This thesis presents the application of game theoretic and regular perturbation methods to the problem of determining robust approximate optimal guidance laws for aeroassisted orbital transfer missions with atmospheric density and navigated state uncertainties. The optimal guidance problem is reformulated as a differential game problem with the guidance law designer and Nature as opposing players. The resulting equations comprise the necessary conditions for the optimal closed loop guidance strategy in the presence of worst case parameter variations. While these equations are nonlinear and cannot be solved analytically, the presence of a small parameter in the equations of motion allows the method of regular perturbations to be used to solve the equations approximately. This thesis is divided into five parts. The first part introduces the class of problems to be considered and presents results of previous research. The second part then presents explicit semianalytical guidance law techniques for the aerodynamically dominated region of flight. These guidance techniques are applied to unconstrained and control constrained aeroassisted plane change missions and Mars aerocapture missions, all subject to significant atmospheric density variations. The third part presents a guidance technique for aeroassisted orbital transfer problems in the gravitationally dominated region of flight. Regular perturbations are used to design an implicit guidance technique similar to the second variation technique but that removes the need for numerically computing an optimal trajectory prior to flight. This methodology is then applied to a set of aeroassisted inclination change missions. In the fourth part, the explicit regular perturbation solution technique is extended to include the class of guidance laws with partial state information. This methodology is then applied to an aeroassisted plane change mission using inertial measurements and subject to uncertainties in the initial value
Optimal strategy for selling on group-buying website
Directory of Open Access Journals (Sweden)
Xuan Jiang
2014-09-01
Full Text Available Purpose: The purpose of this paper is to help business marketers with offline channels to make decisions on whether to sell through Group-buying (GB websites and how to set online price with the coordination of maximum deal size on GB websites. Design/methodology/approach: Considering the deal structure of GB websites especially for the service fee and minimum deal size limit required by GB websites, advertising effect of selling on GB websites, and interaction between online and offline markets, an analytical model is built to derive optimal online price and maximum deal size for sellers selling through GB website. This paper aims to answer four research questions: (1 How to make a decision on maximum deal size with coordination of the deal price? (2 Will selling on GB websites always be better than staying with offline channel only? (3 What kind of products is more appropriate to sell on GB website? (4How could GB website operator induce sellers to offer deep discount in GB deals? Findings and Originality/value: This paper obtains optimal strategies for sellers selling on GB website and finds that: Even if a seller has sufficient capacity, he/she may still set a maximum deal size on the GB deal to take advantage of Advertisement with Limited Availability (ALA effect; Selling through GB website may not bring a higher profit than selling only through offline channel when a GB site only has a small consumer base and/or if there is a big overlap between the online and offline markets; Low margin products are more suitable for being sold online with ALA strategies (LP-ALA or HP-ALA than high margin ones; A GB site operator could set a small minimum deal size to induce deep discounts from the sellers selling through GB deals. Research limitations/implications: The present study assumed that the demand function is determinate and linear. It will be interesting to study how stochastic demand and a more general demand function affect the optimal
Hurford, Anthony; Harou, Julien
2014-05-01
Water related eco-system services are important to the livelihoods of the poorest sectors of society in developing countries. Degradation or loss of these services can increase the vulnerability of people decreasing their capacity to support themselves. New approaches to help guide water resources management decisions are needed which account for the non-market value of ecosystem goods and services. In case studies from Brazil and Kenya we demonstrate the capability of many objective Pareto-optimal trade-off analysis to help decision makers balance economic and non-market benefits from the management of existing multi-reservoir systems. A multi-criteria search algorithm is coupled to a water resources management simulator of each basin to generate a set of Pareto-approximate trade-offs representing the best case management decisions. In both cases, volume dependent reservoir release rules are the management decisions being optimised. In the Kenyan case we further assess the impacts of proposed irrigation investments, and how the possibility of new investments impacts the system's trade-offs. During the multi-criteria search (optimisation), performance of different sets of management decisions (policies) is assessed against case-specific objective functions representing provision of water supply and irrigation, hydropower generation and maintenance of ecosystem services. Results are visualised as trade-off surfaces to help decision makers understand the impacts of different policies on a broad range of stakeholders and to assist in decision-making. These case studies show how the approach can reveal unexpected opportunities for win-win solutions, and quantify the trade-offs between investing to increase agricultural revenue and negative impacts on protected ecosystems which support rural livelihoods.
Chow, Sheung-Chi; Hon, Tai-Yuen; Wong, Wing-Keung; Woo, Kai-Yin
2017-01-01
Recently, a new Bayesian approach has been developed to explain some market anomalies. In this paper, we conduct a questionnaire survey to examine whether the theory holds empirically by studying the conservative and representative heuristics by Hong Kong small investors who adopt momentum and/or contrarian trading strategies. In addition, our study provides evidence for the small investors on their time horizon and risk tolerance when facing uncertainty in their investments. Our findings are...
An Overview of Optimizing Strategies for Flotation Banks
Directory of Open Access Journals (Sweden)
Miguel Maldonado
2012-10-01
Full Text Available A flotation bank is a serial arrangement of cells. How to optimally operate a bank remains a challenge. This article reviews three reported strategies: air profiling, mass-pull (froth velocity profiling and Peak Air Recovery (PAR profiling. These are all ways of manipulating the recovery profile down a bank, which may be the property being exploited. Mathematical analysis has shown that a flat cell-by-cell recovery profile maximizes the separation of two floatable minerals for a given target bank recovery when the relative floatability is constant down the bank. Available bank survey data are analyzed with respect to recovery profiling. Possible variations on recovery profile to minimize entrainment are discussed.
Gradient Material Strategies for Hydrogel Optimization in Tissue Engineering Applications
2018-01-01
Although a number of combinatorial/high-throughput approaches have been developed for biomaterial hydrogel optimization, a gradient sample approach is particularly well suited to identify hydrogel property thresholds that alter cellular behavior in response to interacting with the hydrogel due to reduced variation in material preparation and the ability to screen biological response over a range instead of discrete samples each containing only one condition. This review highlights recent work on cell–hydrogel interactions using a gradient material sample approach. Fabrication strategies for composition, material and mechanical property, and bioactive signaling gradient hydrogels that can be used to examine cell–hydrogel interactions will be discussed. The effects of gradients in hydrogel samples on cellular adhesion, migration, proliferation, and differentiation will then be examined, providing an assessment of the current state of the field and the potential of wider use of the gradient sample approach to accelerate our understanding of matrices on cellular behavior. PMID:29485612
Optimizing urology group partnerships: collaboration strategies and compensation best practices.
Jacoby, Dana L; Maller, Bruce S; Peltier, Lisa R
2014-10-01
Market forces in health care have created substantial regulatory, legislative, and reimbursement changes that have had a significant impact on urology group practices. To maintain viability, many urology groups have merged into larger integrated entities. Although group operations vary considerably, the majority of groups have struggled with the development of a strong culture, effective decision-making, and consensus-building around shared resources, income, and expense. Creating a sustainable business model requires urology group leaders to allocate appropriate time and resources to address these issues in a proactive manner. This article outlines collaboration strategies for creating an effective culture, governance, and leadership, and provides practical suggestions for optimizing the performance of the urology group practice.
Optimal Strategies for Probing Terrestrial Exoplanet Atmospheres with JWST
Batalha, Natasha E.; Lewis, Nikole K.; Line, Michael
2018-01-01
It is imperative that the exoplanet community determines the feasibility and the resources needed to yield high fidelity atmospheric compositions from terrestrial exoplanets. In particular, LHS 1140b and the TRAPPIST-1 system, already slated for observations by JWST’s Guaranteed Time Observers, will be the first two terrestrial planets observed by JWST. I will discuss optimal observing strategies for observing these two systems, focusing on the NIRSpec Prism (1-5μm) and the combination of NIRISS SOSS (1-2.7μm) and NIRSpec G395H (3-5μm). I will also introduce currently unsupported JWST readmodes that have the potential to greatly increase the precision on our atmospheric spectra. Lastly, I will use information content theory to compute the expected confidence interval on the retrieved abundances of key molecular species and temperature profiles as a function of JWST observing cycles.
Optimized control strategy for crowbarless solid state modular power supply
International Nuclear Information System (INIS)
Upadhyay, R.; Badapanda, M.K.; Tripathi, A.; Hannurkar, P.R.; Pithawa, C.K.
2009-01-01
Solid state modular power supply with series connected IGBT based power modules have been employed as high voltage bias power supply of klystron amplifier. Auxiliary compensation of full wave inverter bridge with ZVS/ZCS operations of all IGBTs over entire operating range is incorporated. An optimized control strategy has been adopted for this power supply needing no output filter, making this scheme crowbarless and is presented in this paper. DSP based fully digital control with same duty cycle for all power modules, have been incorporated for regulating this power supply along with adequate protection features. Input to this power supply is taken directly from 11 kV line and the input system is intentionally made 24 pulsed to reduce the input harmonics, improve the input power factor significantly, there by requiring no line filters. Various steps have been taken to increase the efficiency of major subsystems, so as to improve the overall efficiency of this power supply significantly. (author)
Evolution strategy based optimal chiller loading for saving energy
International Nuclear Information System (INIS)
Chang, Y.-C.; Lee, C.-Y.; Chen, C.-R.; Chou, C.-J.; Chen, W.-H.; Chen, W.-H.
2009-01-01
This study employs evolution strategy (ES) to solve optimal chiller loading (OCL) problem. ES overcomes the flaw that Lagrangian method is not adaptable for solving OCL as the power consumption models or the kW-PLR (partial load ratio) curves include convex functions and concave functions simultaneously. The complicated process of evolution by the genetic algorithm (GA) method for solving OCL can also be simplified by the ES method. This study uses the PLR of chiller as the variable to be solved for the decoupled air conditioning system. After analysis and comparison of the case study, it has been concluded that this method not only solves the problems of Lagrangian method and GA method, but also produces results with high accuracy within a rapid timeframe. It can be perfectly applied to the operation of air conditioning systems
Optimal Inspection and Repair Strategies for Structural Systems
DEFF Research Database (Denmark)
Sommer, A. M.; Nowak, A. S.; Thoft-Christensen, Palle
1992-01-01
and a design variable as optimization variables. A model for estimating the total expected costs for structural systems is given including the costs associated with the loss of individual structural members as well as the costs associated with the loss of at least one element of a particular group......A model for reliability-based repair and maintenance strategies of structural systems is described. The total expected costs in the lifetime of the structure are minimized with the number of inspections, the number and positions of the inspected points, the inspection efforts, the repair criteria...... of structural members and the costs associated with the simultaneous loss of all members of a specific group of structural members. The approach is based on the pre-posteriori analysis from the classical decision theory. Special emphasis is given to the problem of selecting the number of points in the structure...
International Nuclear Information System (INIS)
Liu, Z. Q.; Zhang, Z. F.
2013-01-01
Amorphous steels have demonstrated superior properties and great potentials for structural applications since their emergence, yet it still remains unclear about how and why their mechanical properties are correlated with other factors and how to achieve intended properties by designing their compositions. Here, the intrinsic interdependences among the mechanical, thermal, and elastic properties of various amorphous steels are systematically elucidated and a general trade-off relation is exposed between the strength and ductility/toughness. Encouragingly, a breakthrough is achievable that the strength and ductility/toughness can be simultaneously improved by tuning the compositions. The composition dependences of the properties and alloying effects are further analyzed thoroughly and interpreted from the fundamental plastic flow and atomic bonding characters. Most importantly, systematic strategies are outlined for optimizing the mechanical properties of the amorphous steels. The study may help establish the intrinsic correlations among the compositions, atomic structures, and properties of the amorphous steels, and provide useful guidance for their alloy design and property optimization. Thus, it is believed to have implications for the development and applications of the structural amorphous steels
Optimal Prices and Trade-in Rebates for Durable, Remanufacturable Products
Saibal Ray; Tamer Boyaci; Necati Aras
2005-01-01
Most durable products have two distinct types of customers: first-time buyers and customers who already own the product, but are willing to replace it with a new one or purchase a second one. Firms usually adopt a price-discrimination policy by offering a trade-in rebate only to the replacement customers to hasten their purchase decisions. Any return flow of products induced by trade-in rebates has the potential to generate revenues through remanufacturing operations. In this paper, we study ...
An optimal staggered harvesting strategy for herbaceous biomass energy crops
Energy Technology Data Exchange (ETDEWEB)
Bhat, M.G.; English, B.C. [Univ. of Tennessee, Knoxville, TN (United States)
1993-12-31
Biofuel research over the past two decades indicates lignocellulosic crops are a reliable source of feedstock for alternative energy. However, under the current technology of producing, harvesting and converting biomass crops, the cost of biofuel is not competitive with conventional biofuel. Cost of harvesting biomass feedstock is a single largest component of feedstock cost so there is a cost advantage in designing a biomass harvesting system. Traditional farmer-initiated harvesting operation causes over investment. This study develops a least-cost, time-distributed (staggered) harvesting system for example switch grass, that calls for an effective coordination between farmers, processing plant and a single third-party custom harvester. A linear programming model explicitly accounts for the trade-off between yield loss and benefit of reduced machinery overhead cost, associated with the staggered harvesting system. Total cost of producing and harvesting switch grass will decline by 17.94 percent from conventional non-staggered to proposed staggered harvesting strategy. Harvesting machinery cost alone experiences a significant reduction of 39.68 percent from moving from former to latter. The net return to farmers is estimated to increase by 160.40 percent. Per tonne and per hectare costs of feedstock production will decline by 17.94 percent and 24.78 percent, respectively. These results clearly lend support to the view that the traditional system of single period harvesting calls for over investment on agricultural machinery which escalates the feedstock cost. This social loss to the society in the form of escalated harvesting cost can be avoided if there is a proper coordination among farmers, processing plant and custom harvesters as to when and how biomass crop needs to be planted and harvested. Such an institutional arrangement benefits producers, processing plant and, in turn, end users of biofuels.
Collins, Linda M
2018-01-01
This book presents a framework for development, optimization, and evaluation of behavioral, biobehavioral, and biomedical interventions. Behavioral, biobehavioral, and biomedical interventions are programs with the objective of improving and maintaining human health and well-being, broadly defined, in individuals, families, schools, organizations, or communities. These interventions may be aimed at, for example, preventing or treating disease, promoting physical and mental health, preventing violence, or improving academic achievement. This volume introduces the Multiphase Optimization Strategy (MOST), pioneered at The Methodology Center at the Pennsylvania State University, as an alternative to the classical approach of relying solely on the randomized controlled trial (RCT). MOST borrows heavily from perspectives taken and approaches used in engineering, and also integrates concepts from statistics and behavioral science, including the RCT. As described in detail in this book, MOST consists of ...
Optimal Order Strategy in Uncertain Demands with Free Shipping Option
Directory of Open Access Journals (Sweden)
Qing-Chun Meng
2014-01-01
Full Text Available Free shipping with conditions has become one of the most effective marketing tools; more and more companies especially e-business companies prefer to offer free shipping to buyers whenever their orders exceed the minimum quantity specified by them. But in practice, the demands of buyers are uncertain, which are affected by weather, season, and many other factors. Firstly, we model the centralization ordering problem of retailers who face stochastic demands when suppliers offer free shipping, in which limited distributional information such as known mean, support, and some deviation measures of the random data is needed only. Then, based on the linear decision rule mainly for stochastic programming, we analyze the optimal order strategies of retailers and discuss the approximate solution. Further, we present the core allocation between all retailers via dual and cooperative game theory. The existence of core shows that each retailer is pleased to cooperate with others in the centralization problem. Finally, a numerical example is implemented to discuss how uncertain data and parameters affect the optimal solution.
Optimizing the HLT Buffer Strategy with Monte Carlo Simulations
AUTHOR|(CDS)2266763
2017-01-01
This project aims to optimize the strategy of utilizing the disk buffer for the High Level Trigger (HLT) of the LHCb experiment with the help of Monte-Carlo simulations. A method is developed, which simulates the Event Filter Farm (EFF) -- a computing cluster for the High Level Trigger -- as a compound of nodes with different performance properties. In this way, the behavior of the computing farm can be analyzed at a deeper level than before. It is demonstrated that the current operating strategy might be improved when data taking is reaching a mid-year scheduled stop or the year-end technical stop. The processing time of the buffered data can be lowered by distributing the detector data according to the processing power of the nodes instead of the relative disk size as long as the occupancy level of the buffer is low enough. Moreover, this ensures that data taken and stored on the buffer at the same time is processed by different nodes nearly simultaneously, which reduces load on the infrastructure.
Tang, F. R.; Zhang, Rong; Li, Huichao; Li, C. N.; Liu, Wei; Bai, Long
2018-05-01
The trade-off criterion is used to systemically investigate the performance features of two chemical engine models (the low-dissipation model and the endoreversible model). The optimal efficiencies, the dissipation ratios, and the corresponding ratios of the dissipation rates for two models are analytically determined. Furthermore, the performance properties of two kinds of chemical engines are precisely compared and analyzed, and some interesting physics is revealed. Our investigations show that the certain universal equivalence between two models is within the framework of the linear irreversible thermodynamics, and their differences are rooted in the different physical contexts. Our results can contribute to a precise understanding of the general features of chemical engines.
Yadav, Naresh Kumar; Kumar, Mukesh; Gupta, S. K.
2017-03-01
General strategic bidding procedure has been formulated in the literature as a bi-level searching problem, in which the offer curve tends to minimise the market clearing function and to maximise the profit. Computationally, this is complex and hence, the researchers have adopted Karush-Kuhn-Tucker (KKT) optimality conditions to transform the model into a single-level maximisation problem. However, the profit maximisation problem with KKT optimality conditions poses great challenge to the classical optimisation algorithms. The problem has become more complex after the inclusion of transmission constraints. This paper simplifies the profit maximisation problem as a minimisation function, in which the transmission constraints, the operating limits and the ISO market clearing functions are considered with no KKT optimality conditions. The derived function is solved using group search optimiser (GSO), a robust population-based optimisation algorithm. Experimental investigation is carried out on IEEE 14 as well as IEEE 30 bus systems and the performance is compared against differential evolution-based strategic bidding, genetic algorithm-based strategic bidding and particle swarm optimisation-based strategic bidding methods. The simulation results demonstrate that the obtained profit maximisation through GSO-based bidding strategies is higher than the other three methods.
Energy Technology Data Exchange (ETDEWEB)
Hope, E.
1994-06-01
The report discusses the organization and behaviour of grid monopolies in the Norwegian power trade and relations to the socio-economic effectiveness. The main attention is laid on analyzing regulation mechanisms and measures leading to an efficient short-term operation and to the investment of optimum production capacity in a long run. Regarding the management, measures are discussed for increasing the efficiency of total power trade by evaluating the existing marketing function of Statnett. Some basic conditions are accounted concerning the regulation problem of grid monopolies with a particular attention to asymmetric information between the authority and the monopoly. In addition, forms of regulation and regulation mechanisms together with the incentive characteristics of these, are discussed. The existing profit regulation principles in relation to an alternative system design such as maximum price regulation combined with standard regulation, are evaluated. 16 refs., 7 figs.
International Nuclear Information System (INIS)
El Hanandeh, Ali; El-Zein, Abbas
2009-01-01
Climate change is a driving force behind some recent environmental legislation around the world. Greenhouse gas emission reduction targets have been set in many industrialised countries. A change in current practices of almost all greenhouse-emitting industrial sectors is unavoidable, if the set targets is to be achieved. Although, waste disposal contributes around 3% of the total greenhouse gas emissions in Australia (mainly due to fugitive methane emissions from landfills), the carbon credit and trading scheme set to start in 2010 presents significant challenges and opportunities to municipal solid waste practitioners. Technological advances in waste management, if adopted properly, allow the municipal solid waste sector to act as carbon sink, hence earning tradable carbon credits. However, due to the complexity of the system and its inherent uncertainties, optimizing it for carbon credits may worsen its performance under other criteria. We use an integrated, stochastic multi-criteria decision-making tool that we developed earlier to analyse the carbon credit potential of Sydney municipal solid waste under eleven possible future strategies. We find that the changing legislative environment is likely to make current practices highly non-optimal and increase pressures for a change of waste management strategy.
Exploring the Optimal Strategy to Predict Essential Genes in Microbes
Directory of Open Access Journals (Sweden)
Yao Lu
2011-12-01
Full Text Available Accurately predicting essential genes is important in many aspects of biology, medicine and bioengineering. In previous research, we have developed a machine learning based integrative algorithm to predict essential genes in bacterial species. This algorithm lends itself to two approaches for predicting essential genes: learning the traits from known essential genes in the target organism, or transferring essential gene annotations from a closely related model organism. However, for an understudied microbe, each approach has its potential limitations. The first is constricted by the often small number of known essential genes. The second is limited by the availability of model organisms and by evolutionary distance. In this study, we aim to determine the optimal strategy for predicting essential genes by examining four microbes with well-characterized essential genes. Our results suggest that, unless the known essential genes are few, learning from the known essential genes in the target organism usually outperforms transferring essential gene annotations from a related model organism. In fact, the required number of known essential genes is surprisingly small to make accurate predictions. In prokaryotes, when the number of known essential genes is greater than 2% of total genes, this approach already comes close to its optimal performance. In eukaryotes, achieving the same best performance requires over 4% of total genes, reflecting the increased complexity of eukaryotic organisms. Combining the two approaches resulted in an increased performance when the known essential genes are few. Our investigation thus provides key information on accurately predicting essential genes and will greatly facilitate annotations of microbial genomes.
Optimizing strategies to improve interprofessional practice for veterans, part 1
Directory of Open Access Journals (Sweden)
Bhattacharya SB
2014-04-01
Full Text Available Shelley B Bhattacharya,1–3 Michelle I Rossi,1,2 Jennifer M Mentz11Geriatric Research Education and Clinical Center (GRECC, Veteran's Affairs Pittsburgh Healthcare System, 2University of Pittsburgh Medical Center, Pittsburgh, PA, USA; 3Albert Schweitzer Fellowship Program, Pittsburgh, PA, USAIntroduction: Interprofessional patient care is a well-recognized path that health care systems are striving toward. The Veteran's Affairs (VA system initiated interprofessional practice (IPP models with their Geriatric Evaluation and Management (GEM programs. GEM programs incorporate a range of specialties, including but not limited to, medicine, nursing, social work, physical therapy and pharmacy, to collaboratively evaluate veterans. Despite being a valuable resource, they are now faced with significant cut-backs, including closures. The primary goal of this project was to assess how the GEM model could be optimized at the Pittsburgh, Pennsylvania VA to allow for the sustainability of this important IPP assessment. Part 1 of the study evaluated the IPP process using program, patient, and family surveys. Part 2 examined how well the geriatrician matched patients to specialists in the GEM model. This paper describes Part 1 of our study.Methods: Three strategies were used: 1 a national GEM program survey; 2 a veteran/family satisfaction survey; and 3 an absentee assessment.Results: Twenty-six of 92 programs responded to the GEM IPP survey. Six strategies were shared to optimize IPP models throughout the country. Of the 34 satisfaction surveys, 80% stated the GEM clinic was beneficial, 79% stated their concerns were addressed, and 100% would recommend GEM to their friends. Of the 24 absentee assessments, the top three reasons for missing the appointments were transportation, medical illnesses, and not knowing/remembering about the appointment. Absentee rate diminished from 41% to 19% after instituting a reminder phone call policy.Discussion: Maintaining the
Trading off Aircraft Fuel Burn and NO x Emissions for Optimal Climate Policy.
Freeman, Sarah; Lee, David S; Lim, Ling L; Skowron, Agnieszka; De León, Ruben Rodriguez
2018-03-06
Aviation emits pollutants that affect the climate, including CO 2 and NO x , NO x indirectly so, through the formation of tropospheric ozone and reduction of ambient methane. To improve the fuel performance of engines, combustor temperatures and pressures often increase, increasing NO x emissions. Conversely, combustor modifications to reduce NO x may increase CO 2 . Hence, a technology trade-off exists, which also translates to a trade-off between short-lived climate forcers and a long-lived greenhouse gas, CO 2 . Moreover, the NO x -O 3 -CH 4 system responds in a nonlinear manner, according to both aviation emissions and background NO x . A simple climate model was modified to incorporate nonlinearities parametrized from a complex chemistry model. Case studies showed that for a scenario of a 20% reduction in NO x emissions the consequential CO 2 penalty of 2% actually increased the total radiative forcing (RF). For a 2% fuel penalty, NO x emissions needed to be reduced by >43% to realize an overall benefit. Conversely, to ensure that the fuel penalty for a 20% NO x emission reduction did not increase overall forcing, a 0.5% increase in CO 2 was found to be the "break even" point. The time scales of the climate effects of NO x and CO 2 are quite different, necessitating careful analysis of proposed emissions trade-offs.
Emergency strategy optimization for the environmental control system in manned spacecraft
Li, Guoxiang; Pang, Liping; Liu, Meng; Fang, Yufeng; Zhang, Helin
2018-02-01
It is very important for a manned environmental control system (ECS) to be able to reconfigure its operation strategy in emergency conditions. In this article, a multi-objective optimization is established to design the optimal emergency strategy for an ECS in an insufficient power supply condition. The maximum ECS lifetime and the minimum power consumption are chosen as the optimization objectives. Some adjustable key variables are chosen as the optimization variables, which finally represent the reconfigured emergency strategy. The non-dominated sorting genetic algorithm-II is adopted to solve this multi-objective optimization problem. Optimization processes are conducted at four different carbon dioxide partial pressure control levels. The study results show that the Pareto-optimal frontiers obtained from this multi-objective optimization can represent the relationship between the lifetime and the power consumption of the ECS. Hence, the preferred emergency operation strategy can be recommended for situations when there is suddenly insufficient power.
Li, Zejing
2012-01-01
This dissertation is mainly devoted to the research of two problems - the continuous-time portfolio optimization in different Wishart models and the effects of discrete rebalancing on portfolio wealth distribution and optimal portfolio strategy.
Verification and synthesis of optimal decision strategies for complex systems
Energy Technology Data Exchange (ETDEWEB)
Summers, S. J.
2013-07-01
that quantifies the probability of hitting a target set at some point during a finite time horizon, while avoiding an obstacle set during each time step preceding the target hitting time. In contrast with the general reach-avoid formulation, which assumes that the target and obstacle sets are constant and deterministic, we allow these sets to be both time-varying and probabilistic. An optimal reach-avoid control policy is derived as the solution to an optimal control problem via dynamic programming. A framework for analyzing probabilistic safety and reachability problems for discrete time stochastic hybrid systems in scenarios where system dynamics are affected by rational competing agents follows. We consider a zero sum game formulation of the probabilistic reach-avoid problem, in which the control objective is to maximize the probability of reaching a desired subset of the hybrid state space, while avoiding an unsafe set, subject to the worst case behavior of a rational adversary. Theoretical results are provided on a dynamic programming algorithm for computing the maximal reach-avoid probability under the worst-case adversary strategy, as well as the existence of a maxmin control policy that achieves this probability. Probabilistic Computation Tree Logic (PCTL) is a well-known modal logic that has become a standard for expressing temporal properties of finite state Markov chains in the context of automated model checking. Here we consider PCTL for non countable-space Markov chains, and we show that there is a substantial affinity between certain of its operators and problems of dynamic programming. We prove some basic properties of the solutions to the latter. The dissertation concludes with a collection of computational examples in the areas of ecology, robotics, aerospace, and finance. (author)
Verification and synthesis of optimal decision strategies for complex systems
International Nuclear Information System (INIS)
Summers, S. J.
2013-01-01
that quantifies the probability of hitting a target set at some point during a finite time horizon, while avoiding an obstacle set during each time step preceding the target hitting time. In contrast with the general reach-avoid formulation, which assumes that the target and obstacle sets are constant and deterministic, we allow these sets to be both time-varying and probabilistic. An optimal reach-avoid control policy is derived as the solution to an optimal control problem via dynamic programming. A framework for analyzing probabilistic safety and reachability problems for discrete time stochastic hybrid systems in scenarios where system dynamics are affected by rational competing agents follows. We consider a zero sum game formulation of the probabilistic reach-avoid problem, in which the control objective is to maximize the probability of reaching a desired subset of the hybrid state space, while avoiding an unsafe set, subject to the worst case behavior of a rational adversary. Theoretical results are provided on a dynamic programming algorithm for computing the maximal reach-avoid probability under the worst-case adversary strategy, as well as the existence of a maxmin control policy that achieves this probability. Probabilistic Computation Tree Logic (PCTL) is a well-known modal logic that has become a standard for expressing temporal properties of finite state Markov chains in the context of automated model checking. Here we consider PCTL for non countable-space Markov chains, and we show that there is a substantial affinity between certain of its operators and problems of dynamic programming. We prove some basic properties of the solutions to the latter. The dissertation concludes with a collection of computational examples in the areas of ecology, robotics, aerospace, and finance. (author)
Computing Optimal Stochastic Portfolio Execution Strategies: A Parametric Approach Using Simulations
Moazeni, Somayeh; Coleman, Thomas F.; Li, Yuying
2010-09-01
Computing optimal stochastic portfolio execution strategies under appropriate risk consideration presents great computational challenge. We investigate a parametric approach for computing optimal stochastic strategies using Monte Carlo simulations. This approach allows reduction in computational complexity by computing coefficients for a parametric representation of a stochastic dynamic strategy based on static optimization. Using this technique, constraints can be similarly handled using appropriate penalty functions. We illustrate the proposed approach to minimize the expected execution cost and Conditional Value-at-Risk (CVaR).
Directory of Open Access Journals (Sweden)
Fábio Neves de Carvalho da Silva Maia
2010-01-01
Full Text Available Este trabalho avalia os retornos e os riscos de estratégias de hedge para as dez principais regiões produtoras de soja do Brasil em relação aos contratos futuros de soja da Chicago Board of Trade (CBOT. Verificou-se que as bases apresentaram padrão bem definido: fortalecimento entre maio e novembro, seguido por enfraquecimento nos seis meses subsequentes. Os hedgers de compra possuem oportunidades de obter retornos brutos maiores, mas os riscos envolvidos nas estratégias de hedge de compra também são maiores. Conclui-se que os contratos de soja em grão da CBOT apresentam diferentes possibilidades de retornos brutos em função do tipo de hedge, do período hedgeado e do contrato utilizado. Logo, as informações disponibilizadas neste trabalho se apresentam como importante subsídio ao processo de tomada de decisão por parte dos agentes da cadeia agroindustrial da soja.This paper analyzes the return and risks of hedging strategies of the major ten soybean producing regions in Brazil concerning Chicago Board of Trade (CBOT future contracts. It was verified that the bases presented a well defined pattern characterized by strengthening from May to November and weakening in the remaining months. Long hedging had larger returns and larger risks comparing with short hedging. The conclusion of this study is that the CBOT soybean contracts present different returns depending on the type of hedging, on the period of hedging, and on the contract used. Therefore, the information presented in this paper is very important to support the decision making process in the Brazilian soybean agricultural system.
Optimal Stochastic Advertising Strategies for the U.S. Beef Industry
Kun C. Lee; Stanley Schraufnagel; Earl O. Heady
1982-01-01
An important decision variable in the promotional strategy for the beef sector is the optimal level of advertising expenditures over time. Optimal stochastic and deterministic advertising expenditures are derived for the U.S. beef industry for the period `1966 through 1980. They are compared with historical levels and gains realized by optimal advertising strategies are measured. Finally, the optimal advertising expenditures in the future are forecasted.
International Nuclear Information System (INIS)
Gao, Jiajia; Huang, Gongsheng; Xu, Xinhua
2016-01-01
Highlights: • An optimization strategy for a small-scale air-conditioning system is developed. • The optimization strategy aims at optimizing the overall system energy consumption. • The strategy may guarantee the robust control of the space air temperature. • The performance of the optimization strategy was tested on a simulation platform. - Abstract: This paper studies the optimization of a small-scale central air-conditioning system, in which the cooling is provided by a ground source heat pump (GSHP) equipped with an on/off capacity control. The optimization strategy aims to optimize the overall system energy consumption and simultaneously guarantee the robustness of the space air temperature control without violating the allowed GSHP maximum start-ups number per hour specified by customers. The set-point of the chilled water return temperature and the width of the water temperature control band are used as the decision variables for the optimization. The performance of the proposed strategy was tested on a simulation platform. Results show that the optimization strategy can save the energy consumption by 9.59% in a typical spring day and 2.97% in a typical summer day. Meanwhile it is able to enhance the space air temperature control robustness when compared with a basic control strategy without optimization.
Noninfectious uveitis: strategies to optimize treatment compliance and adherence
Directory of Open Access Journals (Sweden)
Dolz-Marco R
2015-08-01
Full Text Available Rosa Dolz-Marco,1 Roberto Gallego-Pinazo,1 Manuel Díaz-Llopis,2 Emmett T Cunningham Jr,3–6 J Fernando Arévalo7,8 1Unit of Macula, Department of Ophthalmology, University and Polytechnic Hospital La Fe, 2Faculty of Medicine, University of Valencia, Spain; 3Department of Ophthalmology, California Pacific Medical Center, San Francisco, 4Department of Ophthalmology, Stanford University School of Medicine, Stanford, 5The Francis I Proctor Foundation, University of California San Francisco Medical Center, 6West Coast Retina Medical Group, San Francisco, CA, USA; 7Vitreoretina Division, King Khaled Eye Specialist Hospital, Riyadh, Saudi Arabia; 8Retina Division, Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA Abstract: Noninfectious uveitis includes a heterogenous group of sight-threatening ocular and systemic disorders. Significant progress has been made in the treatment of noninfectious uveitis in recent years, particularly with regard to the effective use of corticosteroids and non-corticosteroid immunosuppressive drugs, including biologic agents. All of these therapeutic approaches are limited, however, by any given patient’s ability to comply with and adhere to their prescribed treatment. In fact, compliance and adherence are among the most important patient-related determinants of treatment success. We discuss strategies to optimize compliance and adherence. Keywords: noninfectious uveitis, intraocular inflammation, immunosuppressive treatment, adherence, compliance, therapeutic failure
Optimal breast cancer screening strategies for older women: current perspectives
Directory of Open Access Journals (Sweden)
Braithwaite D
2016-02-01
Full Text Available Dejana Braithwaite,1 Joshua Demb,1 Louise M Henderson2 1Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, 2Department of Radiology, University of North Carolina, Chapel Hill, NC, USA Abstract: Breast cancer is a major cause of cancer-related deaths among older women, aged 65 years or older. Screening mammography has been shown to be effective in reducing breast cancer mortality in women aged 50–74 years but not among those aged 75 years or older. Given the large heterogeneity in comorbidity status and life expectancy among older women, controversy remains over screening mammography in this population. Diminished life expectancy with aging may decrease the potential screening benefit and increase the risk of harms. In this review, we summarize the evidence on screening mammography utilization, performance, and outcomes and highlight evidence gaps. Optimizing the screening strategy will involve separating older women who will benefit from screening from those who will not benefit by using information on comorbidity status and life expectancy. This review has identified areas related to screening mammography in older women that warrant additional research, including the need to evaluate emerging screening technologies, such as tomosynthesis among older women and precision cancer screening. In the absence of randomized controlled trials, the benefits and harms of continued screening mammography in older women need to be estimated using both population-based cohort data and simulation models. Keywords: aging, breast cancer, precision cancer screening
An Optimal Investment Strategy for Insurers in Incomplete Markets
Directory of Open Access Journals (Sweden)
Mohamed Badaoui
2018-04-01
Full Text Available In this paper we consider the problem of an insurance company where the wealth of the insurer is described by a Cramér-Lundberg process. The insurer is allowed to invest in a risky asset with stochastic volatility subject to the influence of an economic factor and the remaining surplus in a bank account. The price of the risky asset and the economic factor are modeled by a system of correlated stochastic differential equations. In a finite horizon framework and assuming that the market is incomplete, we study the problem of maximizing the expected utility of terminal wealth. When the insurer’s preferences are exponential, an existence and uniqueness theorem is proven for the non-linear Hamilton-Jacobi-Bellman equation (HJB. The optimal strategy and the value function have been produced in closed form. In addition and in order to show the connection between the insurer’s decision and the correlation coefficient we present two numerical approaches: A Monte-Carlo method based on the stochastic representation of the solution of the insurer problem via Feynman-Kac’s formula, and a mixed Finite Difference Monte-Carlo one. Finally the results are presented in the case of Scott model.
Optimizing individual iron deficiency prevention strategies in physiological pregnancy
Directory of Open Access Journals (Sweden)
Kramarskiy V.A.
2018-04-01
Full Text Available Sideropenia by the end of pregnancy takes place in all mothers without exception. Moreover, the selective administration of iron preparations, in contrast to the routine, makes it possible to avoid hemochromatosis, frequency of which in the general population makes from 0.5 to 13 %. The aim of the study was to optimize the individual strategy for the prevention of iron deficiency in physiological pregnancy. A prospective pre-experimental study was conducted, the criterion of inclusion in which was the mother’s extragenital and obstetrical pathology during the first half of pregnancy, a burdened obstetric and gynecological anamnesis. The study group of 98 women with a physiological pregnancy in the period of 20 to 24 weeks was recruited by simple ran- dom selection. Serum ferritin, hemoglobin, and serum iron were used to estimate iron deficiency. In the latent stage of iron deficiency against a background of monthly correction with Fenules ® in a dose of 90 mg of elemental iron per day, there was a significant increase in ferritin and iron in the blood rotor. In healthy mothers, during the gestational period of 20–24 weeks, a regularity arises in the replenishment of iron status, especially in the case of repeated pregnancy, which is successfully satisfied during the month of Fenules ® intake in doses of 45 mg or 90 mg per day with a serum ferritin level of, respectively, 30 up to 70 μg/l or less than 30 μg/l.
Publish or patent: bibliometric evidence for empirical trade-offs in national funding strategies
Shelton, R.D.; Leydesdorff, L.
2012-01-01
Multivariate linear regression models suggest a trade-off in allocations of national research and development (R&D). Government funding and spending in the higher education sector encourage publications as a long-term research benefit. Conversely, other components such as industrial funding and
Trade-offs and efficiencies in optimal budget-constrained multispecies corridor networks
Bistra Dilkina; Rachel Houtman; Carla P. Gomes; Claire A. Montgomery; Kevin S. McKelvey; Katherine Kendall; Tabitha A. Graves; Richard Bernstein; Michael K. Schwartz
2016-01-01
Conservation biologists recognize that a system of isolated protected areas will be necessary but insufficient to meet biodiversity objectives. Current approaches to connecting core conservation areas through corridors consider optimal corridor placement based on a single optimization goal: commonly, maximizing the movement for a target species across a...
Dewandaru, Ginanjar; Masih, Rumi; Bacha, Obiyathulla Ismath; Masih, A. Mansur. M.
2015-11-01
We provide a new contribution to trading strategies by using multi-fractal de-trended fluctuation analysis (MF-DFA), imported from econophysics, to complement various momentum strategies. The method provides a single measure that can capture both persistency and anti-persistency in stock prices, accounting for multifractality. This study uses a sample of Islamic stocks listed in the U.S. Dow Jones Islamic market for a sample period covering 16 years starting in 1996. The findings show that the MF-DFA strategy produces monthly excess returns of 6.12%, outperforming other various momentum strategies. Even though the risk of the MF-DFA strategy may be relatively higher, it can still produce a Sharpe ratio of 0.164, which is substantially higher than that of the other strategies. When we control for the MF-DFA factor with the other factors, its pure factor return is still able to yield a monthly excess return of 1.35%. Finally, we combine the momentum and MF-DFA strategies, with the proportions of 90/10, 80/20, and 70/30 and by doing so we demonstrate that the MF-DFA measure can boost the total monthly excess returns as well as Sharpe ratio. The value added is non-linear which implies that the additional returns are associated with lower incremental risk.
DEFF Research Database (Denmark)
Jiang, Yuewen; Chen, Meisen; You, Shi
2017-01-01
In a conventional electricity market, trading is conducted based on power forecasts in the day-ahead market, while the power imbalance is regulated in the real-time market, which is a separate trading scheme. With large-scale wind power connected into the power grid, power forecast errors increase...... in the day-ahead market which lowers the economic efficiency of the separate trading scheme. This paper proposes a robust unified trading model that includes the forecasts of real-time prices and imbalance power into the day-ahead trading scheme. The model is developed based on robust optimization in view...... of the undefined probability distribution of clearing prices of the real-time market. For the model to be used efficiently, an improved quantum-behaved particle swarm algorithm (IQPSO) is presented in the paper based on an in-depth analysis of the limitations of the static character of quantum-behaved particle...
Performance and Cost Trade-off in Tracking Area Reconfiguration: A Pareto-optimization Approach
Modarres Razavi, Sara; Yuan, Di; Gunnarsson, Fredrik; Moe, Johan
2012-01-01
Tracking Area (TA) design is one of the key tasks in location management of Long Term Evolution (LTE) networks. TA enables to trace and page User Equipments (UEs). As UEs distribution and mobility patterns change over time, TA design may have to undergo revisions. For revising the TA design, the cells to be reconfigured typically have to be temporary torn down. Consequently, this will result in service interruption and “cost”. There is always a trade-off between the performance in terms of th...
Liquidity Risk, Speculative Trade, and the Optimal Latency of Financial Markets
Fricke, Daniel; Gerig, Austin
2014-01-01
Garbade and Silber (1979) demonstrate that an asset will be liquid if it has (1) low price volatility and (2) a large number of public investors who trade it. Although these results match nicely with common notions of liquidity, one key element is missing: liquidity also depends on (3) an asset s correlation with other securities. For example, if an illiquid asset is highly correlated with a liquid asset, then speculators will naturally step in and make it liquid . In this paper, we update Ga...
Directory of Open Access Journals (Sweden)
Miguel Ángel Gómez-Serrano
Full Text Available Predation is one of the main causes of adult mortality and breeding failure for ground-nesting birds. Micro-habitat structure around nests plays a critical role in minimizing predation risk. Plovers nest in sites with little vegetation cover to maximize the incubating adult visibility, but many studies suggest a trade-off between nest-crypsis and predator detection strategies. However, this trade-off has not been explored in detail because methods used so far do not allow estimating the visibility with regards to critical factors such as slope or plant permeability to vision. Here, we tested the hypothesis that Kentish plovers select exposed sites according to a predator detection strategy, and the hypothesis that more concealed nests survive longer according to a crypsis strategy. To this end, we obtained an accurate estimation of the incubating adult's field of vision through a custom built inverted periscope. Our results showed that plovers selected nest sites with higher visibility than control points randomly selected with regards to humans and dogs, although nests located in sites with higher vegetation cover survived longer. In addition, the flushing distance (i.e., the distance at which incubating adults leave the nest when they detect a potential predator decreased with vegetation cover. Consequently, the advantages of concealing the nest were limited by the ability to detect predators, thus indirectly supporting the existence of the trade-off between crypsis and predator detection. Finally, human disturbance also constrained nest choice, forcing plovers to move to inland sites that were less suitable because of higher vegetation cover, and modulated flushing behavior, since plovers that were habituated to humans left their nests closer to potential predators. This constraint on the width of suitable breeding habitat is particularly relevant for the conservation of Kentish Plover in sand beaches, especially under the current context of
Directory of Open Access Journals (Sweden)
Hugh Stephens
2018-01-01
Full Text Available There has been considerable coverage lately of Canada’s ongoing efforts to secure preferential access to overseas markets in Asia, while trying to save NAFTA and promote its “progressive” trade agenda. The “progressive” trade agenda hit a few recent road bumps, first in Vietnam in November when a planned announcement of an “agreement in principle” on the “TPP 11 Agreement” was postponed at the last minute, and in December in Beijing when Chinese authorities balked at including additional “progressive” chapters in a free trade agreement, the negotiation of which many expected would be announced during Mr. Trudeau’s visit. Although a breakthrough on the TPP11, now known as the Comprehensive and Progressive Trans-Pacific Partnership, was announced on January 23, NAFTA negotiations continue to be difficult. One area that has been overlooked in all the coverage of recent events, and which holds potential for advancing Canadian trade interests in both Latin America and the Asia Pacific, is the Pacific Alliance and Canada’s pursuit of associate member status. The PA trade pact, comprising Chile, Colombia, Mexico and Peru, is currently in the process of discussing with several countries, including Canada, the possibility of becoming “associate members.” Associate member status is novel, thus it is not clear what precisely it will entail or when it will come into effect. However, the possibility of Canada moving from its current "observer" status to becoming a more active part of the PA (or possibly an expanded version of the Alliance, offers significant benefit for Canada. For all the focus on the TPP and the NAFTA renegotiations, not to mention Canada’s recently concluded economic partnership agreement with the EU and potential free-trade negotiations with China, very little attention has been paid in Canada to the developments with the PA. And yet, this is one trade bloc that holds some of the greatest promise for
Polymerase chain reaction: basic protocol plus troubleshooting and optimization strategies.
Lorenz, Todd C
2012-05-22
In the biological sciences there have been technological advances that catapult the discipline into golden ages of discovery. For example, the field of microbiology was transformed with the advent of Anton van Leeuwenhoek's microscope, which allowed scientists to visualize prokaryotes for the first time. The development of the polymerase chain reaction (PCR) is one of those innovations that changed the course of molecular science with its impact spanning countless subdisciplines in biology. The theoretical process was outlined by Keppe and coworkers in 1971; however, it was another 14 years until the complete PCR procedure was described and experimentally applied by Kary Mullis while at Cetus Corporation in 1985. Automation and refinement of this technique progressed with the introduction of a thermal stable DNA polymerase from the bacterium Thermus aquaticus, consequently the name Taq DNA polymerase. PCR is a powerful amplification technique that can generate an ample supply of a specific segment of DNA (i.e., an amplicon) from only a small amount of starting material (i.e., DNA template or target sequence). While straightforward and generally trouble-free, there are pitfalls that complicate the reaction producing spurious results. When PCR fails it can lead to many non-specific DNA products of varying sizes that appear as a ladder or smear of bands on agarose gels. Sometimes no products form at all. Another potential problem occurs when mutations are unintentionally introduced in the amplicons, resulting in a heterogeneous population of PCR products. PCR failures can become frustrating unless patience and careful troubleshooting are employed to sort out and solve the problem(s). This protocol outlines the basic principles of PCR, provides a methodology that will result in amplification of most target sequences, and presents strategies for optimizing a reaction. By following this PCR guide, students should be able to: • Set up reactions and thermal cycling
Strategies towards an optimized use of the shallow geothermal potential
Schelenz, S.; Firmbach, L.; Kalbacher, T.; Goerke, U.; Kolditz, O.; Dietrich, P.; Vienken, T.
2013-12-01
Thermal use of the shallow subsurface for heat generation, cooling and thermal energy storage is increasingly gaining importance in reconsideration of future energy supplies, e.g. in the course of German energy transition, with application shifting from isolated to intensive use. The planning and dimensioning of (geo-)thermal applications is strongly influenced by the availability of exploration data. Hence, reliable site-specific dimensioning of systems for the thermal use of the shallow subsurface will contribute to an increase in resource efficiency, cost reduction during installation and operation, as well as reduction of environmental impacts and prevention of resource over-exploitation. Despite large cumulative investments that are being made for the utilization of the shallow thermal potential, thermal energy is in many cases exploited without prior on-site exploration and investigation of the local geothermal potential, due to the lack of adequate and cost-efficient exploration techniques. We will present new strategies for an optimized utilization of urban thermal potential, showcased at a currently developed residential neighborhood with high demand for shallow geothermal applications, based on a) enhanced site characterization and b) simulation of different site specific application scenarios. For enhanced site characterization, surface geophysics and vertical high resolution direct push-profiling were combined for reliable determination of aquifer structure and aquifer parameterization. Based on the site characterization, different site specific geothermal application scenarios, including different system types and system configurations, were simulated using OpenGeoSys to guarantee an environmental and economic sustainable thermal use of the shallow subsurface.
Bacterial Quorum Sensing Stabilizes Cooperation by Optimizing Growth Strategies.
Bruger, Eric L; Waters, Christopher M
2016-11-15
Communication has been suggested as a mechanism to stabilize cooperation. In bacteria, chemical communication, termed quorum sensing (QS), has been hypothesized to fill this role, and extracellular public goods are often induced by QS at high cell densities. Here we show, with the bacterium Vibrio harveyi, that QS provides strong resistance against invasion of a QS defector strain by maximizing the cellular growth rate at low cell densities while achieving maximum productivity through protease upregulation at high cell densities. In contrast, QS mutants that act as defectors or unconditional cooperators maximize either the growth rate or the growth yield, respectively, and thus are less fit than the wild-type QS strain. Our findings provide experimental evidence that regulation mediated by microbial communication can optimize growth strategies and stabilize cooperative phenotypes by preventing defector invasion, even under well-mixed conditions. This effect is due to a combination of responsiveness to environmental conditions provided by QS, lowering of competitive costs when QS is not induced, and pleiotropic constraints imposed on defectors that do not perform QS. Cooperation is a fundamental problem for evolutionary biology to explain. Conditional participation through phenotypic plasticity driven by communication is a potential solution to this dilemma. Thus, among bacteria, QS has been proposed to be a proximate stabilizing mechanism for cooperative behaviors. Here, we empirically demonstrate that QS in V. harveyi prevents cheating and subsequent invasion by nonproducing defectors by maximizing the growth rate at low cell densities and the growth yield at high cell densities, whereas an unconditional cooperator is rapidly driven to extinction by defectors. Our findings provide experimental evidence that QS regulation prevents the invasion of cooperative populations by QS defectors even under unstructured conditions, and they strongly support the role of
Glaser, Markus
2003-01-01
It is often argued that the internet influences investor behavior. Furthermore, the recent 'bubble' in internet stocks is sometimes ascribed, at least in part, to online trading. However, little is known about how online investors actually behave. This paper contributes to fill this gap. A sample of approximately 3,000 online broker investors is studied over a 51 month period ending in April 2001. The main goal of this paper is to present various descriptive statistics on demographic informat...
International Nuclear Information System (INIS)
Okamoto, Takashi; Hanaoka, Yuya; Aiyoshi, Eitaro; Kobayashi, Yoko
2012-01-01
In this paper, we consider a multi-objective optimization method in order to obtain a preferred solution for the buffer material optimal design problem in the high-level radioactive wastes geological disposal. The buffer material optimal design problem is formulated as a constrained multi-objective optimization problem. Its Pareto optimal solutions are distributed evenly on whole bounds of the feasible region. Hence, we develop a search method to find a preferred solution easily for a decision maker from the Pareto optimal solutions which are distributed evenly and vastly. In the preferred solution search method, the visualization technique of a Pareto optimal solution set using the self-organizing map is introduced into the satisficing trade-off method which is the interactive method to obtain a Pareto optimal solution that satisfies a decision maker. We confirm the effectiveness of the preferred solution search method in the buffer material optimal design problem. (author)
International Nuclear Information System (INIS)
Wang, Xinli; Cai, Wenjian; Lu, Jiangang; Sun, Youxian; Zhao, Lei
2015-01-01
This study presents a model-based optimization strategy for an actual chiller driven dehumidifier of liquid desiccant dehumidification system operating with lithium chloride solution. By analyzing the characteristics of the components, energy predictive models for the components in the dehumidifier are developed. To minimize the energy usage while maintaining the outlet air conditions at the pre-specified set-points, an optimization problem is formulated with an objective function, the constraints of mechanical limitations and components interactions. Model-based optimization strategy using genetic algorithm is proposed to obtain the optimal set-points for desiccant solution temperature and flow rate, to minimize the energy usage in the dehumidifier. Experimental studies on an actual system are carried out to compare energy consumption between the proposed optimization and the conventional strategies. The results demonstrate that energy consumption using the proposed optimization strategy can be reduced by 12.2% in the dehumidifier operation. - Highlights: • Present a model-based optimization strategy for energy saving in LDDS. • Energy predictive models for components in dehumidifier are developed. • The Optimization strategy are applied and tested in an actual LDDS. • Optimization strategy can achieve energy savings by 12% during operation
International Nuclear Information System (INIS)
Tan, Raymond R.; Aviso, Kathleen B.; Barilea, Ivan U.; Culaba, Alvin B.; Cruz, Jose B.
2012-01-01
Interest in bioenergy in recent years has been stimulated by both energy security and climate change concerns. Fuels derived from agricultural crops offer the promise of reducing energy dependence for countries that have traditionally been dependent on imported energy. Nevertheless, it is evident that the potential for biomass production is heavily dependent on the availability of land and water resources. Furthermore, capacity expansion through land conversion is now known to incur a significant carbon debt that may offset any benefits in greenhouse gas reductions arising from the biofuel life cycle. Because of such constraints, there is increasing use of non-local biomass through regional trading. The main challenge in the analysis of such arrangements is that individual geographic regions have their own respective goals. This work presents a multi-region, fuzzy input–output optimization model that reflects production and consumption of bioenergy under land, water and carbon footprint constraints. To offset any local production deficits or surpluses, the model allows for trade to occur among different regions within a defined system; furthermore, importation of additional biofuel from external sources is also allowed. Two illustrative case studies are given to demonstrate the key features of the model.
International Nuclear Information System (INIS)
Koo, Jamin; Han, Kyusang; Yoon, En Sup
2011-01-01
In this paper, a new approach has been proposed that allows a robust optimization of sustainable energy planning over a period of years. It is based on the modified energy flow optimization model (EFOM) and minimizes total costs in planning capacities of power plants and CCS to be added, stripped or retrofitted. In the process, it reduces risks due to a high volatility in fuel prices; it also provides robustness against infeasibility with respect to meeting the required emission level by adopting a penalty constant that corresponds to the price level of emission allowances. In this manner, the proposed methodology enables decision makers to determine the optimal capacities of power plants and/or CCS, as well as volumes of emissions trading in the future that will meet the required emission level and satisfy energy demand from various user-sections with minimum costs and maximum robustness. They can also gain valuable insights on the effects that the price of emission allowances has on the competitiveness of RES and CCS technologies; it may be used in, for example, setting appropriate subsidies and tax policies for promoting greater use of these technologies. The proposed methodology is applied to a case based on directions and volumes of energy flows in South Korea during the year 2008. (author)
Optimal Policies for Deteriorating Items with Maximum Lifetime and Two-Level Trade Credits
Directory of Open Access Journals (Sweden)
Nita H. Shah
2014-01-01
Full Text Available The retailer’s optimal policies are developed when the product has fixed lifetime and also the units in inventory are subject to deterioration at a constant rate. This study will be mainly applicable to pharmaceuticals, drugs, beverages, and dairy products, and so forth. To boost the demand, offering a credit period is considered as the promotional tool. The retailer passes credit period to the buyers which is received from the supplier. The objective is to maximize the total profit per unit time of the retailer with respect to optimal retail price of an item and purchase quantity during the optimal cycle time. The concavity of the total profit per unit time is exhibited using inventory parametric values. The sensitivity analysis is carried out to advise the decision maker to keep an eye on critical inventory parameters.
Yen, Ghi-Feng; Chung, Kun-Jen; Chen, Tzung-Ching
2012-11-01
The traditional economic order quantity model assumes that the retailer's storage capacity is unlimited. However, as we all know, the capacity of any warehouse is limited. In practice, there usually exist various factors that induce the decision-maker of the inventory system to order more items than can be held in his/her own warehouse. Therefore, for the decision-maker, it is very practical to determine whether or not to rent other warehouses. In this article, we try to incorporate two levels of trade credit and two separate warehouses (own warehouse and rented warehouse) to establish a new inventory model to help the decision-maker to make the decision. Four theorems are provided to determine the optimal cycle time to generalise some existing articles. Finally, the sensitivity analysis is executed to investigate the effects of the various parameters on ordering policies and annual costs of the inventory system.
Directory of Open Access Journals (Sweden)
Anuradha Pughat
2016-09-01
Full Text Available Dynamic voltage scaling contributes to a significant amount of power saving, especially in the energy constrained wireless sensor networks (WSNs. Existing dynamic voltage scaling techniques make the system slower and ignore the event miss rate. This results in degradation of the system performance when there is non-stationary workload at input. The overhead due to transition between voltage level and discrete voltage levels are also the limitations of available dynamic voltage scaling (DVS techniques at sensor node (SN. This paper proposes a workload dependent DVS based MSP430 controller model used for SN. An online gradient estimation technique has been used to optimize power and performance trade-offs. The analytical results are validated with the simulation results obtained using simulation tool “SimEvents” and compared with the available AT9OS8535 controller. Based on the stochastic workload, the controller's input voltage, operational frequency, utilization, and average wait time of events are obtained.
Optimal strategy analysis based on robust predictive control for inventory system with random demand
Saputra, Aditya; Widowati, Sutrisno
2017-12-01
In this paper, the optimal strategy for a single product single supplier inventory system with random demand is analyzed by using robust predictive control with additive random parameter. We formulate the dynamical system of this system as a linear state space with additive random parameter. To determine and analyze the optimal strategy for the given inventory system, we use robust predictive control approach which gives the optimal strategy i.e. the optimal product volume that should be purchased from the supplier for each time period so that the expected cost is minimal. A numerical simulation is performed with some generated random inventory data. We simulate in MATLAB software where the inventory level must be controlled as close as possible to a set point decided by us. From the results, robust predictive control model provides the optimal strategy i.e. the optimal product volume that should be purchased and the inventory level was followed the given set point.
Implementation of an optimal control energy management strategy in a hybrid truck
Mullem, D. van; Keulen, T. van; Kessels, J.T.B.A.; Jager, B. de; Steinbuch, M.
2010-01-01
Energy Management Strategies for hybrid powertrains control the power split, between the engine and electric motor, of a hybrid vehicle, with fuel consumption or emission minimization as objective. Optimal control theory can be applied to rewrite the optimization problem to an optimization
Li, Rui
2009-01-01
The target of this work is to extend the canonical Evolution Strategies (ES) from traditional real-valued parameter optimization domain to mixed-integer parameter optimization domain. This is necessary because there exist numerous practical optimization problems from industry in which the set of
Sampling optimization trade-offs for long-term monitoring of gamma dose rates
Melles, S.J.; Heuvelink, G.B.M.; Twenhöfel, C.J.W.; Stöhlker, U.
2008-01-01
This paper applies a recently developed optimization method to examine the design of networks that monitor radiation under routine conditions. Annual gamma dose rates were modelled by combining regression with interpolation of the regression residuals using spatially exhaustive predictors and an
Anodic Cyclization Reactions and the Mechanistic Strategies That Enable Optimization.
Feng, Ruozhu; Smith, Jake A; Moeller, Kevin D
2017-09-19
Oxidation reactions are powerful tools for synthesis because they allow us to reverse the polarity of electron-rich functional groups, generate highly reactive intermediates, and increase the functionality of molecules. For this reason, oxidation reactions have been and continue to be the subject of intense study. Central to these efforts is the development of mechanism-based strategies that allow us to think about the reactive intermediates that are frequently central to the success of the reactions and the mechanistic pathways that those intermediates trigger. For example, consider oxidative cyclization reactions that are triggered by the removal of an electron from an electron-rich olefin and lead to cyclic products that are functionalized for further elaboration. For these reactions to be successful, the radical cation intermediate must first be generated using conditions that limit its polymerization and then channeled down a productive desired pathway. Following the cyclization, a second oxidation step is necessary for product formation, after which the resulting cation must be quenched in a controlled fashion to avoid undesired elimination reactions. Problems can arise at any one or all of these steps, a fact that frequently complicates reaction optimization and can discourage the development of new transformations. Fortunately, anodic electrochemistry offers an outstanding opportunity to systematically probe the mechanism of oxidative cyclization reactions. The use of electrochemical methods allows for the generation of radical cations under neutral conditions in an environment that helps prevent polymerization of the intermediate. Once the intermediates have been generated, a series of "telltale indicators" can be used to diagnose which step in an oxidative cyclization is problematic for less successful transformation. A set of potential solutions to address each type of problem encountered has been developed. For example, problems with the initial
Offshore Wind Farm Layout Design Considering Optimized Power Dispatch Strategy
DEFF Research Database (Denmark)
Hou, Peng; Hu, Weihao; N. Soltani, Mohsen
2017-01-01
Offshore wind farm has drawn more and more attention recently due to its higher energy capacity and more freedom to occupy area. However, the investment is higher. In order to make a cost-effective wind farm, the wind farm layout should be optimized. The wake effect is one of the dominant factors...... leading to energy losses. It is expected that the optimized placement of wind turbines (WT) over a large sea area can lead to the best tradeoff between energy yields and capital investment. This paper proposes a novel way to position offshore WTs for a regular shaped wind farm. In addition to optimizing...... the direction of wind farm placement and the spacing between WTs, the control strategy’s impact on energy yields is also discussed. Since the problem is non-convex and lots of optimization variables are involved, an evolutionary algorithm, the particle swarm optimization algorithm (PSO), is adopted to find...
An Entropic Approach for Pair Trading
Directory of Open Access Journals (Sweden)
Daisuke Yoshikawa
2017-06-01
Full Text Available In this paper, we derive the optimal boundary for pair trading. This boundary defines the points of entry into or exit from the market for a given stock pair. However, if the assumed model contains uncertainty, the resulting boundary could result in large losses. To avoid this, we develop a more robust strategy by accounting for the model uncertainty. To incorporate the model uncertainty, we use the relative entropy as a penalty function in the expected profit from pair trading.
A risk-averse optimization model for trading wind energy in a market environment under uncertainty
International Nuclear Information System (INIS)
Pousinho, H.M.I.; Mendes, V.M.F.; Catalao, J.P.S.
2011-01-01
In this paper, a stochastic programming approach is proposed for trading wind energy in a market environment under uncertainty. Uncertainty in the energy market prices is the main cause of high volatility of profits achieved by power producers. The volatile and intermittent nature of wind energy represents another source of uncertainty. Hence, each uncertain parameter is modeled by scenarios, where each scenario represents a plausible realization of the uncertain parameters with an associated occurrence probability. Also, an appropriate risk measurement is considered. The proposed approach is applied on a realistic case study, based on a wind farm in Portugal. Finally, conclusions are duly drawn. -- Highlights: → We model uncertainties on energy market prices and wind power production. → A hybrid intelligent approach generates price-wind power scenarios. → Risk aversion is also incorporated in the proposed stochastic programming approach. → A realistic case study, based on a wind farm in Portugal, is provided. → Our approach allows selecting the best solution according to the desired risk exposure level.
Directory of Open Access Journals (Sweden)
Yuewen Jiang
2017-04-01
Full Text Available In a conventional electricity market, trading is conducted based on power forecasts in the day-ahead market, while the power imbalance is regulated in the real-time market, which is a separate trading scheme. With large-scale wind power connected into the power grid, power forecast errors increase in the day-ahead market which lowers the economic efficiency of the separate trading scheme. This paper proposes a robust unified trading model that includes the forecasts of real-time prices and imbalance power into the day-ahead trading scheme. The model is developed based on robust optimization in view of the undefined probability distribution of clearing prices of the real-time market. For the model to be used efficiently, an improved quantum-behaved particle swarm algorithm (IQPSO is presented in the paper based on an in-depth analysis of the limitations of the static character of quantum-behaved particle swarm algorithm (QPSO. Finally, the impacts of associated parameters on the separate trading and unified trading model are analyzed to verify the superiority of the proposed model and algorithm.
Finding optimal vaccination strategies for pandemic influenza using genetic algorithms.
Patel, Rajan; Longini, Ira M; Halloran, M Elizabeth
2005-05-21
In the event of pandemic influenza, only limited supplies of vaccine may be available. We use stochastic epidemic simulations, genetic algorithms (GA), and random mutation hill climbing (RMHC) to find optimal vaccine distributions to minimize the number of illnesses or deaths in the population, given limited quantities of vaccine. Due to the non-linearity, complexity and stochasticity of the epidemic process, it is not possible to solve for optimal vaccine distributions mathematically. However, we use GA and RMHC to find near optimal vaccine distributions. We model an influenza pandemic that has age-specific illness attack rates similar to the Asian pandemic in 1957-1958 caused by influenza A(H2N2), as well as a distribution similar to the Hong Kong pandemic in 1968-1969 caused by influenza A(H3N2). We find the optimal vaccine distributions given that the number of doses is limited over the range of 10-90% of the population. While GA and RMHC work well in finding optimal vaccine distributions, GA is significantly more efficient than RMHC. We show that the optimal vaccine distribution found by GA and RMHC is up to 84% more effective than random mass vaccination in the mid range of vaccine availability. GA is generalizable to the optimization of stochastic model parameters for other infectious diseases and population structures.
Mahata, Puspita; Mahata, Gour Chandra; Kumar De, Sujit
2018-03-01
Traditional supply chain inventory modes with trade credit usually only assumed that the up-stream suppliers offered the down-stream retailers a fixed credit period. However, in practice the retailers will also provide a credit period to customers to promote the market competition. In this paper, we formulate an optimal supply chain inventory model under two levels of trade credit policy with default risk consideration. Here, the demand is assumed to be credit-sensitive and increasing function of time. The major objective is to determine the retailer's optimal credit period and cycle time such that the total profit per unit time is maximized. The existence and uniqueness of the optimal solution to the presented model are examined, and an easy method is also shown to find the optimal inventory policies of the considered problem. Finally, numerical examples and sensitive analysis are presented to illustrate the developed model and to provide some managerial insights.
Optimal Software Strategies in the Presence of Network Externalities
Liu, Yipeng
2009-01-01
Network externalities or alternatively termed network effects are pervasive in computer software markets. While software vendors consider pricing strategies, they must also take into account the impact of network externalities on their sales. My main interest in this research is to describe a firm's strategies and behaviors in the presence of…
Optimizing the stirring strategy for the vibrating intrinsic reverberation chamber
Serra, Ramiro; Serra, Ramiro; Leferink, Frank Bernardus Johannes
2010-01-01
This work describes the definition, application and assessment of a factorial plan with the aim of gaining insight on what kind of stirring strategy could work the best in a vibrating intrinsic reverberation chamber. Three different stirring strategies were defined as factors of a factorial
Optimal Pricing Strategies for New Products in Dynamic Oligopolies
Engelbert Dockner; Steffen Jørgensen
1988-01-01
This paper deals with the determination of optimal pricing policies for firms in oligopolistic markets. The problem is studied as a differential game and optimal pricing policies are established as Nash open-loop controls. Cost learning effects are assumed such that unit costs are decreasing with cumulative output. Discounting of future profits is also taken into consideration. Initially, the problem is addressed in a general framework, and we proceed to study some specific cases that are rel...
Multi-Objective Optimization of Start-up Strategy for Pumped Storage Units
Directory of Open Access Journals (Sweden)
Jinjiao Hou
2018-05-01
Full Text Available This paper proposes a multi-objective optimization method for the start-up strategy of pumped storage units (PSU for the first time. In the multi-objective optimization method, the speed rise time and the overshoot during the process of the start-up are taken as the objectives. A precise simulation platform is built for simulating the transient process of start-up, and for calculating the objectives based on the process. The Multi-objective Particle Swarm Optimization algorithm (MOPSO is adopted to optimize the widely applied start-up strategies based on one-stage direct guide vane control (DGVC, and two-stage DGVC. Based on the Pareto Front obtained, a multi-objective decision-making method based on the relative objective proximity is used to sort the solutions in the Pareto Front. Start-up strategy optimization for a PSU of a pumped storage power station in Jiangxi Province in China is conducted in experiments. The results show that: (1 compared with the single objective optimization, the proposed multi-objective optimization of start-up strategy not only greatly shortens the speed rise time and the speed overshoot, but also makes the speed curve quickly stabilize; (2 multi-objective optimization of strategy based on two-stage DGVC achieves better solution for a quick and smooth start-up of PSU than that of the strategy based on one-stage DGVC.
Heinsch, Stephen C; Das, Siba R; Smanski, Michael J
2018-01-01
Increasing the final titer of a multi-gene metabolic pathway can be viewed as a multivariate optimization problem. While numerous multivariate optimization algorithms exist, few are specifically designed to accommodate the constraints posed by genetic engineering workflows. We present a strategy for optimizing expression levels across an arbitrary number of genes that requires few design-build-test iterations. We compare the performance of several optimization algorithms on a series of simulated expression landscapes. We show that optimal experimental design parameters depend on the degree of landscape ruggedness. This work provides a theoretical framework for designing and executing numerical optimization on multi-gene systems.
DEFF Research Database (Denmark)
Lund, Henrik; Salgi, Georges; Elmegaard, Brian
2009-01-01
on electricity spot markets by storing energy when electricity prices are low and producing electricity when prices are high. In order to make a profit on such markets, CAES plant operators have to identify proper strategies to decide when to sell and when to buy electricity. This paper describes three...... plants will not be able to achieve such optimal operation, since the fluctuations of spot market prices in the coming hours and days are not known. Consequently, two simple practical strategies have been identified and compared to the results of the optimal strategy. This comparison shows that...... independent computer-based methodologies which may be used for identifying the optimal operation strategy for a given CAES plant, on a given spot market and in a given year. The optimal strategy is identified as the one which provides the best business-economic net earnings for the plant. In practice, CAES...
Trade, Strategy and Communications on the Roman North-East Frontier
DEFF Research Database (Denmark)
Bekker-Nielsen, Tønnes
2016-01-01
The reorganisation of Pontos that Pompey carried out after defeating Mithradates VI Eupator has traditionally been seen as an example of enlightened Roman policy towards the provincials, which included the introduction of civic self-government and the promotion of commercial life. These goals...... Pompey attempted to achieve by establishing five urban communities along an existing east-west artery known as the “Pontic road”. A closer examination of the textual evidence and the actual remains of the “Pontic road”, however, indicate that the road had not been a trade route of any significance before...... the Roman conquest and that the motives behind Pompey’s dispositions were of a strategic, rather than a commercial, nature....
Evaluating trade-offs in bull trout reintroduction strategies using structured decision making
Brignon, William R.; Peterson, James T.; Dunham, Jason B.; Schaller, Howard A.; Schreck, Carl B.
2018-01-01
Structured decision making allows reintroduction decisions to be made despite uncertainty by linking reintroduction goals with alternative management actions through predictive models of ecological processes. We developed a decision model to evaluate the trade-offs between six bull trout (Salvelinus confluentus) reintroduction decisions with the goal of maximizing the number of adults in the recipient population without reducing the donor population to an unacceptable level. Sensitivity analyses suggested that the decision identity and outcome were most influenced by survival parameters that result in increased adult abundance in the recipient population, increased juvenile survival in the donor and recipient populations, adult fecundity rates, and sex ratio. The decision was least sensitive to survival parameters associated with the captive-reared population, the effect of naivety on released individuals, and juvenile carrying capacity of the reintroduced population. The model and sensitivity analyses can serve as the foundation for formal adaptive management and improved effectiveness, efficiency, and transparency of bull trout reintroduction decisions.
Congestion management rules and trading strategies in the Spanish electricity market
Energy Technology Data Exchange (ETDEWEB)
Furio, Dolores; Lucia, Julio J. [Departamento de Economia Financiera y Actuarial, Universidad de Valencia, Avda. Los Naranjos, s/n, 46022 - Valencia (Spain)
2009-01-15
This paper analyses the economic incentives embodied in the rules governing the resolution of transmission constraints in the Spanish wholesale electricity market and the way these incentives may have influenced on the trading behaviour of both the generators and the demand side. The evidence obtained is consistent with them responding to these incentives. In particular, buyers would respond to the way congestion costs are billed to them by abandoning the daily market in favour of the intraday market as far as possible. Additionally, some strategic generators may have been prompted the system operator to require them to inject electricity into the system to solve network congestions. Finally, these results may contribute to shed light on what should be expected of the reform in the aforementioned rules. (author)
Congestion management rules and trading strategies in the Spanish electricity market
International Nuclear Information System (INIS)
Furio, Dolores; Lucia, Julio J.
2009-01-01
This paper analyses the economic incentives embodied in the rules governing the resolution of transmission constraints in the Spanish wholesale electricity market and the way these incentives may have influenced on the trading behaviour of both the generators and the demand side. The evidence obtained is consistent with them responding to these incentives. In particular, buyers would respond to the way congestion costs are billed to them by abandoning the daily market in favour of the intraday market as far as possible. Additionally, some strategic generators may have been prompted the system operator to require them to inject electricity into the system to solve network congestions. Finally, these results may contribute to shed light on what should be expected of the reform in the aforementioned rules. (author)
TRADE AND FOREIGN DIRECT INVESTMENT MANAGEMENT STRATEGIES FOR U.S. PROCESSED FOOD FIRMS IN CHINA
Marchant, Mary A.; Saghaian, Sayed H.; Vickner, Steven S.
1999-01-01
This research examines the relationship between U.S. foreign direct investment (FDI) and exports of processed foods to China and identifies management strategies to enhance U.S. competitiveness. Two-stage least-squares empirical econometric results from a simultaneous equation system indicate that there exists a strong complementary relationship between U.S exports and FDI into China. Therefore, the appropriate managerial strategy to access Chinese processed foods markets is to increase overa...
Optimal Strategy Analysis of a Competing Portfolio Market with a Polyvariant Profit Function
International Nuclear Information System (INIS)
Bogolubov, Nikolai N. Jr.; Kyshakevych, Bohdan Yu.; Blackmore, Denis; Prykarpatsky, Anatoliy K.
2010-12-01
A competing market model with a polyvariant profit function that assumes 'zeitnot' stock behavior of clients is formulated within the banking portfolio medium and then analyzed from the perspective of devising optimal strategies. An associated Markov process method for finding an optimal choice strategy for monovariant and bivariant profit functions is developed. Under certain conditions on the bank 'promotional' parameter with respect to the 'fee' for a missed share package transaction and at an asymptotically large enough portfolio volume, universal transcendental equations - determining the optimal share package choice among competing strategies with monovariant and bivariant profit functions - are obtained. (author)
Gas Chromatograph Method Optimization Trade Study for RESOLVE: 20-meter Column v. 8-meter Column
Huz, Kateryna
2014-01-01
RESOLVE is the payload on a Class D mission, Resource Prospector, which will prospect for water and other volatile resources at a lunar pole. The RESOLVE payload's primary scientific purpose includes determining the presence of water on the moon in the lunar regolith. In order to detect the water, a gas chromatograph (GC) will be used in conjunction with a mass spectrometer (MS). The goal of the experiment was to compare two GC column lengths and recommend which would be best for RESOLVE's purposes. Throughout the experiment, an Inficon Fusion GC and an Inficon Micro GC 3000 were used. The Fusion had a 20m long column with 0.25mm internal diameter (Id). The Micro GC 3000 had an 8m long column with a 0.32mm Id. By varying the column temperature and column pressure while holding all other parameters constant, the ideal conditions for testing with each column length in their individual instrument configurations were determined. The criteria used for determining the optimal method parameters included (in no particular order) (1) quickest run time, (2) peak sharpness, and (3) peak separation. After testing numerous combinations of temperature and pressure, the parameters for each column length that resulted in the most optimal data given my three criteria were selected. The ideal temperature and pressure for the 20m column were 95 C and 50psig. At this temperature and pressure, the peaks were separated and the retention times were shorter compared to other combinations. The Inficon Micro GC 3000 operated better at lower temperature mainly due to the shorter 8m column. The optimal column temperature and pressure were 70 C and 30psig. The Inficon Micro GC 3000 8m column had worse separation than the Inficon Fusion 20m column, but was able to separate water within a shorter run time. Therefore, the most significant tradeoff between the two column lengths was peak separation of the sample versus run time. After performing several tests, it was concluded that better
Application of evolution strategy algorithm for optimization of a single-layer sound absorber
Directory of Open Access Journals (Sweden)
Morteza Gholamipoor
2014-12-01
Full Text Available Depending on different design parameters and limitations, optimization of sound absorbers has always been a challenge in the field of acoustic engineering. Various methods of optimization have evolved in the past decades with innovative method of evolution strategy gaining more attention in the recent years. Based on their simplicity and straightforward mathematical representations, single-layer absorbers have been widely used in both engineering and industrial applications and an optimized design for these absorbers has become vital. In the present study, the method of evolution strategy algorithm is used for optimization of a single-layer absorber at both a particular frequency and an arbitrary frequency band. Results of the optimization have been compared against different methods of genetic algorithm and penalty functions which are proved to be favorable in both effectiveness and accuracy. Finally, a single-layer absorber is optimized in a desired range of frequencies that is the main goal of an industrial and engineering optimization process.
Scout or Cavalry? Optimal Discovery Strategies for GRBs
International Nuclear Information System (INIS)
Nemiroff, Robert J.
2004-01-01
Many present and past gamma-ray burst (GRB) detectors try to be not only a 'scout', discovering new GRBs, but also the 'cavalry', simultaneously optimizing on-board science return. Recently, however, most GRB science return has moved out from the gamma-ray energy bands where discovery usually occurs. Therefore a future gamma-ray instrument that is only a scout might best optimize future GRB science. Such a scout would specialize solely in the initial discovery of GRBs, determining only those properties that would allow an unambiguous handoff to waiting cavalry instruments. Preliminary general principles of scout design and cadence are discussed. Scouts could implement observing algorithms optimized for finding GRBs with specific attributes of duration, location, or energy. Scout sky-scanning algorithms utilizing a return cadence near to desired durations of short GRBs are suggested as a method of discovering GRBs in the unexplored short duration part of the GRB duration distribution
Economic trade-offs amongst production diversification strategies in Brazilian coffee cooperatives
Directory of Open Access Journals (Sweden)
Fellipe Silva Martins
2014-01-01
Full Text Available Brazilian agricultural cooperatives have seen an unprecedented growth in production in the last decade which has led to several different product diversification strategies. Almost all studies in Brazil focus on the financial outcome of these strategies but few empirical studies have addressed them properly. Even fewer researches have dealt with the causes and possible strategies for the diversification of such cooperatives and their impact on their strategic planning. Hence, this paper aims at comprehending the different strategies in operations management for production diversification in coffee-producing cooperatives in south-eastern Brazil. This was done through a multi-case analysis comprising 6 coffee-producing cooperatives. The research analysed both verbal (through interviews and non-verbal (multi-criteria decision analysis responses to the causes of their diversification behaviours. It was possible to find out that most of the cooperatives’ rationale for diversifying is their pre-emptive response to financial crisis followed by increasing the number of associates as a strategy to overcome this economic struggle.
Mohammad Aghaei; Amin Asadollahi; Elham Vahedi; Mahdi Pirooz
2013-01-01
To maintain and achieve optimal growth, development and to be more competitive, organizations need a comprehensive and coherent plan compatible with their objectives and goals which is called strategic planning. This research aims to analyse strategically “Etka Chain Stores” and to propose optimal strategies by using SWOT model and based on fuzzy logic. The scope of this research is limited to “Etka Chain stores in Tehran”. As instrumentation, a questioner, consisting of 138 questions, was us...
Optimizing torque vectoring strategies for an electric vehicle concept
van Boekel, J.J.P.; Besselink, I.J.M.; Nijmeijer, H.; Rauh, J.; Knorr, S.; Durnberger, J.
2013-01-01
As part of the internship project carried out at Daimler AG, this report describes the application and optimization of torque vectoring on a research vehicle based on the Mercedes- Benz SLS AMG E-CELL. A concise introduction is given regarding the MATLAB scripts and Simulink models that were used
Taxing Strategies for Carbon Emissions: A Bilevel Optimization Approach
Directory of Open Access Journals (Sweden)
Wei Wei
2014-04-01
Full Text Available This paper presents a quantitative and computational method to determine the optimal tax rate among generating units. To strike a balance between the reduction of carbon emission and the profit of energy sectors, the proposed bilevel optimization model can be regarded as a Stackelberg game between the government agency and the generation companies. The upper-level, which represents the government agency, aims to limit total carbon emissions within a certain level by setting optimal tax rates among generators according to their emission performances. The lower-level, which represents decision behaviors of the grid operator, tries to minimize the total production cost under the tax rates set by the government. The bilevel optimization model is finally reformulated into a mixed integer linear program (MILP which can be solved by off-the-shelf MILP solvers. Case studies on a 10-unit system as well as a provincial power grid in China demonstrate the validity of the proposed method and its capability in practical applications.
An Optimal Stochastic Investment and Consumption Strategy with ...
African Journals Online (AJOL)
This paper considers a single investor who owns a production plant that generates units of consumption goods in a capitalist economy. The goal is to choose optimal investment and consumption policies that maximize the finite horizon expected discounted logarithmic utility of consumption and terminal wealth. A dynamical ...
Optimal detection and control strategies for invasive species management
Shefali V. Mehta; Robert G. Haight; Frances R. Homans; Stephen Polasky; Robert C. Venette
2007-01-01
The increasing economic and environmental losses caused by non-native invasive species amplify the value of identifying and implementing optimal management options to prevent, detect, and control invasive species. Previous literature has focused largely on preventing introductions of invasive species and post-detection control activities; few have addressed the role of...
Trade-off among different anti-herbivore defence strategies along an altitudinal gradient
Czech Academy of Sciences Publication Activity Database
Dostálek, T.; Rokaya, Maan Bahadur; Maršík, P.; Rezek, J.; Skuhrovec, J.; Pavela, R.; Münzbergová, Z.
2016-01-01
Roč. 8, Jul 11 (2016), č. článku plw026. ISSN 2041-2851 Institutional support: RVO:67179843 Keywords : Climate change * Lamiaceae * VOCs * defence strategies * elevation * greenhouse experiment * insect herbivory * plant–animal interactions Subject RIV: EH - Ecology, Behaviour Impact factor: 2.238, year: 2016
Boundedly rational learning and heterogeneous trading strategies with hybrid neuro-fuzzy models
Bekiros, S.D.
2009-01-01
The present study deals with heterogeneous learning rules in speculative markets where heuristic strategies reflect the rules-of-thumb of boundedly rational investors. The major challenge for "chartists" is the development of new models that would enhance forecasting ability particularly for time
Carbon Emissions Trading and Combined Heat and Power Strategies: Unintended Consequences
Tysseling, John C.; Vosevich, Mary; Boersma, Benjamin R.; Zumwalt, Jefferey A.
2009-01-01
Facility professionals continuously search for projects that reduce energy consumption and operating costs so as to directly benefit their bottom line. Many institutions nationwide have contemplated or made investments in combined heat and power (CHP) projects as a life-cycle strategy to minimize operating costs. However, recent sustainability and…
Trade-off among different anti-herbivore defence strategies along an altitudinal gradient
Czech Academy of Sciences Publication Activity Database
Dostálek, Tomáš; Rokaya, Maan Bahadur; Maršík, Petr; Rezek, Jan; Skuhrovec, J.; Pavela, R.; Münzbergová, Zuzana
2016-01-01
Roč. 8, Jul 11 (2016), č. článku plw026. ISSN 2041-2851 R&D Projects: GA ČR GP13-10850P Institutional support: RVO:67985939 ; RVO:61389030 Keywords : climate change * plant–animal interactions * defence strategies Subject RIV: EF - Botanics; EF - Botanics (UEB-Q) Impact factor: 2.238, year: 2016
Investigating the Optimal Management Strategy for a Healthcare Facility Maintenance Program
National Research Council Canada - National Science Library
Gaillard, Daria
2004-01-01
...: strategic partnering with an equipment management firm. The objective of this study is to create a decision-model for selecting the optimal management strategy for a healthcare organization's facility maintenance program...
Directory of Open Access Journals (Sweden)
Daiki Min
2017-11-01
Full Text Available Recently, much research has focused on lowering carbon emissions in logistics. This paper attempts to contribute to the literature on the joint shipment size and carbon reduction decisions by developing novel models for distribution systems under direct shipment and peddling distribution strategies. Unlike the literature that has simply investigated the effects of carbon costs on operational decisions, we address how to reduce carbon emissions and logistics costs by adjusting shipment size and making an optimal decision on carbon reduction investment. An optimal decision is made by analyzing the distribution cost including not only logistics and carbon trading costs but also the cost for adjusting carbon emission factors. No research has explicitly considered the two sources of carbon emissions, but we develop a model covering the difference in managing carbon emissions from transportation and storage. Structural analysis guides how to determine an optimal shipment size and emission factors in a closed form. Moreover, we analytically prove the possibility of reducing the distribution cost and carbon emissions at the same time. Numerical analysis follows validation of the results and demonstrates some interesting findings on carbon and distribution cost reduction.
Mean-variance Optimal Reinsurance-investment Strategy in Continuous Time
Directory of Open Access Journals (Sweden)
Daheng Peng
2017-10-01
Full Text Available In this paper, Lagrange method is used to solve the continuous-time mean-variance reinsurance-investment problem. Proportional reinsurance, multiple risky assets and risk-free asset are considered synthetically in the optimal strategy for insurers. By solving the backward stochastic differential equation for the Lagrange multiplier, we get the mean-variance optimal reinsurance-investment strategy and its effective frontier in explicit forms.
Ndeffo Mbah , Martial L.; Gilligan , Christopher A.
2010-01-01
Abstract There is growing interest in incorporating economic factors into epidemiological models in order to identify optimal strategies for disease control when resources are limited. In this paper we consider how to optimize the control of a pathogen that is capable of infecting multiple hosts with different rates of transmission within and between species. Our objective is to find control strategies that maximize the discounted number of healthy individuals. We consider two clas...
Directory of Open Access Journals (Sweden)
Musa Danjuma SHEHU
2008-06-01
Full Text Available This paper lays emphasis on formulation of two dimensional differential games via optimal control theory and consideration of control systems whose dynamics is described by a system of Ordinary Differential equation in the form of linear equation under the influence of two controls U(. and V(.. Base on this, strategies were constructed. Hence we determine the optimal strategy for a control say U(. under a perturbation generated by the second control V(. within a given manifold M.
The CEV Model and Its Application in a Study of Optimal Investment Strategy
Directory of Open Access Journals (Sweden)
Aiyin Wang
2014-01-01
Full Text Available The constant elasticity of variance (CEV model is used to describe the price of the risky asset. Maximizing the expected utility relating to the Hamilton-Jacobi-Bellman (HJB equation which describes the optimal investment strategies, we obtain a partial differential equation. Applying the Legendre transform, we transform the equation into a dual problem and obtain an approximation solution and an optimal investment strategies for the exponential utility function.
Mean-variance Optimal Reinsurance-investment Strategy in Continuous Time
Daheng Peng; Fang Zhang
2017-01-01
In this paper, Lagrange method is used to solve the continuous-time mean-variance reinsurance-investment problem. Proportional reinsurance, multiple risky assets and risk-free asset are considered synthetically in the optimal strategy for insurers. By solving the backward stochastic differential equation for the Lagrange multiplier, we get the mean-variance optimal reinsurance-investment strategy and its effective frontier in explicit forms.
Optimized Control Strategy For Over Loaded Offshore Wind Turbines
DEFF Research Database (Denmark)
Odgaard, Peter Fogh; Knudsen, Torben; Wisniewski, Rafal
2015-01-01
controller tuning for a given wind turbine. It also enables a very safe and robust comparison between a new control strategy and the present one. Main body of abstract Is it true that power de-rating indeed the best way to reduce loads? The power de-rating approach has the drawback of only indirectly...
Provencher, Véronique; Desrosiers, Johanne; Demers, Louise; Carmichael, Pierre-Hugues
2016-01-01
This study aimed to (1) determine the categories of behavioral coping strategies most strongly correlated with optimal seniors' social participation in different activity and role domains and (2) identify the demographic, health and environmental factors associated with the use of these coping strategies optimizing social participation. The sample consisted of 350 randomly recruited community-dwelling older adults (≥65 years). Coping strategies and social participation were measured, respectively, using the Inventory of Coping Strategies Used by the Elderly and Assessment of Life Habits questionnaires. Information about demographic, health and environmental factors was also collected during the interview. Regression analyses showed a strong relationship between the use of cooking- and transportation-related coping strategies and optimal participation in the domains of nutrition and community life, respectively. Older age and living alone were associated with increased use of cooking-related strategies, while good self-rated health and not living in a seniors' residence were correlated with greater use of transportation-related strategies. Our study helped to identify useful behavioral coping strategies that should be incorporated in disability prevention programs designed to promote community-dwelling seniors' social participation. However, the appropriateness of these strategies depends on whether they are used in relevant contexts and tailored to specific needs. Our results support the relevance of including behavioral coping strategies related to cooking and transportation in disability prevention programs designed to promote community-dwelling seniors' social participation in the domains of nutrition and community life, respectively. Older age and living alone were associated with increased use of cooking-related strategies, while good self-rated health and not living in a seniors' residence were correlated with greater use of transportation
Maintenance and test strategies to optimize NPP equipment performance
International Nuclear Information System (INIS)
Mayer, S.; Tomic, B.
2000-01-01
This paper proposes an approach to maintenance optimization of nuclear power plant components, which can help to increase both safety and availability. In order to evaluate the benefits of preventive maintenance on a quantitative basis, a software code has been developed for component performance and reliability simulation of safety related nuclear power plant equipment. A three state Markov model will be introduced, considering a degraded state in addition to an operational state and a failed state. (author)
Optimal Input Strategy for Plug and Play Process Control Systems
DEFF Research Database (Denmark)
Kragelund, Martin Nygaard; Leth, John-Josef; Wisniewski, Rafal
2010-01-01
This paper considers the problem of optimal operation of a plant, which goal is to maintain production at minimum cost. The system considered in this work consists of a joined plant and redundant input systems. It is assumed that each input system contributes to a flow of goods into the joined pa...... the performance of the plant. The results are applied to a coal fired power plant where an additional new fuel system, gas, becomes available....
Systems analysis as a tool for optimal process strategy
International Nuclear Information System (INIS)
Ditterich, K.; Schneider, J.
1975-09-01
For the description and the optimal treatment of complex processes, the methods of Systems Analysis are used as the most promising approach in recent times. In general every process should be optimised with respect to reliability, safety, economy and environmental pollution. In this paper the complex relations between these general optimisation postulates are established in qualitative form. These general trend relations have to be quantified for every particular system studied in practice
Optimal Quality Strategy and Matching Service on Crowdfunding Platforms
Directory of Open Access Journals (Sweden)
Wenqing Wu
2018-04-01
Full Text Available This paper develops a crowdfunding platform model incorporating quality and a matching service from the perspective of a two-sided market. It aims to explore the impact of different factors on the optimal quality threshold and matching service in a context of crowdfunding from the perspective of a two-sided market. We discuss the impact of different factors on the optimal quality threshold and matching service. Two important influential factors are under consideration, simultaneously. One is the quality threshold of admission and the other is the matching efficiency on crowdfunding platforms. This paper develops a two-sided market model incorporating quality, a matching service, and the characters of crowdfunding campaigns. After attempting to solve the model by derivative method, this paper identifies the mechanism of how the parameters influence the optimal quality threshold and matching service. Additionally, it compares the platform profits in scenarios with and without an exclusion policy. The results demonstrate that excluding low-quality projects is profitable when funder preference for project quality is substantial enough. Crowdfunding platform managers would be unwise to admit the quality threshold of the crowdfunding project and charge entrance fees when the parameter of funder preference for project quality is small.
Synergies, Conflicts, and Trade-offs of C40 Cities Adaptation Strategies
DEFF Research Database (Denmark)
Driscoll, Patrick Arthur; De Rosa, Michele; Lehmann, Martin
2013-01-01
There is a growing body of literature in the field of urban climate change adaptation planning that indicate a need to address climate change planning measures from a more holistic sustainable development perspective. This paper presents the findings from a recently completed study that indicates...... there remain significant unresolved tensions between the development pathways and the climate change adaptation strategies of the 58 cities within the C40 Cities Climate Leadership Group....
Directory of Open Access Journals (Sweden)
Rizky Luxianto
2014-08-01
Full Text Available This paper wants to explore the effectiveness of momentum or contrarian strategy in Indonesian Stock Exchange using different methods in measuring the performance. The point of momentum or contrarian strategy is selecting winner (stocks with highest gain or loser stocks (stocks with highest loss and then buy or sell it based on the research result. This research employed three methods in measuring performance to select winner and loser stocks. The irst method used cross section relative return, while the second method used cross section relative return plus risk component (return divided by standard deviation, and the third method employed historical relative return instead of cross section. The result is that, all of those three methods prove that momentum strategy is effectively applicable for winner stock, so in the next period winner stock will continue to make profit, while for loser stock, it is more effective to use contrarian strategy because in the next period, loser stock will rebound and make proit after suffering from high loss. ";} // -->activate javascript
Optimalizace vybrané obchodní strategie na měnovém trhu FOREX
KALKUS, Rudolf
2012-01-01
The aim of the thesis was to optimize selected trading strategy in the currency market FOREX. For the optimization was chosen strategy Donchian 5 and 20 and was applied on currency pair EUR/USD. At first was performed backtesting, exit optimization, time optimization and found the importance of position sizing. Then the system was tested in paper trading at broker Admiral Markets, daytrading five minutes chart. Business strategy was optimized and is achieving positive results.
International Nuclear Information System (INIS)
Zhang, Zili; Gao, Chao; Liu, Yuxin; Qian, Tao
2014-01-01
Ant colony optimization (ACO) algorithms often fall into the local optimal solution and have lower search efficiency for solving the travelling salesman problem (TSP). According to these shortcomings, this paper proposes a universal optimization strategy for updating the pheromone matrix in the ACO algorithms. The new optimization strategy takes advantages of the unique feature of critical paths reserved in the process of evolving adaptive networks of the Physarum-inspired mathematical model (PMM). The optimized algorithms, denoted as PMACO algorithms, can enhance the amount of pheromone in the critical paths and promote the exploitation of the optimal solution. Experimental results in synthetic and real networks show that the PMACO algorithms are more efficient and robust than the traditional ACO algorithms, which are adaptable to solve the TSP with single or multiple objectives. Meanwhile, we further analyse the influence of parameters on the performance of the PMACO algorithms. Based on these analyses, the best values of these parameters are worked out for the TSP. (paper)
Directory of Open Access Journals (Sweden)
Min Zhang
2017-11-01
Full Text Available The utilization of forest residue to produce forest biomass energy can mitigate CO2 emissions and generate additional revenue for related eco-enterprises and farmers. In China, however, the benefit of this utilization is still in question because of high costs and CO2 emissions in the entire supply chain. In this paper, a multi-objective linear programming model (MLP is employed to analyze the trade-offs between the economic and environmental benefits of all nodes within the forest biomass power generation supply chain. The MLP model is tested in the Mao Wu Su biomass Thermoelectric Company. The optimization results show that (1 the total cost and CO2 emissions are decreased by US$98.4 thousand and 60.6 thousand kg, respectively; 3750 thousand kg of waste-wood products is reduced and 3750 thousand kg of sandy shrub stubble residue is increased; (2 64% of chipped sandy shrub residue is transported directly from the forestland to the power plant, 36% of non-chipped sandy shrub residue is transported from the forestland to the power plant via the chipping plant; (3 transportation and chipping play a significant role in the supply chain; and (4 the results of a sensitivity analysis show that the farmer’s average transportation distance should be 84.13 km and unit chipping cost should be $0.01022 thousand for the optimization supply cost and CO2 emissions. Finally, we suggest the following: (1 develop long-term cooperation with farmers; (2 buy chain-saws for regularly used farmers; (3 build several chipping plants in areas that are rich in sandy shrub.
Multiresolution strategies for the numerical solution of optimal control problems
Jain, Sachin
There exist many numerical techniques for solving optimal control problems but less work has been done in the field of making these algorithms run faster and more robustly. The main motivation of this work is to solve optimal control problems accurately in a fast and efficient way. Optimal control problems are often characterized by discontinuities or switchings in the control variables. One way of accurately capturing the irregularities in the solution is to use a high resolution (dense) uniform grid. This requires a large amount of computational resources both in terms of CPU time and memory. Hence, in order to accurately capture any irregularities in the solution using a few computational resources, one can refine the mesh locally in the region close to an irregularity instead of refining the mesh uniformly over the whole domain. Therefore, a novel multiresolution scheme for data compression has been designed which is shown to outperform similar data compression schemes. Specifically, we have shown that the proposed approach results in fewer grid points in the grid compared to a common multiresolution data compression scheme. The validity of the proposed mesh refinement algorithm has been verified by solving several challenging initial-boundary value problems for evolution equations in 1D. The examples have demonstrated the stability and robustness of the proposed algorithm. The algorithm adapted dynamically to any existing or emerging irregularities in the solution by automatically allocating more grid points to the region where the solution exhibited sharp features and fewer points to the region where the solution was smooth. Thereby, the computational time and memory usage has been reduced significantly, while maintaining an accuracy equivalent to the one obtained using a fine uniform mesh. Next, a direct multiresolution-based approach for solving trajectory optimization problems is developed. The original optimal control problem is transcribed into a
Directory of Open Access Journals (Sweden)
Jingxian Hao
2016-11-01
Full Text Available The rule-based logic threshold control strategy has been frequently used in energy management strategies for hybrid electric vehicles (HEVs owing to its convenience in adjusting parameters, real-time performance, stability, and robustness. However, the logic threshold control parameters cannot usually ensure the best vehicle performance at different driving cycles and conditions. For this reason, the optimization of key parameters is important to improve the fuel economy, dynamic performance, and drivability. In principle, this is a multiparameter nonlinear optimization problem. The logic threshold energy management strategy for an all-wheel-drive HEV is comprehensively analyzed and developed in this study. Seven key parameters to be optimized are extracted. The optimization model of key parameters is proposed from the perspective of fuel economy. The global optimization method, DIRECT algorithm, which has good real-time performance, low computational burden, rapid convergence, is selected to optimize the extracted key parameters globally. The results show that with the optimized parameters, the engine operates more at the high efficiency range resulting into a fuel savings of 7% compared with non-optimized parameters. The proposed method can provide guidance for calibrating the parameters of the vehicle energy management strategy from the perspective of fuel economy.
A two-level strategy to realize life-cycle production optimization in an operational setting
Essen, van G.M.; Hof, Van den P.M.J.; Jansen, J.D.
2012-01-01
We present a two-level strategy to improve robustness against uncertainty and model errors in life-cycle flooding optimization. At the upper level, a physics-based large-scale reservoir model is used to determine optimal life-cycle injection and production profiles. At the lower level these profiles
A two-level strategy to realize life-cycle production optimization in an operational setting
Essen, van G.M.; Hof, Van den P.M.J.; Jansen, J.D.
2013-01-01
We present a two-level strategy to improve robustness against uncertainty and model errors in life-cycle flooding optimization. At the upper level, a physics-based large-scale reservoir model is used to determine optimal life-cycle injection and production profiles. At the lower level these profiles
Wakano, Joe Yuichiro; Miura, Chiaki
2014-02-01
Inheritance of culture is achieved by social learning and improvement is achieved by individual learning. To realize cumulative cultural evolution, social and individual learning should be performed in this order in one's life. However, it is not clear whether such a learning schedule can evolve by the maximization of individual fitness. Here we study optimal allocation of lifetime to learning and exploitation in a two-stage life history model under a constant environment. We show that the learning schedule by which high cultural level is achieved through cumulative cultural evolution is unlikely to evolve as a result of the maximization of individual fitness, if there exists a trade-off between the time spent in learning and the time spent in exploiting the knowledge that has been learned in earlier stages of one's life. Collapse of a fully developed culture is predicted by a game-theoretical analysis where individuals behave selfishly, e.g., less learning and more exploiting. The present study suggests that such factors as group selection, the ability of learning-while-working ("on the job training"), or environmental fluctuation might be important in the realization of rapid and cumulative cultural evolution that is observed in humans. Copyright © 2013 Elsevier Inc. All rights reserved.
The Optimal Strategy to Research Pension Funds in China Based on the Loss Function
Directory of Open Access Journals (Sweden)
Jian-wei Gao
2007-10-01
Full Text Available Based on the theory of actuarial present value, a pension fund investment goal can be formulated as an objective function. The mean-variance model is extended by defining the objective loss function. Furthermore, using the theory of stochastic optimal control, an optimal investment model is established under the minimum expectation of loss function. In the light of the Hamilton-Jacobi-Bellman (HJB equation, the analytic solution of the optimal investment strategy problem is derived.
The Optimal Strategy to Research Pension Funds in China Based on the Loss Function
Gao, Jian-wei; Guo, Hong-zhen; Ye, Yan-cheng
2007-01-01
Based on the theory of actuarial present value, a pension fund investment goal can be formulated as an objective function. The mean-variance model is extended by defining the objective loss function. Furthermore, using the theory of stochastic optimal control, an optimal investment model is established under the minimum expectation of loss function. In the light of the Hamilton-Jacobi-Bellman (HJB) equation, the analytic solution of the optimal investment strategy problem is derived.
Optimal vaccination strategies against vector-borne diseases
DEFF Research Database (Denmark)
Græsbøll, Kaare; Enøe, Claes; Bødker, Rene
2014-01-01
Using a process oriented semi-agent based model, we simulated the spread of Bluetongue virus by Culicoides, biting midges, between cattle in Denmark. We evaluated the minimum vaccination cover and minimum cost for eight different preventive vaccination strategies in Denmark. The simulation model ...... results when index cases were in the vaccinated areas. However, given that the long-range spread of midge borne disease is still poorly quantified, more robust national vaccination schemes seem preferable....
Optimal Pricing Strategy for Wireless Social Community Networks
Mazloumian, Amin; Manshaei, Mohammad Hossein; Felegyhazi, Mark; Hubaux, Jean-Pierre
2008-01-01
The increasing number of mobile applications fuels the demand for affordable and ubiquitous wireless access. The traditional wireless network technologies such as EV-DO or WiMAX provide this service but require a huge upfront investment in infrastructure and spectrum. On the contrary, as they do not have to face such an investment, social community operators rely on subscribers who constitute a community of users. The pricing strategy of the provided wireless access is an open problem for thi...
In-operation learning of optimal wind farm operation strategy
Oliva Gratacós, Joan
2017-01-01
In a wind farm, power losses due to wind turbine wake effects can be up to 30-40% under certain conditions. As the global installed wind power capacity increases, the mitigation of wake effects in wind farms is gaining more importance. Following a conventional control strategy, each individual turbine maximizes its own power production without taking into consideration its effects on the performance of downstream turbines. Therefore, this control scheme results in operation con...
Optimization Strategy to Capitalize on the Romanian Tourism Potential
PhD Lecturer Dindire Laura; PhD Reader Dugan Silvia
2010-01-01
An important direction of the improvement of promotional activities achieved both by the decisional governmental and non-governmental organisms within the tourist services sector and by the tourism firms, both on an intern and international level, is the promotional strategy. Consisting in the mastership of obtaining the best results, through organizing, coordination, prediction, communication and control activities, the promotional management means knowing and understanding the intern and in...
Fueling strategies to optimize performance: training high or training low?
Burke, L M
2010-10-01
Availability of carbohydrate as a substrate for the muscle and central nervous system is critical for the performance of both intermittent high-intensity work and prolonged aerobic exercise. Therefore, strategies that promote carbohydrate availability, such as ingesting carbohydrate before, during and after exercise, are critical for the performance of many sports and a key component of current sports nutrition guidelines. Guidelines for daily carbohydrate intakes have evolved from the "one size fits all" recommendation for a high-carbohydrate diets to an individualized approach to fuel needs based on the athlete's body size and exercise program. More recently, it has been suggested that athletes should train with low carbohydrate stores but restore fuel availability for competition ("train low, compete high"), based on observations that the intracellular signaling pathways underpinning adaptations to training are enhanced when exercise is undertaken with low glycogen stores. The present literature is limited to studies of "twice a day" training (low glycogen for the second session) or withholding carbohydrate intake during training sessions. Despite increasing the muscle adaptive response and reducing the reliance on carbohydrate utilization during exercise, there is no clear evidence that these strategies enhance exercise performance. Further studies on dietary periodization strategies, especially those mimicking real-life athletic practices, are needed. © 2010 John Wiley & Sons A/S.
Improved quantum-behaved particle swarm optimization with local search strategy
Directory of Open Access Journals (Sweden)
Maolong Xi
2017-03-01
Full Text Available Quantum-behaved particle swarm optimization, which was motivated by analysis of particle swarm optimization and quantum system, has shown compared performance in finding the optimal solutions for many optimization problems to other evolutionary algorithms. To address the problem of premature, a local search strategy is proposed to improve the performance of quantum-behaved particle swarm optimization. In proposed local search strategy, a super particle is presented which is a collection body of randomly selected particles’ dimension information in the swarm. The selected probability of particles in swarm is different and determined by their fitness values. To minimization problems, the fitness value of one particle is smaller; the selected probability is more and will contribute more information in constructing the super particle. In addition, in order to investigate the influence on algorithm performance with different local search space, four methods of computing the local search radius are applied in local search strategy and propose four variants of local search quantum-behaved particle swarm optimization. Empirical studies on a suite of well-known benchmark functions are undertaken in order to make an overall performance comparison among the proposed methods and other quantum-behaved particle swarm optimization. The simulation results show that the proposed quantum-behaved particle swarm optimization variants have better advantages over the original quantum-behaved particle swarm optimization.
Women who sell sex in a Ugandan trading town: life histories, survival strategies and risk.
Gysels, Marjolein; Pool, Robert; Nnalusiba, Betty
2002-01-01
Little is known about the background of commercial sex workers in Africa. This study investigated how women in a trading town on the trans-Africa highway in southwest Uganda become involved in commercial sex work, which factors contribute to their economic success or lack of success, and what effect life trajectories and economic success have on negotiating power and risk behaviour. Over the course of two years detailed life histories of 34 women were collected through recording open, in-depth interviews, the collection of sexual and income and expenditure diaries, visits to the women's native villages, and participant observation. The women share similar disadvantaged backgrounds and this has played a role in their move into commercial sex. They have divergent experiences, however, in their utilisation of opportunities and in the level of success they achieve. They have developed different life styles and a variety of ways of dealing with sexual relationships. Three groups of women were identified: (1) women who work in the back-street bars, have no capital of their own and are almost entirely dependent on selling sex for their livelihood; (2) waitresses in the bars along the main road who engage in a more institutionalised kind of commercial sex, often mediated by middlemen and (3) the more successful entrepreneurs who earn money from their own bars as well as from commercial sex. The three groups had different risk profiles. Due partly to their financial independence from men, women in the latter group have taken control of sexual relationships and can negotiate good sexual deals for themselves, both financially and in terms of safe sex. The poorer women were more vulnerable and less able to negotiate safer sex. A disadvantaged background and restricted access to economic resources are the major reasons for women gravitating to commercial sex work. Various aspects of personality play a role in utilising income from commercial sex to set up an economic basis that
FOREIGN MARKET ENTRY STRATEGIES IN THE UNITED STATES/EUROPEAN UNION AGRIBUSINESS TRADE CONTEXT
Directory of Open Access Journals (Sweden)
Cristina Lelis Leal Calegario
2015-07-01
Full Text Available Our study makes an analysis of American’ multinationals foreign market entry strategies in the European Union agribusiness context. We have used a logistic regression analysis using generalized estimating equation method to make hypothesis about the multinationals’ choices. Our results suggest that American food companies operating in EU appear not to choose their mode of entry based merely on host country factors, but mostly on firm related factors, including firm-specific factors and firm financial performance. Despite the creation of a common institutional framework for M&As in the EU, they are still subject to peculiarities due mostly to organizational characteristics of investing firms.
Integrated Emission Management strategy for cost-optimal engine-aftertreatment operation
Cloudt, R.P.M.; Willems, F.P.T.
2011-01-01
A new cost-based control strategy is presented that optimizes engine-aftertreatment performance under all operating conditions. This Integrated Emission Management strategy minimizes fuel consumption within the set emission limits by on-line adjustment of air management based on the actual state of
Optimization as a Reasoning Strategy for Dealing with Socioscientific Decision-Making Situations
Papadouris, Nicos
2012-01-01
This paper reports on an attempt to help 12-year-old students develop a specific optimization strategy for selecting among possible solutions in socioscientific decision-making situations. We have developed teaching and learning materials for elaborating this strategy, and we have implemented them in two intact classes (N = 48). Prior to and after…
Exploring optimal fertigation strategies for orange production, using soil-crop modelling
Qin, Wei; Heinen, Marius; Assinck, Falentijn B.T.; Oenema, Oene
2016-01-01
Water and nitrogen (N) are two key limiting factors in orange (Citrus sinensis) production. The amount and the timing of water and N application are critical, but optimal strategies have not yet been well established. This study presents an analysis of 47 fertigation strategies examined by a
Strategy of Trade-Reliable Featured Product Supporting Regional Innovation Systems
Riskiawan, H. Y.; Purnomo, B. H.; Abdurahman, A.; Hariono, B.; Puspitasari, T. D.
2018-01-01
Pacitan, Ponorogo, and Magetan had planned the development of featured products as contained in the Medium Term Development Plan (MTDP) until 2020. The focus of development is almost similar to featured products derived from agribusiness, food processing, handycrafts, and tourism. The geographical proximity results characteristics of natural resources and social culture have similarities, including the type of featured products, constraints, problems, and opportunities for development. Given the characteristics and the support system of some featured products contained in these three regions have a lot in common and their functional interactions involving actors from across the region, it is necessary to develop cross-jurisdictional policy. The resulting strategy should be able to support the development of Regional Innovation System (RIS). The purpose of this research is 1) Determining featured product cross-regional between Pacitan regency; Ponorogo and Magetan districts in support of RIS development; and 2) Designing a featured product development strategy using supply chain management in order to drive the local economy. Based on the results of research conducted, featured products across the region that have potentiality to be developed are: processed products of “janggelan” leather products, and woven bamboo.
Optimal Coordinated Strategy Analysis for the Procurement Logistics of a Steel Group
Directory of Open Access Journals (Sweden)
Lianbo Deng
2014-01-01
Full Text Available This paper focuses on the optimization of an internal coordinated procurement logistics system in a steel group and the decision on the coordinated procurement strategy by minimizing the logistics costs. Considering the coordinated procurement strategy and the procurement logistics costs, the aim of the optimization model was to maximize the degree of quality satisfaction and to minimize the procurement logistics costs. The model was transformed into a single-objective model and solved using a simulated annealing algorithm. In the algorithm, the supplier of each subsidiary was selected according to the evaluation result for independent procurement. Finally, the effect of different parameters on the coordinated procurement strategy was analysed. The results showed that the coordinated strategy can clearly save procurement costs; that the strategy appears to be more cooperative when the quality requirement is not stricter; and that the coordinated costs have a strong effect on the coordinated procurement strategy.
Optimization Strategy of the APR+ BOP Technical Specifications
International Nuclear Information System (INIS)
Cho, Yoon Sang; Lee, Jae Gon; Han, Sung Heum
2016-01-01
The BOP is one of the key factors for successful project implementation of NPP. In constructing the APR1400 NPP, the BOP procurement has been one of the biggest concerns. Due to the design changes and increased capacity of equipment in NPP, lots of BOPs should be ‘first supplied equipment’ [hereinafter, ‘FSE’]. The manufacture-ability, and the performances of FSEs have not been fully proved and tested, manufacturers and suppliers are requested to submit Reports for Equipment Qualification Evaluation in accordance with 10 CFR 50.49, IEEE 323. They need at least 1-2 years’ tests for Environment Qualification (EQ) and Seismic Qualification (SQ). This study is focused how to prepare the BOP purchase specifications in order to control the FSEs, especially in safety class equipment. With the optimization plan for BOP packages of this study, the FSEs’ occurrence can be reasonably controlled as low as possible. For successful NPP project, the concerns in procuring BOPs shall be fully analyzed beforehand. Now Korea is preparing new era of APR+, with closing the time of APR1400. The technical specification of APR+ BOPs can be developed and prepared successfully and very effectively according to this optimization plan. This will be a great contribution not only in constructing APR+ in time, but also in exporting APR+ overseas, all over the world in the future
Optimization Strategy of the APR+ BOP Technical Specifications
Energy Technology Data Exchange (ETDEWEB)
Cho, Yoon Sang; Lee, Jae Gon; Han, Sung Heum [KHNP CRI, Daejeon (Korea, Republic of)
2016-10-15
The BOP is one of the key factors for successful project implementation of NPP. In constructing the APR1400 NPP, the BOP procurement has been one of the biggest concerns. Due to the design changes and increased capacity of equipment in NPP, lots of BOPs should be ‘first supplied equipment’ [hereinafter, ‘FSE’]. The manufacture-ability, and the performances of FSEs have not been fully proved and tested, manufacturers and suppliers are requested to submit Reports for Equipment Qualification Evaluation in accordance with 10 CFR 50.49, IEEE 323. They need at least 1-2 years’ tests for Environment Qualification (EQ) and Seismic Qualification (SQ). This study is focused how to prepare the BOP purchase specifications in order to control the FSEs, especially in safety class equipment. With the optimization plan for BOP packages of this study, the FSEs’ occurrence can be reasonably controlled as low as possible. For successful NPP project, the concerns in procuring BOPs shall be fully analyzed beforehand. Now Korea is preparing new era of APR+, with closing the time of APR1400. The technical specification of APR+ BOPs can be developed and prepared successfully and very effectively according to this optimization plan. This will be a great contribution not only in constructing APR+ in time, but also in exporting APR+ overseas, all over the world in the future.
Muratore-Ginanneschi, Paolo
2005-05-01
Investment strategies in multiplicative Markovian market models with transaction costs are defined using growth optimal criteria. The optimal strategy is shown to consist in holding the amount of capital invested in stocks within an interval around an ideal optimal investment. The size of the holding interval is determined by the intensity of the transaction costs and the time horizon. The inclusion of financial derivatives in the models is also considered. All the results presented in this contributions were previously derived in collaboration with E. Aurell.
Energy Technology Data Exchange (ETDEWEB)
Aha, Ulrich
2013-07-01
Maintenance strategies are aimed to keep a technical facility functioning in spite of damaging processes (wear, corrosion, fatigue) with simultaneous control of these processes. The project optimization of maintenance strategies in case of data uncertainties is aimed to optimize maintenance measures like preventive measures (lubrication etc.), inspections and replacements to keep the facility/plant operating including the minimization of financial costs. The report covers the following topics: modeling assumptions, model development and optimization procedure, results for a conventional power plant and an oxyfuel plant.
Ye, Quanliang; Li, Yi; Zhuo, La; Zhang, Wenlong; Xiong, Wei; Wang, Chao; Wang, Peifang
2018-02-01
This study provides an innovative application of virtual water trade in the traditional allocation of physical water resources in water scarce regions. A multi-objective optimization model was developed to optimize the allocation of physical water and virtual water resources to different water users in Beijing, China, considering the trade-offs between economic benefit and environmental impacts of water consumption. Surface water, groundwater, transferred water and reclaimed water constituted the physical resource of water supply side, while virtual water flow associated with the trade of five major crops (barley, corn, rice, soy and wheat) and three livestock products (beef, pork and poultry) in agricultural sector (calculated by the trade quantities of products and their virtual water contents). Urban (daily activities and public facilities), industry, environment and agriculture (products growing) were considered in water demand side. As for the traditional allocation of physical water resources, the results showed that agriculture and urban were the two predominant water users (accounting 54% and 28%, respectively), while groundwater and surface water satisfied around 70% water demands of different users (accounting 36% and 34%, respectively). When considered the virtual water trade of eight agricultural products in water allocation procedure, the proportion of agricultural consumption decreased to 45% in total water demand, while the groundwater consumption decreased to 24% in total water supply. Virtual water trade overturned the traditional components of water supplied from different sources for agricultural consumption, and became the largest water source in Beijing. Additionally, it was also found that environmental demand took a similar percentage of water consumption in each water source. Reclaimed water was the main water source for industrial and environmental users. The results suggest that physical water resources would mainly satisfy the consumption
Multi-step optimization strategy for fuel-optimal orbital transfer of low-thrust spacecraft
Rasotto, M.; Armellin, R.; Di Lizia, P.
2016-03-01
An effective method for the design of fuel-optimal transfers in two- and three-body dynamics is presented. The optimal control problem is formulated using calculus of variation and primer vector theory. This leads to a multi-point boundary value problem (MPBVP), characterized by complex inner constraints and a discontinuous thrust profile. The first issue is addressed by embedding the MPBVP in a parametric optimization problem, thus allowing a simplification of the set of transversality constraints. The second problem is solved by representing the discontinuous control function by a smooth function depending on a continuation parameter. The resulting trajectory optimization method can deal with different intermediate conditions, and no a priori knowledge of the control structure is required. Test cases in both the two- and three-body dynamics show the capability of the method in solving complex trajectory design problems.
Directory of Open Access Journals (Sweden)
Qijia Yao
2017-07-01
Full Text Available The optimal control of multibody spacecraft during the stretching process of solar arrays is investigated, and a hybrid optimization strategy based on Gauss pseudospectral method (GPM and direct shooting method (DSM is presented. First, the elastic deformation of flexible solar arrays was described approximately by the assumed mode method, and a dynamic model was established by the second Lagrangian equation. Then, the nonholonomic motion planning problem is transformed into a nonlinear programming problem by using GPM. By giving fewer LG points, initial values of the state variables and control variables were obtained. A serial optimization framework was adopted to obtain the approximate optimal solution from a feasible solution. Finally, the control variables were discretized at LG points, and the precise optimal control inputs were obtained by DSM. The optimal trajectory of the system can be obtained through numerical integration. Through numerical simulation, the stretching process of solar arrays is stable with no detours, and the control inputs match the various constraints of actual conditions. The results indicate that the method is effective with good robustness. Keywords: Motion planning, Multibody spacecraft, Optimal control, Gauss pseudospectral method, Direct shooting method
Dispositional optimism and coping strategies in patients with a kidney transplant.
Costa-Requena, Gemma; Cantarell-Aixendri, M Carmen; Parramon-Puig, Gemma; Serón-Micas, Daniel
2014-01-01
Dispositional optimism is a personal resource that determines the coping style and adaptive response to chronic diseases. The aim of this study was to assess the correlations between dispositional optimism and coping strategies in patients with recent kidney transplantation and evaluate the differences in the use of coping strategies in accordance with the level of dispositional optimism. Patients who were hospitalised in the nephrology department were selected consecutively after kidney transplantation was performed. The evaluation instruments were the Life Orientation Test-Revised, and the Coping Strategies Inventory. The data were analysed with central tendency measures, correlation analyses and means were compared using Student’s t-test. 66 patients with a kidney transplant participated in the study. The coping styles that characterised patients with a recent kidney transplantation were Social withdrawal and Problem avoidance. Correlations between dispositional optimism and coping strategies were significant in a positive direction in Problem-solving (p<.05) and Cognitive restructuring (p<.01), and inversely with Self-criticism (p<.05). Differences in dispositional optimism created significant differences in the Self-Criticism dimension (t=2.58; p<.01). Dispositional optimism scores provide differences in coping responses after kidney transplantation. Moreover, coping strategies may influence the patient’s perception of emotional wellbeing after kidney transplantation.
Tank waste remediation system optimized processing strategy with an altered treatment scheme
International Nuclear Information System (INIS)
Slaathaug, E.J.
1996-03-01
This report provides an alternative strategy evolved from the current Hanford Site Tank Waste Remediation System (TWRS) programmatic baseline for accomplishing the treatment and disposal of the Hanford Site tank wastes. This optimized processing strategy with an altered treatment scheme performs the major elements of the TWRS Program, but modifies the deployment of selected treatment technologies to reduce the program cost. The present program for development of waste retrieval, pretreatment, and vitrification technologies continues, but the optimized processing strategy reuses a single facility to accomplish the separations/low-activity waste (LAW) vitrification and the high-level waste (HLW) vitrification processes sequentially, thereby eliminating the need for a separate HLW vitrification facility
Optimization of remediation strategies using vadose zone monitoring systems
Dahan, Ofer
2016-04-01
In-situ bio-remediation of the vadose zone depends mainly on the ability to change the subsurface hydrological, physical and chemical conditions in order to enable development of specific, indigenous, pollutants degrading bacteria. As such the remediation efficiency is much dependent on the ability to implement optimal hydraulic and chemical conditions in deep sections of the vadose zone. These conditions are usually determined in laboratory experiments where parameters such as the chemical composition of the soil water solution, redox potential and water content of the sediment are fully controlled. Usually, implementation of desired optimal degradation conditions in deep vadose zone at full scale field setups is achieved through infiltration of water enriched with chemical additives on the land surface. It is assumed that deep percolation into the vadose zone would create chemical conditions that promote biodegradation of specific compounds. However, application of water with specific chemical conditions near land surface dose not necessarily results in promoting of desired chemical and hydraulic conditions in deep sections of the vadose zone. A vadose-zone monitoring system (VMS) that was recently developed allows continuous monitoring of the hydrological and chemical properties of deep sections of the unsaturated zone. The VMS includes flexible time-domain reflectometry (FTDR) probes which allow continuous monitoring of the temporal variation of the vadose zone water content, and vadose-zone sampling ports (VSPs) which are designed to allow frequent sampling of the sediment pore-water and gas at multiple depths. Implementation of the vadose zone monitoring system in sites that undergoes active remediation provides real time information on the actual chemical and hydrological conditions in the vadose zone as the remediation process progresses. Up-to-date the system has been successfully implemented in several studies on water flow and contaminant transport in
Optimizing noise control strategy in a forging workshop.
Razavi, Hamideh; Ramazanifar, Ehsan; Bagherzadeh, Jalal
2014-01-01
In this paper, a computer program based on a genetic algorithm is developed to find an economic solution for noise control in a forging workshop. Initially, input data, including characteristics of sound sources, human exposure, abatement techniques, and production plans are inserted into the model. Using sound pressure levels at working locations, the operators who are at higher risk are identified and picked out for the next step. The program is devised in MATLAB such that the parameters can be easily defined and changed for comparison. The final results are structured into 4 sections that specify an appropriate abatement method for each operator and machine, minimum allowance time for high-risk operators, required damping material for enclosures, and minimum total cost of these treatments. The validity of input data in addition to proper settings in the optimization model ensures the final solution is practical and economically reasonable.
Global optimization numerical strategies for rate-independent processes
Czech Academy of Sciences Publication Activity Database
Benešová, Barbora
2011-01-01
Roč. 50, č. 2 (2011), s. 197-220 ISSN 0925-5001 R&D Projects: GA ČR GAP201/10/0357 Grant - others:GA MŠk(CZ) LC06052 Program:LC Institutional research plan: CEZ:AV0Z20760514 Keywords : rate-independent processes * numerical global optimization * energy estimates based algorithm Subject RIV: BA - General Mathematics Impact factor: 1.196, year: 2011 http://math.hnue.edu.vn/portal/rss.viewpage.php?id=0000037780&ap=L3BvcnRhbC9ncmFiYmVyLnBocD9jYXRpZD0xMDEyJnBhZ2U9Mg==
Optimization of wind farm power production using innovative control strategies
DEFF Research Database (Denmark)
Duc, Thomas
Wind energy has experienced a very significant growth and cost reduction over the past decade, and is now able to compete with conventional power generation sources. New concepts are currently investigated to decrease costs of production of electricity even further. Wind farm coordinated control...... deficit caused by the wake downstream, or yawing the turbine to deflect the wake away from the downwind turbine. Simulation results found in the literature indicate that an increase in overall power production can be obtained. However they underline the high sensitivity of these gains to incoming wind...... aligned wind turbines. The experimental results show that the scenarios implemented during the first measurement campaign did not achieve an increase in overall power production, which confirms the difficulty to realize wind farm power optimization in real operating conditions. In the curtailment field...
Optimal dispatch strategy for the agile virtual power plant
DEFF Research Database (Denmark)
Petersen, Mette Højgaard; Bendtsen, Jan Dimon; Stoustrup, Jakob
2012-01-01
The introduction of large ratios of renewable energy into the existing power system is complicated by the inherent variability of production technologies, which harvest energy from wind, sun and waves. Fluctuations of renewable power production can be predicted to some extent, but the assumption...... of perfect prediction is unrealistic. This paper therefore introduces the Agile Virtual Power Plant. The Agile Virtual Power Plant assumes that the base load production planning based on best available knowledge is already given, so imbalances cannot be predicted. Consequently the Agile Virtual Power Plant...... attempts to preserve maneuverability (stay agile) rather than optimize performance according to predictions. In this paper the imbalance compensation problem for an Agile Virtual Power Plant is formulated. It is proved formally, that when local units are power and energy constrained integrators a dispatch...
Experimental transport phenomena and optimization strategies for thermoelectrics
Energy Technology Data Exchange (ETDEWEB)
Ehrlich, A C; Gillespie, D J
1997-07-01
When a new and promising thermoelectric material is discovered, an effort is undertaken to improve its figure of merit. If the effort is to be more efficient than one of trial and error with perhaps some rule of thumb guidance then it is important to be able to make the connection between experimental data and the underlying material characteristics, electronic and phononic, that influence the figure of merit. Transport and fermiology experimental data can be used to evaluate these material characteristics and thus establish trends as a function of some controllable parameter, such as composition. In this paper some of the generic-materials characteristics, generally believed to be required for a high figure of merit, will be discussed in terms of the experimental approach to their evaluation and optimization. Transport and fermiology experiments will be emphasized and both will be outlined in what they can reveal and what can be obscured by the simplifying assumptions generally used in their interpretation.
Optimal Sizing and Control Strategy Design for Heavy Hybrid Electric Truck
Directory of Open Access Journals (Sweden)
Yuan Zou
2012-01-01
Full Text Available Due to the complexity of the hybrid powertrain, the control is highly involved to improve the collaborations of the different components. For the specific powertrain, the components' sizing just gives the possibility to propel the vehicle and the control will realize the function of the propulsion. Definitely the components' sizing also gives the constraints to the control design, which cause a close coupling between the sizing and control strategy design. This paper presents a parametric study focused on sizing of the powertrain components and optimization of the power split between the engine and electric motor for minimizing the fuel consumption. A framework is put forward to accomplish the optimal sizing and control design for a heavy parallel pre-AMT hybrid truck under the natural driving schedule. The iterative plant-controller combined optimization methodology is adopted to optimize the key parameters of the plant and control strategy simultaneously. A scalable powertrain model based on a bilevel optimization framework is built. Dynamic programming is applied to find the optimal control in the inner loop with a prescribed cycle. The parameters are optimized in the outer loop. The results are analysed and the optimal sizing and control strategy are achieved simultaneously.
Footprints of Optimal Protein Assembly Strategies in the Operonic Structure of Prokaryotes
Directory of Open Access Journals (Sweden)
Jan Ewald
2015-04-01
Full Text Available In this work, we investigate optimality principles behind synthesis strategies for protein complexes using a dynamic optimization approach. We show that the cellular capacity of protein synthesis has a strong influence on optimal synthesis strategies reaching from a simultaneous to a sequential synthesis of the subunits of a protein complex. Sequential synthesis is preferred if protein synthesis is strongly limited, whereas a simultaneous synthesis is optimal in situations with a high protein synthesis capacity. We confirm the predictions of our optimization approach through the analysis of the operonic organization of protein complexes in several hundred prokaryotes. Thereby, we are able to show that cellular protein synthesis capacity is a driving force in the dissolution of operons comprising the subunits of a protein complex. Thus, we also provide a tested hypothesis explaining why the subunits of many prokaryotic protein complexes are distributed across several operons despite the presumably less precise co-regulation.
Optimizing Lidar Scanning Strategies for Wind Energy Measurements (Invited)
Newman, J. F.; Bonin, T. A.; Klein, P.; Wharton, S.; Chilson, P. B.
2013-12-01
Environmental concerns and rising fossil fuel prices have prompted rapid development in the renewable energy sector. Wind energy, in particular, has become increasingly popular in the United States. However, the intermittency of available wind energy makes it difficult to integrate wind energy into the power grid. Thus, the expansion and successful implementation of wind energy requires accurate wind resource assessments and wind power forecasts. The actual power produced by a turbine is affected by the wind speeds and turbulence levels experienced across the turbine rotor disk. Because of the range of measurement heights required for wind power estimation, remote sensing devices (e.g., lidar) are ideally suited for these purposes. However, the volume averaging inherent in remote sensing technology produces turbulence estimates that are different from those estimated by a sonic anemometer mounted on a standard meteorological tower. In addition, most lidars intended for wind energy purposes utilize a standard Doppler beam-swinging or Velocity-Azimuth Display technique to estimate the three-dimensional wind vector. These scanning strategies are ideal for measuring mean wind speeds but are likely inadequate for measuring turbulence. In order to examine the impact of different lidar scanning strategies on turbulence measurements, a WindCube lidar, a scanning Halo lidar, and a scanning Galion lidar were deployed at the Southern Great Plains Atmospheric Radiation Measurement (ARM) site in Summer 2013. Existing instrumentation at the ARM site, including a 60-m meteorological tower and an additional scanning Halo lidar, were used in conjunction with the deployed lidars to evaluate several user-defined scanning strategies. For part of the experiment, all three scanning lidars were pointed at approximately the same point in space and a tri-Doppler analysis was completed to calculate the three-dimensional wind vector every 1 second. In another part of the experiment, one of
Optimal combined purchasing strategies for a risk-averse manufacturer under price uncertainty
Directory of Open Access Journals (Sweden)
Qiao Wu
2015-09-01
Full Text Available Purpose: The purpose of our paper is to analyze optimal purchasing strategies when a manufacturer can buy raw materials from a long-term contract supplier and a spot market under spot price uncertainty. Design/methodology/approach: This procurement model can be solved by using dynamic programming. First, we maximize the DM’s utility of the second period, obtaining the optimal contract quantity and spot quantity for the second period. Then, maximize the DM’s utility of both periods, obtaining the optimal purchasing strategy for the first period. We use a numerical method to compare the performance level of a pure spot sourcing strategy with that of a mixed strategy. Findings: Our results show that optimal purchasing strategies vary with the trend of contract prices. If the contract price falls, the total quantity purchased in period 1 will decrease in the degree of risk aversion. If the contract price increases, the total quantity purchased in period 1 will increase in the degree of risk aversion. The relationship between the optimal contract quantity and the degree of risk aversion depends on whether the expected spot price or the contract price is larger in period 2. Finally, we compare the performance levels between a combined strategy and a spot sourcing strategy. It shows that a combined strategy is optimal for a risk-averse buyer. Originality/value: It’s challenging to deal with a two-period procurement problem with risk consideration. We have obtained results of a two-period procurement problem with two sourcing options, namely contract procurement and spot purchases. Our model incorporates the buyer’s risk aversion factor and the change of contract prices, which are not addressed in early studies.
Approximate representation of optimal strategies from influence diagrams
DEFF Research Database (Denmark)
Jensen, Finn V.
2008-01-01
, and where the policy functions for the decisions have so large do- mains that they cannot be represented directly in a strategy tree. The approach is to have separate ID representations for each decision variable. In each representation the actual information is fully exploited, however the representation...... of policies for future decisions are approximations. We call the approximation information abstraction. It consists in introducing a dummy structure connecting the past with the decision. We study how to specify, implement and learn information abstraction.......There are three phases in the life of a decision problem, specification, solution, and rep- resentation of solution. The specification and solution phases are off-line, while the rep- resention of solution often shall serve an on-line situation with rather tough constraints on time and space. One...
Ling, Qing-Hua; Song, Yu-Qing; Han, Fei; Yang, Dan; Huang, De-Shuang
2016-01-01
For ensemble learning, how to select and combine the candidate classifiers are two key issues which influence the performance of the ensemble system dramatically. Random vector functional link networks (RVFL) without direct input-to-output links is one of suitable base-classifiers for ensemble systems because of its fast learning speed, simple structure and good generalization performance. In this paper, to obtain a more compact ensemble system with improved convergence performance, an improved ensemble of RVFL based on attractive and repulsive particle swarm optimization (ARPSO) with double optimization strategy is proposed. In the proposed method, ARPSO is applied to select and combine the candidate RVFL. As for using ARPSO to select the optimal base RVFL, ARPSO considers both the convergence accuracy on the validation data and the diversity of the candidate ensemble system to build the RVFL ensembles. In the process of combining RVFL, the ensemble weights corresponding to the base RVFL are initialized by the minimum norm least-square method and then further optimized by ARPSO. Finally, a few redundant RVFL is pruned, and thus the more compact ensemble of RVFL is obtained. Moreover, in this paper, theoretical analysis and justification on how to prune the base classifiers on classification problem is presented, and a simple and practically feasible strategy for pruning redundant base classifiers on both classification and regression problems is proposed. Since the double optimization is performed on the basis of the single optimization, the ensemble of RVFL built by the proposed method outperforms that built by some single optimization methods. Experiment results on function approximation and classification problems verify that the proposed method could improve its convergence accuracy as well as reduce the complexity of the ensemble system.
Combining two strategies to optimize biometric decisions against spoofing attacks
Li, Weifeng; Poh, Norman; Zhou, Yicong
2014-09-01
Spoof attack by replicating biometric traits represents a real threat to an automatic biometric verification/ authentication system. This is because the system, originally designed to distinguish between genuine users from impostors, simply cannot distinguish between a replicated biometric sample (replica) from a live sample. An effective solution is to obtain some measures that can indicate whether or not a biometric trait has been tempered with, e.g., liveness detection measures. These measures are referred to as evidence of spoofing or anti-spoofing measures. In order to make the final accept/rejection decision, a straightforward solution to define two thresholds: one for the anti-spoofing measure, and another for the verification score. We compared two variants of a method that relies on applying two thresholds - one to the verification (matching) score and another to the anti-spoofing measure. Our experiments carried out using a signature database as well as by simulation show that both the brute-force and its probabilistic variant turn out to be optimal under different operating conditions.
Energy Optimization Using a Case-Based Reasoning Strategy.
González-Briones, Alfonso; Prieto, Javier; De La Prieta, Fernando; Herrera-Viedma, Enrique; Corchado, Juan M
2018-03-15
At present, the domotization of homes and public buildings is becoming increasingly popular. Domotization is most commonly applied to the field of energy management, since it gives the possibility of managing the consumption of the devices connected to the electric network, the way in which the users interact with these devices, as well as other external factors that influence consumption. In buildings, Heating, Ventilation and Air Conditioning (HVAC) systems have the highest consumption rates. The systems proposed so far have not succeeded in optimizing the energy consumption associated with a HVAC system because they do not monitor all the variables involved in electricity consumption. For this reason, this article presents an agent approach that benefits from the advantages provided by a Multi-Agent architecture (MAS) deployed in a Cloud environment with a wireless sensor network (WSN) in order to achieve energy savings. The agents of the MAS learn social behavior thanks to the collection of data and the use of an artificial neural network (ANN). The proposed system has been assessed in an office building achieving an average energy savings of 41% in the experimental group offices.
An optimal strategy for functional mapping of dynamic trait loci.
Jin, Tianbo; Li, Jiahan; Guo, Ying; Zhou, Xiaojing; Yang, Runqing; Wu, Rongling
2010-02-01
As an emerging powerful approach for mapping quantitative trait loci (QTLs) responsible for dynamic traits, functional mapping models the time-dependent mean vector with biologically meaningful equations and are likely to generate biologically relevant and interpretable results. Given the autocorrelation nature of a dynamic trait, functional mapping needs the implementation of the models for the structure of the covariance matrix. In this article, we have provided a comprehensive set of approaches for modelling the covariance structure and incorporated each of these approaches into the framework of functional mapping. The Bayesian information criterion (BIC) values are used as a model selection criterion to choose the optimal combination of the submodels for the mean vector and covariance structure. In an example for leaf age growth from a rice molecular genetic project, the best submodel combination was found between the Gaussian model for the correlation structure, power equation of order 1 for the variance and the power curve for the mean vector. Under this combination, several significant QTLs for leaf age growth trajectories were detected on different chromosomes. Our model can be well used to study the genetic architecture of dynamic traits of agricultural values.
Advanced Variance Reduction Strategies for Optimizing Mesh Tallies in MAVRIC
International Nuclear Information System (INIS)
Peplow, Douglas E.; Blakeman, Edward D; Wagner, John C
2007-01-01
More often than in the past, Monte Carlo methods are being used to compute fluxes or doses over large areas using mesh tallies (a set of region tallies defined on a mesh that overlays the geometry). For problems that demand that the uncertainty in each mesh cell be less than some set maximum, computation time is controlled by the cell with the largest uncertainty. This issue becomes quite troublesome in deep-penetration problems, and advanced variance reduction techniques are required to obtain reasonable uncertainties over large areas. The CADIS (Consistent Adjoint Driven Importance Sampling) methodology has been shown to very efficiently optimize the calculation of a response (flux or dose) for a single point or a small region using weight windows and a biased source based on the adjoint of that response. This has been incorporated into codes such as ADVANTG (based on MCNP) and the new sequence MAVRIC, which will be available in the next release of SCALE. In an effort to compute lower uncertainties everywhere in the problem, Larsen's group has also developed several methods to help distribute particles more evenly, based on forward estimates of flux. This paper focuses on the use of a forward estimate to weight the placement of the source in the adjoint calculation used by CADIS, which we refer to as a forward-weighted CADIS (FW-CADIS)
Optimal investment strategies in decentralized renewable power generation under uncertainty
International Nuclear Information System (INIS)
Fleten, S.-E.; Maribu, K.M.; Wangensteen, I.
2007-01-01
This paper presents a method for evaluating investments in decentralized renewable power generation under price un certainty. The analysis is applicable for a client with an electricity load and a renewable resource that can be utilized for power generation. The investor has a deferrable opportunity to invest in one local power generating unit, with the objective to maximize the profits from the opportunity. Renewable electricity generation can serve local load when generation and load coincide in time, and surplus power can be exported to the grid. The problem is to find the price intervals and the capacity of the generator at which to invest. Results from a case with wind power generation for an office building suggests it is optimal to wait for higher prices than the net present value break-even price under price uncertainty, and that capacity choice can depend on the current market price and the price volatility. With low price volatility there can be more than one investment price interval for different units with intermediate waiting regions between them. High price volatility increases the value of the investment opportunity, and therefore makes it more attractive to postpone investment until larger units are profitable. (author)
Energy Optimization Using a Case-Based Reasoning Strategy
Directory of Open Access Journals (Sweden)
Alfonso González-Briones
2018-03-01
Full Text Available At present, the domotization of homes and public buildings is becoming increasingly popular. Domotization is most commonly applied to the field of energy management, since it gives the possibility of managing the consumption of the devices connected to the electric network, the way in which the users interact with these devices, as well as other external factors that influence consumption. In buildings, Heating, Ventilation and Air Conditioning (HVAC systems have the highest consumption rates. The systems proposed so far have not succeeded in optimizing the energy consumption associated with a HVAC system because they do not monitor all the variables involved in electricity consumption. For this reason, this article presents an agent approach that benefits from the advantages provided by a Multi-Agent architecture (MAS deployed in a Cloud environment with a wireless sensor network (WSN in order to achieve energy savings. The agents of the MAS learn social behavior thanks to the collection of data and the use of an artificial neural network (ANN. The proposed system has been assessed in an office building achieving an average energy savings of 41% in the experimental group offices.
Energy Optimization Using a Case-Based Reasoning Strategy
Herrera-Viedma, Enrique
2018-01-01
At present, the domotization of homes and public buildings is becoming increasingly popular. Domotization is most commonly applied to the field of energy management, since it gives the possibility of managing the consumption of the devices connected to the electric network, the way in which the users interact with these devices, as well as other external factors that influence consumption. In buildings, Heating, Ventilation and Air Conditioning (HVAC) systems have the highest consumption rates. The systems proposed so far have not succeeded in optimizing the energy consumption associated with a HVAC system because they do not monitor all the variables involved in electricity consumption. For this reason, this article presents an agent approach that benefits from the advantages provided by a Multi-Agent architecture (MAS) deployed in a Cloud environment with a wireless sensor network (WSN) in order to achieve energy savings. The agents of the MAS learn social behavior thanks to the collection of data and the use of an artificial neural network (ANN). The proposed system has been assessed in an office building achieving an average energy savings of 41% in the experimental group offices. PMID:29543729
A Parameter Communication Optimization Strategy for Distributed Machine Learning in Sensors.
Zhang, Jilin; Tu, Hangdi; Ren, Yongjian; Wan, Jian; Zhou, Li; Li, Mingwei; Wang, Jue; Yu, Lifeng; Zhao, Chang; Zhang, Lei
2017-09-21
In order to utilize the distributed characteristic of sensors, distributed machine learning has become the mainstream approach, but the different computing capability of sensors and network delays greatly influence the accuracy and the convergence rate of the machine learning model. Our paper describes a reasonable parameter communication optimization strategy to balance the training overhead and the communication overhead. We extend the fault tolerance of iterative-convergent machine learning algorithms and propose the Dynamic Finite Fault Tolerance (DFFT). Based on the DFFT, we implement a parameter communication optimization strategy for distributed machine learning, named Dynamic Synchronous Parallel Strategy (DSP), which uses the performance monitoring model to dynamically adjust the parameter synchronization strategy between worker nodes and the Parameter Server (PS). This strategy makes full use of the computing power of each sensor, ensures the accuracy of the machine learning model, and avoids the situation that the model training is disturbed by any tasks unrelated to the sensors.
Optimal bidding strategies for competitive generators and large consumers
International Nuclear Information System (INIS)
Fushuan Wen; David, A.K.
2001-01-01
There exists the potential for gaming such as strategic bidding by participants (power suppliers and large consumers) in a deregulated power market, which is more an oligopoly than a laissez-faire market. Each participant can increase his or her own profit through strategic bidding but this has a negative effect on maximising social welfare. A method to build bidding strategies for both power suppliers and large consumers in a poolco-type electricity market is presented in this paper. It is assumed that each supplier/large consumer bids a linear supply/demand function, and the system is dispatched to maximise social welfare. Each supplier/large consumer chooses the coefficients in the linear supply/demand function to maximise benefits, subject to expectations about how rival participants will bid. The problem is formulated as a stochastic optimisation problem, and solved by a Monte Carlo approach. A numerical example with six suppliers and two large consumers serves to illustrate the essential features of the method. (author)
Communication strategies to optimize commitments and investments in iron programming.
Griffiths, Marcia
2002-04-01
There is consensus that a communications component is crucial to the success of iron supplementation and fortification programs. However, in many instances, we have not applied what we know about successful advocacy and program communications to iron programs. Communication must play a larger and more central role in iron programs to overcome several common shortcomings and allow the use of new commitments and investments in iron programming to optimum advantage. One shortcoming is that iron program communication has been driven primarily by the supply side of the supply-demand continuum. That is, technical information has been given without thought for what people want to know or do. To overcome this, the communication component, which should be responsive to the consumer perspective, must be considered at program inception, not enlisted late in the program cycle as a remedy when interventions fail to reach their targets. Another shortcoming is the lack of program focus on behavior. Because the "technology" of iron, a supplement, or fortified or specific local food must be combined with appropriate consumer behavior, it is not enough to promote the technology. The appropriate use of technology must be ensured, and this requires precise and strategically crafted communications. A small number of projects from countries as diverse as Indonesia, Egypt, Nicaragua and Peru offer examples of successful communications efforts and strategies for adaptation by other countries.
Wang, Bo; Tian, Kuo; Zhao, Haixin; Hao, Peng; Zhu, Tianyu; Zhang, Ke; Ma, Yunlong
2017-06-01
In order to improve the post-buckling optimization efficiency of hierarchical stiffened shells, a multilevel optimization framework accelerated by adaptive equivalent strategy is presented in this paper. Firstly, the Numerical-based Smeared Stiffener Method (NSSM) for hierarchical stiffened shells is derived by means of the numerical implementation of asymptotic homogenization (NIAH) method. Based on the NSSM, a reasonable adaptive equivalent strategy for hierarchical stiffened shells is developed from the concept of hierarchy reduction. Its core idea is to self-adaptively decide which hierarchy of the structure should be equivalent according to the critical buckling mode rapidly predicted by NSSM. Compared with the detailed model, the high prediction accuracy and efficiency of the proposed model is highlighted. On the basis of this adaptive equivalent model, a multilevel optimization framework is then established by decomposing the complex entire optimization process into major-stiffener-level and minor-stiffener-level sub-optimizations, during which Fixed Point Iteration (FPI) is employed to accelerate convergence. Finally, the illustrative examples of the multilevel framework is carried out to demonstrate its efficiency and effectiveness to search for the global optimum result by contrast with the single-level optimization method. Remarkably, the high efficiency and flexibility of the adaptive equivalent strategy is indicated by compared with the single equivalent strategy.
A Particle Swarm Optimization Variant with an Inner Variable Learning Strategy
Directory of Open Access Journals (Sweden)
Guohua Wu
2014-01-01
Full Text Available Although Particle Swarm Optimization (PSO has demonstrated competitive performance in solving global optimization problems, it exhibits some limitations when dealing with optimization problems with high dimensionality and complex landscape. In this paper, we integrate some problem-oriented knowledge into the design of a certain PSO variant. The resulting novel PSO algorithm with an inner variable learning strategy (PSO-IVL is particularly efficient for optimizing functions with symmetric variables. Symmetric variables of the optimized function have to satisfy a certain quantitative relation. Based on this knowledge, the inner variable learning (IVL strategy helps the particle to inspect the relation among its inner variables, determine the exemplar variable for all other variables, and then make each variable learn from the exemplar variable in terms of their quantitative relations. In addition, we design a new trap detection and jumping out strategy to help particles escape from local optima. The trap detection operation is employed at the level of individual particles whereas the trap jumping out strategy is adaptive in its nature. Experimental simulations completed for some representative optimization functions demonstrate the excellent performance of PSO-IVL. The effectiveness of the PSO-IVL stresses a usefulness of augmenting evolutionary algorithms by problem-oriented domain knowledge.
Pinto Mariano, Adriano; Bastos Borba Costa, Caliane; de Franceschi de Angelis, Dejanira; Maugeri Filho, Francisco; Pires Atala, Daniel Ibraim; Wolf Maciel, Maria Regina; Maciel Filho, Rubens
2009-11-01
In this work, the mathematical optimization of a continuous flash fermentation process for the production of biobutanol was studied. The process consists of three interconnected units, as follows: fermentor, cell-retention system (tangential microfiltration), and vacuum flash vessel (responsible for the continuous recovery of butanol from the broth). The objective of the optimization was to maximize butanol productivity for a desired substrate conversion. Two strategies were compared for the optimization of the process. In one of them, the process was represented by a deterministic model with kinetic parameters determined experimentally and, in the other, by a statistical model obtained using the factorial design technique combined with simulation. For both strategies, the problem was written as a nonlinear programming problem and was solved with the sequential quadratic programming technique. The results showed that despite the very similar solutions obtained with both strategies, the problems found with the strategy using the deterministic model, such as lack of convergence and high computational time, make the use of the optimization strategy with the statistical model, which showed to be robust and fast, more suitable for the flash fermentation process, being recommended for real-time applications coupling optimization and control.
Strategies to Optimize Adult Stem Cell Therapy for Tissue Regeneration
Directory of Open Access Journals (Sweden)
Shan Liu
2016-06-01
Full Text Available Stem cell therapy aims to replace damaged or aged cells with healthy functioning cells in congenital defects, tissue injuries, autoimmune disorders, and neurogenic degenerative diseases. Among various types of stem cells, adult stem cells (i.e., tissue-specific stem cells commit to becoming the functional cells from their tissue of origin. These cells are the most commonly used in cell-based therapy since they do not confer risk of teratomas, do not require fetal stem cell maneuvers and thus are free of ethical concerns, and they confer low immunogenicity (even if allogenous. The goal of this review is to summarize the current state of the art and advances in using stem cell therapy for tissue repair in solid organs. Here we address key factors in cell preparation, such as the source of adult stem cells, optimal cell types for implantation (universal mesenchymal stem cells vs. tissue-specific stem cells, or induced vs. non-induced stem cells, early or late passages of stem cells, stem cells with endogenous or exogenous growth factors, preconditioning of stem cells (hypoxia, growth factors, or conditioned medium, using various controlled release systems to deliver growth factors with hydrogels or microspheres to provide apposite interactions of stem cells and their niche. We also review several approaches of cell delivery that affect the outcomes of cell therapy, including the appropriate routes of cell administration (systemic, intravenous, or intraperitoneal vs. local administration, timing for cell therapy (immediate vs. a few days after injury, single injection of a large number of cells vs. multiple smaller injections, a single site for injection vs. multiple sites and use of rodents vs. larger animal models. Future directions of stem cell-based therapies are also discussed to guide potential clinical applications.
Adams, Vanessa M; Pressey, Robert L; Álvarez-Romero, Jorge G
2016-01-01
Development of land resources can contribute to increased economic productivity but can also negatively affect the extent and condition of native vegetation, jeopardize the persistence of native species, reduce water quality, and erode ecosystem services. Spatial planning must therefore balance outcomes for conservation, development, and social goals. One approach to evaluating these trade-offs is scenario planning. In this paper we demonstrate methods for incorporating stakeholder preferences into scenario planning through both defining scenario objectives and evaluating the scenarios that emerge. In this way, we aim to develop spatial plans capable of informing actual land-use decisions. We used a novel approach to scenario planning that couples optimal land-use design and social evaluation of environmental outcomes. Four land-use scenarios combined differences in total clearing levels (10% and 20%) in our study region, the Daly Catchment Australia, with the presence or absence of spatial precincts to concentrate irrigated agriculture. We used the systematic conservation planning tool Marxan with Zones to optimally plan for multiple land-uses that met objectives for both conservation and development. We assessed the performance of the scenarios in terms of the number of objectives met and the degree to which existing land-use policies were compromised (e.g., whether clearing limits in existing guidelines were exceeded or not). We also assessed the land-use scenarios using expected stakeholder satisfaction with changes in the catchment to explore how the scenarios performed against social preferences. There were a small fraction of conservation objectives with high conservation targets (100%) that could not be met due to current land uses; all other conservation and development objectives were met in all scenarios. Most scenarios adhered to the existing clearing guidelines with only marginal exceedances of limits, indicating that the scenario objectives were
Directory of Open Access Journals (Sweden)
Vanessa M Adams
Full Text Available Development of land resources can contribute to increased economic productivity but can also negatively affect the extent and condition of native vegetation, jeopardize the persistence of native species, reduce water quality, and erode ecosystem services. Spatial planning must therefore balance outcomes for conservation, development, and social goals. One approach to evaluating these trade-offs is scenario planning. In this paper we demonstrate methods for incorporating stakeholder preferences into scenario planning through both defining scenario objectives and evaluating the scenarios that emerge. In this way, we aim to develop spatial plans capable of informing actual land-use decisions. We used a novel approach to scenario planning that couples optimal land-use design and social evaluation of environmental outcomes. Four land-use scenarios combined differences in total clearing levels (10% and 20% in our study region, the Daly Catchment Australia, with the presence or absence of spatial precincts to concentrate irrigated agriculture. We used the systematic conservation planning tool Marxan with Zones to optimally plan for multiple land-uses that met objectives for both conservation and development. We assessed the performance of the scenarios in terms of the number of objectives met and the degree to which existing land-use policies were compromised (e.g., whether clearing limits in existing guidelines were exceeded or not. We also assessed the land-use scenarios using expected stakeholder satisfaction with changes in the catchment to explore how the scenarios performed against social preferences. There were a small fraction of conservation objectives with high conservation targets (100% that could not be met due to current land uses; all other conservation and development objectives were met in all scenarios. Most scenarios adhered to the existing clearing guidelines with only marginal exceedances of limits, indicating that the scenario
Directory of Open Access Journals (Sweden)
Chengfen Zhang
2015-01-01
Full Text Available Dry-type air-core reactor is now widely applied in electrical power distribution systems, for which the optimization design is a crucial issue. In the optimization design problem of dry-type air-core reactor, the objectives of minimizing the production cost and minimizing the operation cost are both important. In this paper, a multiobjective optimal model is established considering simultaneously the two objectives of minimizing the production cost and minimizing the operation cost. To solve the multi-objective optimization problem, a memetic evolutionary algorithm is proposed, which combines elitist nondominated sorting genetic algorithm version II (NSGA-II with a local search strategy based on the covariance matrix adaptation evolution strategy (CMA-ES. NSGA-II can provide decision maker with flexible choices among the different trade-off solutions, while the local-search strategy, which is applied to nondominated individuals randomly selected from the current population in a given generation and quantity, can accelerate the convergence speed. Furthermore, another modification is that an external archive is set in the proposed algorithm for increasing the evolutionary efficiency. The proposed algorithm is tested on a dry-type air-core reactor made of rectangular cross-section litz-wire. Simulation results show that the proposed algorithm has high efficiency and it converges to a better Pareto front.
Development of a codon optimization strategy using the efor RED reporter gene as a test case
Yip, Chee-Hoo; Yarkoni, Orr; Ajioka, James; Wan, Kiew-Lian; Nathan, Sheila
2018-04-01
Synthetic biology is a platform that enables high-level synthesis of useful products such as pharmaceutically related drugs, bioplastics and green fuels from synthetic DNA constructs. Large-scale expression of these products can be achieved in an industrial compliant host such as Escherichia coli. To maximise the production of recombinant proteins in a heterologous host, the genes of interest are usually codon optimized based on the codon usage of the host. However, the bioinformatics freeware available for standard codon optimization might not be ideal in determining the best sequence for the synthesis of synthetic DNA. Synthesis of incorrect sequences can prove to be a costly error and to avoid this, a codon optimization strategy was developed based on the E. coli codon usage using the efor RED reporter gene as a test case. This strategy replaces codons encoding for serine, leucine, proline and threonine with the most frequently used codons in E. coli. Furthermore, codons encoding for valine and glycine are substituted with the second highly used codons in E. coli. Both the optimized and original efor RED genes were ligated to the pJS209 plasmid backbone using Gibson Assembly and the recombinant DNAs were transformed into E. coli E. cloni 10G strain. The fluorescence intensity per cell density of the optimized sequence was improved by 20% compared to the original sequence. Hence, the developed codon optimization strategy is proposed when designing an optimal sequence for heterologous protein production in E. coli.
A Single-Degree-of-Freedom Energy Optimization Strategy for Power-Split Hybrid Electric Vehicles
Directory of Open Access Journals (Sweden)
Chaoying Xia
2017-07-01
Full Text Available This paper presents a single-degree-of-freedom energy optimization strategy to solve the energy management problem existing in power-split hybrid electric vehicles (HEVs. The proposed strategy is based on a quadratic performance index, which is innovatively designed to simultaneously restrict the fluctuation of battery state of charge (SOC and reduce fuel consumption. An extended quadratic optimal control problem is formulated by approximating the fuel consumption rate as a quadratic polynomial of engine power. The approximated optimal control law is obtained by utilizing the solution properties of the Riccati equation and adjoint equation. It is easy to implement in real-time and the engineering significance is explained in details. In order to validate the effectiveness of the proposed strategy, the forward-facing vehicle simulation model is established based on the ADVISOR software (Version 2002, National Renewable Energy Laboratory, Golden, CO, USA. The simulation results show that there is only a little fuel consumption difference between the proposed strategy and the Pontryagin’s minimum principle (PMP-based global optimal strategy, and the proposed strategy also exhibits good adaptability under different initial battery SOC, cargo mass and road slope conditions.
Directory of Open Access Journals (Sweden)
Sathya Swaroop Debasish
2012-12-01
Full Text Available The primary objective of the study is to investigate the existence of seasonality in stock price behavior in Indian stock market and more specifically in the IT sector. The period of the study is from 3rd November 1994 to 31st December 2010. The study has employed daily price series of selected seven IT companies obtained from the official website of National Stock Exchange (NSE. The study used multiple regression technique to examine the significance of the regression coefficient for investigating day of week effects and week of the month effect, and Kruskal Wallis for analysis of trading strategy. It is found that all the seven selected IT companies evidenced day of the week effect and mostly either on Monday, Tuesday or Wednesday. Only Patni and Wipro evidenced significant Thursday effect. Similarly, evidence on week of month effect mostly either on 1st week, 2nd week or 3rd week. This implies that active portfolio management taking into account the findings will provide superior returns on investment in the IT sector in India.
Directory of Open Access Journals (Sweden)
Mandic Radivoj
2016-09-01
Full Text Available The aim of the present study was to explore the control strategy of maximum countermovement jumps regarding the preferred countermovement depth preceding the concentric jump phase. Elite basketball players and physically active non-athletes were tested on the jumps performed with and without an arm swing, while the countermovement depth was varied within the interval of almost 30 cm around its preferred value. The results consistently revealed 5.1-11.2 cm smaller countermovement depth than the optimum one, but the same difference was more prominent in non-athletes. In addition, although the same differences revealed a marked effect on the recorded force and power output, they reduced jump height for only 0.1-1.2 cm. Therefore, the studied control strategy may not be based solely on the countermovement depth that maximizes jump height. In addition, the comparison of the two groups does not support the concept of a dual-task strategy based on the trade-off between maximizing jump height and minimizing the jumping quickness that should be more prominent in the athletes that routinely need to jump quickly. Further research could explore whether the observed phenomenon is based on other optimization principles, such as the minimization of effort and energy expenditure. Nevertheless, future routine testing procedures should take into account that the control strategy of maximum countermovement jumps is not fully based on maximizing the jump height, while the countermovement depth markedly confound the relationship between the jump height and the assessed force and power output of leg muscles.
Mandic, Radivoj; Knezevic, Olivera M; Mirkov, Dragan M; Jaric, Slobodan
2016-09-01
The aim of the present study was to explore the control strategy of maximum countermovement jumps regarding the preferred countermovement depth preceding the concentric jump phase. Elite basketball players and physically active non-athletes were tested on the jumps performed with and without an arm swing, while the countermovement depth was varied within the interval of almost 30 cm around its preferred value. The results consistently revealed 5.1-11.2 cm smaller countermovement depth than the optimum one, but the same difference was more prominent in non-athletes. In addition, although the same differences revealed a marked effect on the recorded force and power output, they reduced jump height for only 0.1-1.2 cm. Therefore, the studied control strategy may not be based solely on the countermovement depth that maximizes jump height. In addition, the comparison of the two groups does not support the concept of a dual-task strategy based on the trade-off between maximizing jump height and minimizing the jumping quickness that should be more prominent in the athletes that routinely need to jump quickly. Further research could explore whether the observed phenomenon is based on other optimization principles, such as the minimization of effort and energy expenditure. Nevertheless, future routine testing procedures should take into account that the control strategy of maximum countermovement jumps is not fully based on maximizing the jump height, while the countermovement depth markedly confound the relationship between the jump height and the assessed force and power output of leg muscles.
An Optimal Operating Strategy for Battery Life Cycle Costs in Electric Vehicles
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Yinghua Han
2014-01-01
Full Text Available Impact on petroleum based vehicles on the environment, cost, and availability of fuel has led to an increased interest in electric vehicle as a means of transportation. Battery is a major component in an electric vehicle. Economic viability of these vehicles depends on the availability of cost-effective batteries. This paper presents a generalized formulation for determining the optimal operating strategy and cost optimization for battery. Assume that the deterioration of the battery is stochastic. Under the assumptions, the proposed operating strategy for battery is formulated as a nonlinear optimization problem considering reliability and failure number. And an explicit expression of the average cost rate is derived for battery lifetime. Results show that the proposed operating strategy enhances the availability and reliability at a low cost.
Optimal Investment-Consumption Strategy under Inflation in a Markovian Regime-Switching Market
Directory of Open Access Journals (Sweden)
Huiling Wu
2016-01-01
Full Text Available This paper studies an investment-consumption problem under inflation. The consumption price level, the prices of the available assets, and the coefficient of the power utility are assumed to be sensitive to the states of underlying economy modulated by a continuous-time Markovian chain. The definition of admissible strategies and the verification theory corresponding to this stochastic control problem are presented. The analytical expression of the optimal investment strategy is derived. The existence, boundedness, and feasibility of the optimal consumption are proven. Finally, we analyze in detail by mathematical and numerical analysis how the risk aversion, the correlation coefficient between the inflation and the stock price, the inflation parameters, and the coefficient of utility affect the optimal investment and consumption strategy.
Integrated Optimization of Bus Line Fare and Operational Strategies Using Elastic Demand
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Chunyan Tang
2017-01-01
Full Text Available An optimization approach for designing a transit service system is proposed. Its objective would be the maximization of total social welfare, by providing a profitable fare structure and tailoring operational strategies to passenger demand. These operational strategies include full route operation (FRO, limited stop, short turn, and a mix of the latter two strategies. The demand function is formulated to reflect the attributes of these strategies, in-vehicle crowding, and fare effects on demand variation. The fare is either a flat fare or a differential fare structure; the latter is based on trip distance and achieved service levels. This proposed methodology is applied to a case study of Dalian, China. The optimal results indicate that an optimal combination of operational strategies integrated with a differential fare structure results in the highest potential for increasing total social welfare, if the value of parameter ε related to additional service fee is low. When this value increases up to more than a threshold, strategies with a flat fare show greater benefits. If this value increases beyond yet another threshold, the use of skipped stop strategies is not recommended.
Design of Underwater Robot Lines Based on a Hybrid Automatic Optimization Strategy
Institute of Scientific and Technical Information of China (English)
Wenjing Lyu; Weilin Luo
2014-01-01
In this paper, a hybrid automatic optimization strategy is proposed for the design of underwater robot lines. Isight is introduced as an integration platform. The construction of this platform is based on the user programming and several commercial software including UG6.0, GAMBIT2.4.6 and FLUENT12.0. An intelligent parameter optimization method, the particle swarm optimization, is incorporated into the platform. To verify the strategy proposed, a simulation is conducted on the underwater robot model 5470, which originates from the DTRC SUBOFF project. With the automatic optimization platform, the minimal resistance is taken as the optimization goal;the wet surface area as the constraint condition; the length of the fore-body, maximum body radius and after-body’s minimum radius as the design variables. With the CFD calculation, the RANS equations and the standard turbulence model are used for direct numerical simulation. By analyses of the simulation results, it is concluded that the platform is of high efficiency and feasibility. Through the platform, a variety of schemes for the design of the lines are generated and the optimal solution is achieved. The combination of the intelligent optimization algorithm and the numerical simulation ensures a global optimal solution and improves the efficiency of the searching solutions.
An Optimal Investment Strategy and Multiperiod Deposit Insurance Pricing Model for Commercial Banks
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Grant E. Muller
2018-01-01
Full Text Available We employ the method of stochastic optimal control to derive the optimal investment strategy for maximizing an expected exponential utility of a commercial bank’s capital at some future date T>0. In addition, we derive a multiperiod deposit insurance (DI pricing model that incorporates the explicit solution of the optimal control problem and an asset value reset rule comparable to the typical practice of insolvency resolution by insuring agencies. By way of numerical simulations, we study the effects of changes in the DI coverage horizon, the risk associated with the asset portfolio of the bank, and the bank’s initial leverage level (deposit-to-asset ratio on the DI premium while the optimal investment strategy is followed.
Multi-objective optimal strategy for generating and bidding in the power market
International Nuclear Information System (INIS)
Peng Chunhua; Sun Huijuan; Guo Jianfeng; Liu Gang
2012-01-01
Highlights: ► A new benefit/risk/emission comprehensive generation optimization model is established. ► A hybrid multi-objective differential evolution optimization algorithm is designed. ► Fuzzy set theory and entropy weighting method are employed to extract the general best solution. ► The proposed approach of generating and bidding is efficient for maximizing profit and minimizing both risk and emissions. - Abstract: Based on the coordinated interaction between units output and electricity market prices, the benefit/risk/emission comprehensive generation optimization model with objectives of maximal profit and minimal bidding risk and emissions is established. A hybrid multi-objective differential evolution optimization algorithm, which successfully integrates Pareto non-dominated sorting with differential evolution algorithm and improves individual crowding distance mechanism and mutation strategy to avoid premature and unevenly search, is designed to achieve Pareto optimal set of this model. Moreover, fuzzy set theory and entropy weighting method are employed to extract one of the Pareto optimal solutions as the general best solution. Several optimization runs have been carried out on different cases of generation bidding and scheduling. The results confirm the potential and effectiveness of the proposed approach in solving the multi-objective optimization problem of generation bidding and scheduling. In addition, the comparison with the classical optimization algorithms demonstrates the superiorities of the proposed algorithm such as integrality of Pareto front, well-distributed Pareto-optimal solutions, high search speed.
Directory of Open Access Journals (Sweden)
Davood Mahmoodzadeh
2016-05-01
Full Text Available Groundwater in coastal areas is an essential source of freshwater that warrants protection from seawater intrusion as a priority based on an optimal management plan. Proper optimal management strategies can be developed using a variety of decision-making models. The present study aims to investigate the impacts of environmental changes on groundwater resources. For this purpose, a combined simulation-optimization model is employed that incorporates the SUTRA numerical model and the evolutionaty method of ant colony optimization. The fresh groundwater lens in Kish Island is used as a case study and different scenarios are considered for the likely enviromental changes. Results indicate that while variations in recharge rate form an important factor in the fresh groundwater lens, land-surface inundation due to rises in seawater level, especially in low-lying lands, is the major factor affecting the lens. Furthermore, impacts of environmental changes when effected into the Kish Island aquifer optimization management plan have led to a reduction of more than 20% in the allowable water extraction, indicating the high sensitivity of groundwater resources management plans in small islands to such variations.
Directory of Open Access Journals (Sweden)
Mun-Kyeom Kim
2017-09-01
Full Text Available This study introduces a frequency regulation strategy to enable the participation of wind turbines with permanent magnet synchronous generators (PMSGs. The optimal strategy focuses on developing the frequency support capability of PMSGs connected to the power system. Active power control is performed using maximum power point tracking (MPPT and de-loaded control to supply the required power reserve following a disturbance. A kinetic energy (KE reserve control is developed to enhance the frequency regulation capability of wind turbines. The coordination with the de-loaded control prevents instability in the PMSG wind system due to excessive KE discharge. A KE optimization method that maximizes the sum of the KE reserves at wind farms is also adopted to determine the de-loaded power reference for each PMSG wind turbine using the particle swarm optimization (PSO algorithm. To validate the effectiveness of the proposed optimal control and operation strategy, three different case studies are conducted using the PSCAD/EMTDC simulation tool. The results demonstrate that the optimal strategy enhances the frequency support contribution from PMSG wind turbines.
DEFF Research Database (Denmark)
Hu, Weihao; Chen, Zhe; Bak-Jensen, Birgitte
2010-01-01
markets in some ways, is chosen as the studied power system in this paper. Two kinds of BESS, based on polysulfide-bromine (PSB) and vanadium redox (VRB) battery technologies, are studies in the paper. Simulation results show, that the proposed optimal operation strategy is an effective measure to achieve......Since the hourly spot market price is available one day ahead, the price could be transferred to the consumers and they may have some motivations to install an energy storage system in order to save their energy costs. This paper presents an optimal operation strategy for a battery energy storage...
Energy evaluation of optimal control strategies for central VWV chiller systems
International Nuclear Information System (INIS)
Jin Xinqiao; Du Zhimin; Xiao Xiaokun
2007-01-01
Under various conditions, the actual load of the heating, ventilation and air conditioning (HVAC) systems is less than it is originally designed in most operation periods. To save energy and to optimize the controls for chilling systems, the performance of variable water volume (VWV) systems and characteristics of control systems are analyzed, and three strategies are presented and tested based on simulation in this paper. Energy evaluation for the three strategies shows that they can save energy to some extent, and there is potential remained. To minimize the energy consumption of chilling system, the setpoints of controls of supply chilled water temperature and supply head of secondary pump should be optimized simultaneously
Distributed Strategy for Optimal Dispatch of Unbalanced Three-Phase Islanded Microgrids
DEFF Research Database (Denmark)
Vergara Barrios, Pedro Pablo; Rey-López, Juan Manuel; Shaker, Hamid Reza
2018-01-01
This paper presents a distributed strategy for the optimal dispatch of islanded microgrids, modeled as unbalanced three-phase electrical distribution systems (EDS). To set the dispatch of the distributed generation (DG) units, an optimal generation problem is stated and solved distributively based......-phase microgrid. According to the obtained results, the proposed strategy achieves a lower cost solution when compared with a centralized approach based on a static droop framework, with a considerable reduction on the communication system complexity. Additionally, it corrects the mismatch between generation...
Convexity of Ruin Probability and Optimal Dividend Strategies for a General Lévy Process
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Chuancun Yin
2015-01-01
Full Text Available We consider the optimal dividends problem for a company whose cash reserves follow a general Lévy process with certain positive jumps and arbitrary negative jumps. The objective is to find a policy which maximizes the expected discounted dividends until the time of ruin. Under appropriate conditions, we use some recent results in the theory of potential analysis of subordinators to obtain the convexity properties of probability of ruin. We present conditions under which the optimal dividend strategy, among all admissible ones, takes the form of a barrier strategy.
Convexity of Ruin Probability and Optimal Dividend Strategies for a General Lévy Process
Yuen, Kam Chuen; Shen, Ying
2015-01-01
We consider the optimal dividends problem for a company whose cash reserves follow a general Lévy process with certain positive jumps and arbitrary negative jumps. The objective is to find a policy which maximizes the expected discounted dividends until the time of ruin. Under appropriate conditions, we use some recent results in the theory of potential analysis of subordinators to obtain the convexity properties of probability of ruin. We present conditions under which the optimal dividend strategy, among all admissible ones, takes the form of a barrier strategy. PMID:26351655
Optimal Claiming Strategies in Bonus Malus Systems and Implied Markov Chains
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Arthur Charpentier
2017-11-01
Full Text Available In this paper, we investigate the impact of the accident reporting strategy of drivers, within a Bonus-Malus system. We exhibit the induced modification of the corresponding class level transition matrix and derive the optimal reporting strategy for rational drivers. The hunger for bonuses induces optimal thresholds under which, drivers do not claim their losses. Mathematical properties of the induced level class process are studied. A convergent numerical algorithm is provided for computing such thresholds and realistic numerical applications are discussed.
Evolution strategies and multi-objective optimization of permanent magnet motor
DEFF Research Database (Denmark)
Andersen, Søren Bøgh; Santos, Ilmar
2012-01-01
When designing a permanent magnet motor, several geometry and material parameters are to be defined. This is not an easy task, as material properties and magnetic fields are highly non-linear and the design of a motor is therefore often an iterative process. From an engineering point of view, we...... of evolution strategies, ES to effectively design and optimize parameters of permanent magnet motors. Single as well as multi-objective optimization procedures are carried out. A modified way of creating the strategy parameters for the ES algorithm is also proposed and has together with the standard ES...
Directory of Open Access Journals (Sweden)
Li MingChu
2017-01-01
Full Text Available The terrorist’s coordinated attack is becoming an increasing threat to western countries. By monitoring potential terrorists, security agencies are able to detect and destroy terrorist plots at their planning stage. Therefore, an optimal monitoring strategy for the domestic security agency becomes necessary. However, previous study about monitoring strategy generation fails to consider the information leakage, due to hackers and insider threat. Such leakage events may lead to failure of watching potential terrorists and destroying the plot, and cause a huge risk to public security. This paper makes two major contributions. Firstly, we develop a new Stackelberg game model for the security agency to generate optimal monitoring strategy with the consideration of information leakage. Secondly, we provide a double-oracle framework DO-TPDIL for calculation effectively. The experimental result shows that our approach can obtain robust strategies against information leakage with high feasibility and efficiency.
The Development and Empirical Validation of an E-based Supply Chain Strategy Optimization Model
DEFF Research Database (Denmark)
Kotzab, Herbert; Skjoldager, Niels; Vinum, Thorkil
2003-01-01
Examines the formulation of supply chain strategies in complex environments. Argues that current state‐of‐the‐art e‐business and supply chain management, combined into the concept of e‐SCM, as well as the use of transaction cost theory, network theory and resource‐based theory, altogether can...... be used to form a model for analyzing supply chains with the purpose of reducing the uncertainty of formulating supply chain strategies. Presents e‐supply chain strategy optimization model (e‐SOM) as a way to analyze supply chains in a structured manner as regards strategic preferences for supply chain...... design, relations and resources in the chains with the ultimate purpose of enabling the formulation of optimal, executable strategies for specific supply chains. Uses research results for a specific supply chain to validate the usefulness of the model....
International Nuclear Information System (INIS)
Kim, Heungseob; Kim, Pansoo
2017-01-01
To maximize the reliability of a system, the traditional reliability–redundancy allocation problem (RRAP) determines the component reliability and level of redundancy for each subsystem. This paper proposes an advanced RRAP that also considers the optimal redundancy strategy, either active or cold standby. In addition, new examples are presented for it. Furthermore, the exact reliability function for a cold standby redundant subsystem with an imperfect detector/switch is suggested, and is expected to replace the previous approximating model that has been used in most related studies. A parallel genetic algorithm for solving the RRAP as a mixed-integer nonlinear programming model is presented, and its performance is compared with those of previous studies by using numerical examples on three benchmark problems. - Highlights: • Optimal strategy is proposed to solve reliability redundancy allocation problem. • The redundancy strategy uses parallel genetic algorithm. • Improved reliability function for a cold standby subsystem is suggested. • Proposed redundancy strategy enhances the system reliability.
The topography of the environment alters the optimal search strategy for active particles
Volpe, Giorgio; Volpe, Giovanni
2017-10-01
In environments with scarce resources, adopting the right search strategy can make the difference between succeeding and failing, even between life and death. At different scales, this applies to molecular encounters in the cell cytoplasm, to animals looking for food or mates in natural landscapes, to rescuers during search and rescue operations in disaster zones, and to genetic computer algorithms exploring parameter spaces. When looking for sparse targets in a homogeneous environment, a combination of ballistic and diffusive steps is considered optimal; in particular, more ballistic Lévy flights with exponent α≤1 are generally believed to optimize the search process. However, most search spaces present complex topographies. What is the best search strategy in these more realistic scenarios? Here, we show that the topography of the environment significantly alters the optimal search strategy toward less ballistic and more Brownian strategies. We consider an active particle performing a blind cruise search for nonregenerating sparse targets in a 2D space with steps drawn from a Lévy distribution with the exponent varying from α=1 to α=2 (Brownian). We show that, when boundaries, barriers, and obstacles are present, the optimal search strategy depends on the topography of the environment, with α assuming intermediate values in the whole range under consideration. We interpret these findings using simple scaling arguments and discuss their robustness to varying searcher's size. Our results are relevant for search problems at different length scales from animal and human foraging to microswimmers' taxis to biochemical rates of reaction.
Directory of Open Access Journals (Sweden)
Karim Marini Thomé
2013-04-01
economias emergentes foi identificado como a capacidade da firma em gerenciar as interfaces entre os recursos e capacidades da firma, as demandas de competitividade industrial e as condições e transições institucionais. Esta capacidade possibilitou à firma estudada se sobressair à dificuldade e a explorar oportunidades de negócios em diferentes partes do globo.This case study revisits the questions raised by Peng (2004; 2003 with respect to what drives firm strategy and the determinants of success or failure in international business. Specifically, the study investigates what drives the strategy of a trading company and determines its success in international business. The theoretical framework focuses on trading companies and the triangular relationships between these companies, their clients and their suppliers and on three approaches or bases of strategy in international business, those of industrial competitiveness, firm resources and capabilities, and institutional contexts and transitions. The study, descriptive and qualitative in nature, collected data by means of in-depth interviews, document analysis and non-participant observation during the period from July, 2010 to January, 2011. The firm selected for study is a trading company conducting a large percentage of its total transactions between emerging economies. Results demonstrate that there is no single driver of this trading company strategy. Rather, there was evidence of the use of a variety of strategies, driven at times by the demands of industrial competitiveness, at times by firm resources and capabilities, and at times by institutional conditions. Each driver corresponded to a specific moment in the trajectory of the trading company studied. In addition, there was no evidence neither of a linear chronological order for these drivers, nor of driver obsolescence. On the contrary, the evidence of the study suggests that drivers are cumulative and cyclical, requiring review and even re-thinking when
Directory of Open Access Journals (Sweden)
Santanu Biswas
Full Text Available Visceral leishmaniasis (VL is a deadly neglected tropical disease that poses a serious problem in various countries all over the world. Implementation of various intervention strategies fail in controlling the spread of this disease due to issues of parasite drug resistance and resistance of sandfly vectors to insecticide sprays. Due to this, policy makers need to develop novel strategies or resort to a combination of multiple intervention strategies to control the spread of the disease. To address this issue, we propose an extensive SIR-type model for anthroponotic visceral leishmaniasis transmission with seasonal fluctuations modeled in the form of periodic sandfly biting rate. Fitting the model for real data reported in South Sudan, we estimate the model parameters and compare the model predictions with known VL cases. Using optimal control theory, we study the effects of popular control strategies namely, drug-based treatment of symptomatic and PKDL-infected individuals, insecticide treated bednets and spray of insecticides on the dynamics of infected human and vector populations. We propose that the strategies remain ineffective in curbing the disease individually, as opposed to the use of optimal combinations of the mentioned strategies. Testing the model for different optimal combinations while considering periodic seasonal fluctuations, we find that the optimal combination of treatment of individuals and insecticide sprays perform well in controlling the disease for the time period of intervention introduced. Performing a cost-effective analysis we identify that the same strategy also proves to be efficacious and cost-effective. Finally, we suggest that our model would be helpful for policy makers to predict the best intervention strategies for specific time periods and their appropriate implementation for elimination of visceral leishmaniasis.
Li MingChu; Yang Zekun; Lu Kun; Guo Cheng
2017-01-01
The terrorist’s coordinated attack is becoming an increasing threat to western countries. By monitoring potential terrorists, security agencies are able to detect and destroy terrorist plots at their planning stage. Therefore, an optimal monitoring strategy for the domestic security agency becomes necessary. However, previous study about monitoring strategy generation fails to consider the information leakage, due to hackers and insider threat. Such leakage events may lead to failure of watch...
Optimization of Gas Supply as a Component of the Energy Strategy of Ukraine
Directory of Open Access Journals (Sweden)
Skrypnyk Andrii V.
2017-09-01
Full Text Available There considered the trade in natural gas in four regional markets, namely the market of North America, the market of Central and South America, the market of Europe and Eurasia, and the Pacific market. The process of a global convergence of regimes of trading in natural gas is studied, and a hypothesis on the prospect of creating a world natural gas market is proposed. The hypothesis is based on reducing the dispersion of prices and increasing the share of liquefied natural gas in the total world sales of natural gas. Two optimization models are constructed: the first one relates to minimization of the transport costs on distributing the imported and domestically produced natural gas on the territory of Ukraine; the second model considers determination of the optimal structure of purchasing natural gas by Ukraine and its further distribution on the territory of the country, taking into account the prices of each supplier and the distances between the consumers and suppliers. There identified advantages for Ukraine from the possible formation of a world natural gas market, in particular improving the state of energy security and independence as well as reducing the amount of costs associated with meeting the domestic demand for natural gas.
International Nuclear Information System (INIS)
Porteus, E.
1982-01-01
The study of infinite-horizon nonstationary dynamic programs using the operator approach is continued. The point of view here differs slightly from that taken by others, in that Denardo's local income function is not used as a starting point. Infinite-horizon values are defined as limits of finite-horizon values, as the horizons get long. Two important conditions of an earlier paper are weakened, yet the optimality equations, the optimality criterion, and the existence of optimal ''structured'' strategies are still obtained
Risk-Averse Suppliers’ Optimal Pricing Strategies in a Two-Stage Supply Chain
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Rui Shen
2013-01-01
Full Text Available Risk-averse suppliers’ optimal pricing strategies in two-stage supply chains under competitive environment are discussed. The suppliers in this paper focus more on losses as compared to profits, and they care their long-term relationship with their customers. We introduce for the suppliers a loss function, which covers both current loss and future loss. The optimal wholesale price is solved under situations of risk neutral, risk averse, and a combination of minimizing loss and controlling risk, respectively. Besides, some properties of and relations among these optimal wholesale prices are given as well. A numerical example is given to illustrate the performance of the proposed method.
Optimization of cooling strategy and seeding by FBRM analysis of batch crystallization
Zhang, Dejiang; Liu, Lande; Xu, Shijie; Du, Shichao; Dong, Weibing; Gong, Junbo
2018-03-01
A method is presented for optimizing the cooling strategy and seed loading simultaneously. Focused beam reflectance measurement (FBRM) was used to determine the approximating optimal cooling profile. Using these results in conjunction with constant growth rate assumption, modified Mullin-Nyvlt trajectory could be calculated. This trajectory could suppress secondary nucleation and has the potential to control product's polymorph distribution. Comparing with linear and two step cooling, modified Mullin-Nyvlt trajectory have a larger size distribution and a better morphology. Based on the calculating results, the optimized seed loading policy was also developed. This policy could be useful for guiding the batch crystallization process.
Optimized bolt tightening strategies for gasketed flanged pipe joints of different sizes
International Nuclear Information System (INIS)
Abid, Muhammad; Khan, Ayesha; Nash, David Hugh; Hussain, Masroor; Wajid, Hafiz Abdul
2016-01-01
Achieving a proper preload in the bolts of a gasketed bolted flanged pipe joint during joint assembly is considered important for its optimized performance. This paper presents results of detailed non-linear finite element analysis of an optimized bolt tightening strategy of different joint sizes for achieving proper preload close to the target stress values. Industrial guidelines are considered for applying recommended target stress values with TCM (torque control method) and SCM (stretch control method) using a customized optimization algorithm. Different joint components performance is observed and discussed in detail.
Volpato, Enilze de Souza Nogueira; Betini, Marluci; Puga, Maria Eduarda; Agarwal, Arnav; Cataneo, Antônio José Maria; Oliveira, Luciane Dias de; Bazan, Rodrigo; Braz, Leandro Gobbo; Pereira, José Eduardo Guimarães; El Dib, Regina
2018-01-15
A high-quality electronic search is essential for ensuring accuracy and comprehensiveness among the records retrieved when conducting systematic reviews. Therefore, we aimed to identify the most efficient method for searching in both MEDLINE (through PubMed) and EMBASE, covering search terms with variant spellings, direct and indirect orders, and associations with MeSH and EMTREE terms (or lack thereof). Experimental study. UNESP, Brazil. We selected and analyzed 37 search strategies that had specifically been developed for the field of anesthesiology. These search strategies were adapted in order to cover all potentially relevant search terms, with regard to variant spellings and direct and indirect orders, in the most efficient manner. When the strategies included variant spellings and direct and indirect orders, these adapted versions of the search strategies selected retrieved the same number of search results in MEDLINE (mean of 61.3%) and a higher number in EMBASE (mean of 63.9%) in the sample analyzed. The numbers of results retrieved through the searches analyzed here were not identical with and without associated use of MeSH and EMTREE terms. However, association of these terms from both controlled vocabularies retrieved a larger number of records than did the use of either one of them. In view of these results, we recommend that the search terms used should include both preferred and non-preferred terms (i.e. variant spellings and direct/indirect order of the same term) and associated MeSH and EMTREE terms, in order to develop highly-sensitive search strategies for systematic reviews.
Social Optimization and Pricing Policy in Cognitive Radio Networks with an Energy Saving Strategy
Directory of Open Access Journals (Sweden)
Shunfu Jin
2016-01-01
Full Text Available The rapid growth of wireless application results in an increase in demand for spectrum resource and communication energy. In this paper, we firstly introduce a novel energy saving strategy in cognitive radio networks (CRNs and then propose an appropriate pricing policy for secondary user (SU packets. We analyze the behavior of data packets in a discrete-time single-server priority queue under multiple-vacation discipline. With the help of a Quasi-Birth-Death (QBD process model, we obtain the joint distribution for the number of SU packets and the state of base station (BS via the Matrix-Geometric Solution method. We assess the average latency of SU packets and the energy saving ratio of system. According to a natural reward-cost structure, we study the individually optimal behavior and the socially optimal behavior of the energy saving strategy and use an optimization algorithm based on standard particle swarm optimization (SPSO method to search the socially optimal arrival rate of SU packets. By comparing the individually optimal behavior and the socially optimal behavior, we impose an appropriate admission fee to SU packets. Finally, we present numerical results to show the impacts of system parameters on the system performance and the pricing policy.
Optimal robust control strategy of a solid oxide fuel cell system
Wu, Xiaojuan; Gao, Danhui
2018-01-01
Optimal control can ensure system safe operation with a high efficiency. However, only a few papers discuss optimal control strategies for solid oxide fuel cell (SOFC) systems. Moreover, the existed methods ignore the impact of parameter uncertainty on system instantaneous performance. In real SOFC systems, several parameters may vary with the variation of operation conditions and can not be identified exactly, such as load current. Therefore, a robust optimal control strategy is proposed, which involves three parts: a SOFC model with parameter uncertainty, a robust optimizer and robust controllers. During the model building process, boundaries of the uncertain parameter are extracted based on Monte Carlo algorithm. To achieve the maximum efficiency, a two-space particle swarm optimization approach is employed to obtain optimal operating points, which are used as the set points of the controllers. To ensure the SOFC safe operation, two feed-forward controllers and a higher-order robust sliding mode controller are presented to control fuel utilization ratio, air excess ratio and stack temperature afterwards. The results show the proposed optimal robust control method can maintain the SOFC system safe operation with a maximum efficiency under load and uncertainty variations.
Two-objective on-line optimization of supervisory control strategy
Energy Technology Data Exchange (ETDEWEB)
Nassif, N.; Kajl, S.; Sabourin, R. [Ecole de Technologie Superieure, Montreal (Canada)
2004-09-01
The set points of supervisory control strategy are optimized with respect to energy use and thermal comfort for existing HVAC systems. The set point values of zone temperatures, supply duct static pressure, and supply air temperature are the problem variables, while energy use and thermal comfort are the objective functions. The HVAC system model includes all the individual component models developed and validated against the monitored data of an existing VAV system. It serves to calculate energy use during the optimization process, whereas the actual energy use is determined by using monitoring data and the appropriate validated component models. A comparison, done for one summer week, of actual and optimal energy use shows that the on-line implementation of a genetic algorithm optimization program to determine the optimal set points of supervisory control strategy could save energy by 19.5%, while satisfying the minimum zone airflow rates and the thermal comfort. The results also indicate that the application of the two-objective optimization problem can help control daily energy use or daily building thermal comfort, thus saving more energy than the application of the one-objective optimization problem. (Author)
Institute of Scientific and Technical Information of China (English)
DeqingTan; GuangzhongLiu
2004-01-01
The Bertrand model of two firms' static multidimensional game with incomplete information for two kinds of product with certain substitution is discussed in the paper,and analyzes influences of the firms' forecasting results of total market demands on their optimal strategies according to marxet information. The conclusions are that the more a firm masters market information, the greater differences of forecasted values and expected values of market demands for products have influence upon equilibrium strategies; conversely, the less they have influence upon equilibrium strategies.
Optimism, pain coping strategies and pain intensity among women with rheumatoid arthritis
Directory of Open Access Journals (Sweden)
Zuzanna Kwissa-Gajewska
2014-07-01
Full Text Available Objectives: According to the biopsychosocial model of pain, it is a multidimensional phenomenon, which comprises physiological (sensation-related factors, psychological (affective and social (socio-economic status, social support factors. Researchers have mainly focused on phenomena increasing the pain sensation; very few studies have examined psychological factors preventing pain. The aim of the research is to assess chronic pain intensity as determined by level of optimism, and to identify pain coping strategies in women with rheumatoid arthritis (RA. Material and methods : A survey was carried out among 54 women during a 7-day period of hospitalisation. The following questionnaires were used: LOT-R (optimism; Scheier, Carver and Bridges, the Coping Strategies Questionnaire (CSQ; Rosenstiel and Keefe and the 10-point visual-analogue pain scale (VAS. Results: The research findings indicate the significance of optimism in the experience of chronic pain, and in the pain coping strategies. Optimists felt a significantly lower level of pain than pessimists. Patients with positive outcome expectancies (optimists experienced less pain thanks to replacing catastrophizing (negative concentration on pain with an increased activity level. Regardless of personality traits, active coping strategies (e.g. ignoring pain sensations, coping self-statements – appraising pain as a challenge, a belief in one’s ability to manage pain resulted in a decrease in pain, whilst catastrophizing contributed to its intensification. The most common coping strategies included praying and hoping. Employment was an important demographic variable: the unemployed experienced less pain than those who worked. Conclusions : The research results indicate that optimism and pain coping strategies should be taken into account in clinical practice. Particular attention should be given to those who have negative outcome expectations, which in turn determine strong chronic pain
Assessment of trading partners for China's rare earth exports using a decision analytic approach.
He, Chunyan; Lei, Yalin; Ge, Jianping
2014-01-01
Chinese rare earth export policies currently result in accelerating its depletion. Thus adopting an optimal export trade selection strategy is crucial to determining and ultimately identifying the ideal trading partners. This paper introduces a multi-attribute decision-making methodology which is then used to select the optimal trading partner. In the method, an evaluation criteria system is established to assess the seven top trading partners based on three dimensions: political relationships, economic benefits and industrial security. Specifically, a simple additive weighing model derived from an additive utility function is utilized to calculate, rank and select alternatives. Results show that Japan would be the optimal trading partner for Chinese rare earths. The criteria evaluation method of trading partners for China's rare earth exports provides the Chinese government with a tool to enhance rare earth industrial policies.
Reliability optimization of series–parallel systems with mixed redundancy strategy in subsystems
International Nuclear Information System (INIS)
Abouei Ardakan, Mostafa; Zeinal Hamadani, Ali
2014-01-01
Traditionally in redundancy allocation problem (RAP), it is assumed that the redundant components are used based on a predefined active or standby strategies. Recently, some studies consider the situation that both active and standby strategies can be used in a specific system. However, these researches assume that the redundancy strategy for each subsystem can be either active or standby and determine the best strategy for these subsystems by using a proper mathematical model. As an extension to this assumption, a novel strategy, that is a combination of traditional active and standby strategies, is introduced. The new strategy is called mixed strategy which uses both active and cold-standby strategies in one subsystem simultaneously. Therefore, the problem is to determine the component type, redundancy level, number of active and cold-standby units for each subsystem in order to maximize the system reliability. To have a more practical model, the problem is formulated with imperfect switching of cold-standby redundant components and k-Erlang time-to-failure (TTF) distribution. As the optimization of RAP belongs to NP-hard class of problems, a genetic algorithm (GA) is developed. The new strategy and proposed GA are implemented on a well-known test problem in the literature which leads to interesting results. - Highlights: • In this paper the redundancy allocation problem (RAP) for a series–parallel system is considered. • Traditionally there are two main strategies for redundant component namely active and standby. • In this paper a new redundancy strategy which is called “Mixed” redundancy strategy is introduced. • Computational experiments demonstrate that implementing the new strategy lead to interesting results
A characteristic study of CCF modeling techniques and optimization of CCF defense strategies
International Nuclear Information System (INIS)
Kim, Min Chull
2000-02-01
Common Cause Failures (CCFs ) are among the major contributors to risk and core damage frequency (CDF ) from operating nuclear power plants (NPPs ). Our study on CCF focused on the following aspects : 1) a characteristic study on the CCF modeling techniques and 2) development of the optimal CCF defense strategy. Firstly, the characteristics of CCF modeling techniques were studied through sensitivity study of CCF occurrence probability upon system redundancy. The modeling techniques considered in this study include those most widely used worldwide, i.e., beta factor, MGL, alpha factor, and binomial failure rate models. We found that MGL and alpha factor models are essentially identical in terms of the CCF probability. Secondly, in the study for CCF defense, the various methods identified in the previous studies for defending against CCF were classified into five different categories. Based on these categories, we developed a generic method by which the optimal CCF defense strategy can be selected. The method is not only qualitative but also quantitative in nature: the selection of the optimal strategy among candidates is based on the use of analytic hierarchical process (AHP). We applied this method to two motor-driven valves for containment sump isolation in Ulchin 3 and 4 nuclear power plants. The result indicates that the method for developing an optimal CCF defense strategy is effective
Beyond the drugs : non-pharmacological strategies to optimize procedural care in children
Leroy, Piet L.; Costa, Luciane R.; Emmanouil, Dimitris; van Beukering, Alice; Franck, Linda S.
2016-01-01
Purpose of review Painful and/or stressful medical procedures mean a substantial burden for sick children. There is good evidence that procedural comfort can be optimized by a comprehensive comfort-directed policy containing the triad of non-pharmacological strategies (NPS) in all cases, timely or
Energy Technology Data Exchange (ETDEWEB)
A.Badri; Jadid, S. [Department of Electrical Engineering, Iran University of Science and Technology (Iran); Rashidinejad, M. [Shahid Bahonar University, Kerman (Iran); Moghaddam, M.P. [Tarbiat Modarres University, Tehran (Iran)
2008-06-15
In electricity industry with transmission constraints and limited number of producers, Generation Companies (GenCos) are facing an oligopoly market rather than a perfect competition one. Under oligopoly market environment, each GenCo may increase its own profit through a favorable bidding strategy. This paper investigates the problem of developing optimal bidding strategies of GenCos, considering bilateral contracts and transmission constraints. The problem is modeled with a bi-level optimization algorithm, where in the first level each GenCo maximizes its payoff and in the second level a system dispatch will be accomplished through an OPF problem in which transmission constraints are taken into account. It is assumed that each GenCo has information about initial bidding strategies of other competitors. Impacts of exercising market power due to transmission constraints as well as irrational biddings of the some generators are studied and the interactions of different bidding strategies on participants' corresponding payoffs are presented. Furthermore, a risk management-based method to obtain GenCos' optimal bilateral contracts is proposed and the impacts of these contracts on GenCos' optimal biddings and obtained payoffs are investigated. At the end, IEEE 30-bus test system is used for the case study in order to demonstrate the simulation results and support the effectiveness of the proposed model. (author)
Optimal Control Strategy Search Using a Simplest 3-D PWR Xenon Oscillation Simulator
International Nuclear Information System (INIS)
Yoichiro, Shimazu
2004-01-01
Power spatial oscillations due to the transient xenon spatial distribution are well known as xenon oscillation in large PWRs. When the reactor size becomes larger than the current design, then even radial oscillations can be also divergent. Even if the radial oscillation is convergent, when some control rods malfunction occurs, it is necessary to suppress the oscillation in as short time as possible. In such cases, optimal control strategy is required. Generally speaking the optimality search based on the modern control theory requires a lot of calculation for the evaluation of state variables. In the case of control rod malfunctions the xenon oscillation could be three dimensional. In such case, direct core calculations would be inevitable. From this point of view a very simple model, only four point reactor model, has been developed and verified. In this paper, an example of a procedure and the results for optimal control strategy search are presented. It is shown that we have only one optimal strategy within a half cycle of the oscillation with fixed control strength. It is also shown that a 3-D xenon oscillation introduced by a control rod malfunction can not be controlled by only one control step as can be done for axial oscillations. They might be quite strong limitations to the operators. Thus it is recommended that a strategy generator, which is quick in analyzing and easy to use, might be installed in a monitoring system or operator guiding system. (author)
Research of Ant Colony Optimized Adaptive Control Strategy for Hybrid Electric Vehicle
Directory of Open Access Journals (Sweden)
Linhui Li
2014-01-01
Full Text Available Energy management control strategy of hybrid electric vehicle has a great influence on the vehicle fuel consumption with electric motors adding to the traditional vehicle power system. As vehicle real driving cycles seem to be uncertain, the dynamic driving cycles will have an impact on control strategy’s energy-saving effect. In order to better adapt the dynamic driving cycles, control strategy should have the ability to recognize the real-time driving cycle and adaptively adjust to the corresponding off-line optimal control parameters. In this paper, four types of representative driving cycles are constructed based on the actual vehicle operating data, and a fuzzy driving cycle recognition algorithm is proposed for online recognizing the type of actual driving cycle. Then, based on the equivalent fuel consumption minimization strategy, an ant colony optimization algorithm is utilized to search the optimal control parameters “charge and discharge equivalent factors” for each type of representative driving cycle. At last, the simulation experiments are conducted to verify the accuracy of the proposed fuzzy recognition algorithm and the validity of the designed control strategy optimization method.
A Regional Time-of-Use Electricity Price Based Optimal Charging Strategy for Electrical Vehicles
Directory of Open Access Journals (Sweden)
Jun Yang
2016-08-01
Full Text Available With the popularization of electric vehicles (EVs, the out-of-order charging behaviors of large numbers of EVs will bring new challenges to the safe and economic operation of power systems. This paper studies an optimal charging strategy for EVs. For that a typical urban zone is divided into four regions, a regional time-of-use (RTOU electricity price model is proposed to guide EVs when and where to charge considering spatial and temporal characteristics. In light of the elastic coefficient, the user response to the RTOU electricity price is analyzed, and also a bilayer optimization charging strategy including regional-layer and node-layer models is suggested to schedule the EVs. On the one hand, the regional layer model is designed to coordinate the EVs located in different time and space. On the other hand, the node layer model is built to schedule the EVs to charge in certain nodes. According to the simulations of an IEEE 33-bus distribution network, the performance of the proposed optimal charging strategy is verified. The results demonstrate that the proposed bilayer optimization strategy can effectively decrease the charging cost of users, mitigate the peak-valley load difference and the network loss. Besides, the RTOU electricity price shows better performance than the time-of-use (TOU electricity price.
An Optimal Portfolio and Capital Management Strategy for Basel III Compliant Commercial Banks
Directory of Open Access Journals (Sweden)
Grant E. Muller
2014-01-01
Full Text Available We model a Basel III compliant commercial bank that operates in a financial market consisting of a treasury security, a marketable security, and a loan and we regard the interest rate in the market as being stochastic. We find the investment strategy that maximizes an expected utility of the bank’s asset portfolio at a future date. This entails obtaining formulas for the optimal amounts of bank capital invested in different assets. Based on the optimal investment strategy, we derive a model for the Capital Adequacy Ratio (CAR, which the Basel Committee on Banking Supervision (BCBS introduced as a measure against banks’ susceptibility to failure. Furthermore, we consider the optimal investment strategy subject to a constant CAR at the minimum prescribed level. We derive a formula for the bank’s asset portfolio at constant (minimum CAR value and present numerical simulations on different scenarios. Under the optimal investment strategy, the CAR is above the minimum prescribed level. The value of the asset portfolio is improved if the CAR is at its (constant minimum value.
Optimal orientation in flows : Providing a benchmark for animal movement strategies
McLaren, James D.; Shamoun-Baranes, Judy; Dokter, Adriaan M.; Klaassen, Raymond H. G.; Bouten, Willem
2014-01-01
Animal movements in air and water can be strongly affected by experienced flow. While various flow-orientation strategies have been proposed and observed, their performance in variable flow conditions remains unclear. We apply control theory to establish a benchmark for time-minimizing (optimal)
Stability Analysis and Optimal Control Strategy for Prevention of Pine Wilt Disease
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Kwang Sung Lee
2014-01-01
Full Text Available We propose a mathematical model of pine wilt disease (PWD which is caused by pine sawyer beetles carrying the pinewood nematode (PWN. We calculate the basic reproduction number R0 and investigate the stability of a disease-free and endemic equilibrium in a given mathematical model. We show that the stability of the equilibrium in the proposed model can be controlled through the basic reproduction number R0. We then discuss effective optimal control strategies for the proposed PWD mathematical model. We demonstrate the existence of a control problem, and then we apply both analytical and numerical techniques to demonstrate effective control methods to prevent the transmission of the PWD. In order to do this, we apply two control strategies: tree-injection of nematicide and the eradication of adult beetles through aerial pesticide spraying. Optimal prevention strategies can be determined by solving the corresponding optimality system. Numerical simulations of the optimal control problem using a set of reasonable parameter values suggest that reducing the number of pine sawyer beetles is more effective than the tree-injection strategy for controlling the spread of PWD.
Paterakis, N.G.; Erdinç, O.; Bakirtzis, A.G.; Catalao, J.P.S.
2015-01-01
In this paper, a detailed home energy management system structure is developed to determine the optimal dayahead appliance scheduling of a smart household under hourly pricing and peak power-limiting (hard and soft power limitation)-based demand response strategies. All types of controllable assets
Optimal and Robust Switching Control Strategies : Theory, and Applications in Traffic Management
Hajiahmadi, M.
2015-01-01
Macroscopic modeling, predictive and robust control and route guidance for large-scale freeway and urban traffic networks are the main focus of this thesis. In order to increase the efficiency of our control strategies, we propose several mathematical and optimization techniques. Moreover, in the
Burger, J.M.S.; Hemerik, L.; Lenteren, van J.C.; Vet, L.E.M.
2004-01-01
We developed a dynamic state variable model for studying optimal host-handling strategies in the whitefly parasitoid Encarsia formosa Gahan (Hymenoptera: Aphelinidae). We assumed that (a) the function of host feeding is to gain nutrients that can be matured into eggs, (b) oogenesis is continuous and
Burger, J.S.M.; Hemerik, L.; Van Lenteren, J.C.; Vet, L.E.M.
2004-01-01
We developed a dynamic state variable model for studying optimal host-handling strategies in the whitefly parasitoid Encarsia formosa Gahan (Hymenoptera: Aphelinidae). We assumed that (a) the function of host feeding is to gain nutrients that can be matured into eggs, (b) oögenesis is continuous and
International Nuclear Information System (INIS)
Badri, A.; Jadid, S.; Rashidinejad, M.; Moghaddam, M.P.
2008-01-01
In electricity industry with transmission constraints and limited number of producers, Generation Companies (GenCos) are facing an oligopoly market rather than a perfect competition one. Under oligopoly market environment, each GenCo may increase its own profit through a favorable bidding strategy. This paper investigates the problem of developing optimal bidding strategies of GenCos, considering bilateral contracts and transmission constraints. The problem is modeled with a bi-level optimization algorithm, where in the first level each GenCo maximizes its payoff and in the second level a system dispatch will be accomplished through an OPF problem in which transmission constraints are taken into account. It is assumed that each GenCo has information about initial bidding strategies of other competitors. Impacts of exercising market power due to transmission constraints as well as irrational biddings of the some generators are studied and the interactions of different bidding strategies on participants' corresponding payoffs are presented. Furthermore, a risk management-based method to obtain GenCos' optimal bilateral contracts is proposed and the impacts of these contracts on GenCos' optimal biddings and obtained payoffs are investigated. At the end, IEEE 30-bus test system is used for the case study in order to demonstrate the simulation results and support the effectiveness of the proposed model. (author)
Robinson, Stephanie A.; Rickenbach, Elizabeth H.; Lachman, Margie E.
2016-01-01
The effective use of self-regulatory strategies, such as selection, optimization, and compensation (SOC) requires resources. However, it is theorized that SOC use is most advantageous for those experiencing losses and diminishing resources. The present study explored this seeming paradox within the context of limitations or constraints due to…
Multi-objective Optimization Strategies Using Adjoint Method and Game Theory in Aerodynamics
Tang, Zhili
2006-08-01
There are currently three different game strategies originated in economics: (1) Cooperative games (Pareto front), (2) Competitive games (Nash game) and (3) Hierarchical games (Stackelberg game). Each game achieves different equilibria with different performance, and their players play different roles in the games. Here, we introduced game concept into aerodynamic design, and combined it with adjoint method to solve multi-criteria aerodynamic optimization problems. The performance distinction of the equilibria of these three game strategies was investigated by numerical experiments. We computed Pareto front, Nash and Stackelberg equilibria of the same optimization problem with two conflicting and hierarchical targets under different parameterizations by using the deterministic optimization method. The numerical results show clearly that all the equilibria solutions are inferior to the Pareto front. Non-dominated Pareto front solutions are obtained, however the CPU cost to capture a set of solutions makes the Pareto front an expensive tool to the designer.
Development of an evaluation method for optimization of maintenance strategy in commercial plant
International Nuclear Information System (INIS)
Ito, Satoshi; Shiraishi, Natsuki; Yuki, Kazuhisa; Hashizume, Hidetoshi
2006-01-01
In this study, a new simulation method is developed for optimization of maintenance strategy in NPP as a multiple-objective optimization problem (MOP). The result of operation is evaluated as the average of the following three measures in 3,000 trials: Cost of Electricity (COE) as economic risk, Frequency of unplanned shutdown as plant reliability, and Unavailability of Regular Service System (RSS) and Engineering Safety Features (ESF) as safety measures. The following maintenance parameters are considered to evaluate several risk in plant operation by changing maintenance strategy: planned outage cycle, surveillance cycle, major inspection cycle, and surveillance cycle depending on the value of Fussel-Vesely importance measure. By using the Decision-Making method based on AHP, there are individual tendencies depending on individual decision-maker. Therefore this study could be useful for resolving the problem of maintenance optimization as a MOP. (author)
Multi-objective optimization strategies using adjoint method and game theory in aerodynamics
Institute of Scientific and Technical Information of China (English)
Zhili Tang
2006-01-01
There are currently three different game strategies originated in economics:(1) Cooperative games (Pareto front),(2)Competitive games (Nash game) and (3)Hierarchical games (Stackelberg game).Each game achieves different equilibria with different performance,and their players play different roles in the games.Here,we introduced game concept into aerodynamic design, and combined it with adjoint method to solve multicriteria aerodynamic optimization problems.The performance distinction of the equilibria of these three game strategies was investigated by numerical experiments.We computed Pareto front, Nash and Stackelberg equilibria of the same optimization problem with two conflicting and hierarchical targets under different parameterizations by using the deterministic optimization method.The numerical results show clearly that all the equilibria solutions are inferior to the Pareto front.Non-dominated Pareto front solutions are obtained,however the CPU cost to capture a set of solutions makes the Pareto front an expensive tool to the designer.
Modelling and Optimal Control of Typhoid Fever Disease with Cost-Effective Strategies.
Tilahun, Getachew Teshome; Makinde, Oluwole Daniel; Malonza, David
2017-01-01
We propose and analyze a compartmental nonlinear deterministic mathematical model for the typhoid fever outbreak and optimal control strategies in a community with varying population. The model is studied qualitatively using stability theory of differential equations and the basic reproductive number that represents the epidemic indicator is obtained from the largest eigenvalue of the next-generation matrix. Both local and global asymptotic stability conditions for disease-free and endemic equilibria are determined. The model exhibits a forward transcritical bifurcation and the sensitivity analysis is performed. The optimal control problem is designed by applying Pontryagin maximum principle with three control strategies, namely, the prevention strategy through sanitation, proper hygiene, and vaccination; the treatment strategy through application of appropriate medicine; and the screening of the carriers. The cost functional accounts for the cost involved in prevention, screening, and treatment together with the total number of the infected persons averted. Numerical results for the typhoid outbreak dynamics and its optimal control revealed that a combination of prevention and treatment is the best cost-effective strategy to eradicate the disease.
Optimal offering and operating strategies for wind-storage systems with linear decision rules
DEFF Research Database (Denmark)
Ding, Huajie; Pinson, Pierre; Hu, Zechun
2016-01-01
The participation of wind farm-energy storage systems (WF-ESS) in electricity markets calls for an integrated view of day-ahead offering strategies and real-time operation policies. Such an integrated strategy is proposed here by co-optimizing offering at the day-ahead stage and operation policy...... to be used at the balancing stage. Linear decision rules are seen as a natural approach to model and optimize the real-time operation policy. These allow enhancing profits from balancing markets based on updated information on prices and wind power generation. Our integrated strategies for WF...
Optimal Search Strategy of Robotic Assembly Based on Neural Vibration Learning
Directory of Open Access Journals (Sweden)
Lejla Banjanovic-Mehmedovic
2011-01-01
Full Text Available This paper presents implementation of optimal search strategy (OSS in verification of assembly process based on neural vibration learning. The application problem is the complex robot assembly of miniature parts in the example of mating the gears of one multistage planetary speed reducer. Assembly of tube over the planetary gears was noticed as the most difficult problem of overall assembly. The favourable influence of vibration and rotation movement on compensation of tolerance was also observed. With the proposed neural-network-based learning algorithm, it is possible to find extended scope of vibration state parameter. Using optimal search strategy based on minimal distance path between vibration parameter stage sets (amplitude and frequencies of robots gripe vibration and recovery parameter algorithm, we can improve the robot assembly behaviour, that is, allow the fastest possible way of mating. We have verified by using simulation programs that search strategy is suitable for the situation of unexpected events due to uncertainties.
Optimal recharge and driving strategies for a battery-powered electric vehicle
Directory of Open Access Journals (Sweden)
Lee W. R.
1999-01-01
Full Text Available A major problem facing battery-powered electric vehicles is in their batteries: weight and charge capacity. Thus, a battery-powered electric vehicle only has a short driving range. To travel for a longer distance, the batteries are required to be recharged frequently. In this paper, we construct a model for a battery-powered electric vehicle, in which driving strategy is to be obtained such that the total travelling time between two locations is minimized. The problem is formulated as an optimization problem with switching times and speed as decision variables. This is an unconventional optimization problem. However, by using the control parametrization enhancing technique (CPET, it is shown that this unconventional optimization is equivalent to a conventional optimal parameter selection problem. Numerical examples are solved using the proposed method.
A novel optimal coordinated control strategy for the updated robot system for single port surgery.
Bai, Weibang; Cao, Qixin; Leng, Chuntao; Cao, Yang; Fujie, Masakatsu G; Pan, Tiewen
2017-09-01
Research into robotic systems for single port surgery (SPS) has become widespread around the world in recent years. A new robot arm system for SPS was developed, but its positioning platform and other hardware components were not efficient. Special features of the developed surgical robot system make good teleoperation with safety and efficiency difficult. A robot arm is combined and used as new positioning platform, and the remote center motion is realized by a new method using active motion control. A new mapping strategy based on kinematics computation and a novel optimal coordinated control strategy based on real-time approaching to a defined anthropopathic criterion configuration that is referred to the customary ease state of human arms and especially the configuration of boxers' habitual preparation posture are developed. The hardware components, control architecture, control system, and mapping strategy of the robotic system has been updated. A novel optimal coordinated control strategy is proposed and tested. The new robot system can be more dexterous, intelligent, convenient and safer for preoperative positioning and intraoperative adjustment. The mapping strategy can achieve good following and representation for the slave manipulator arms. And the proposed novel control strategy can enable them to complete tasks with higher maneuverability, lower possibility of self-interference and singularity free while teleoperating. Copyright © 2017 John Wiley & Sons, Ltd.
Trade Friction of Sino-US Intellectual Property and Coping Strategies%中美贸易中知识产权摩擦及应对策略
Institute of Scientific and Technical Information of China (English)
贾显维
2012-01-01
In recent years, trade friction of Sino-US intellectual property is becoming the focus of Sino-US trade friction, which has become the biggest obstacle for China's enterprises exporting to the U.S. In this paper, the causes and characteristics of trade friction of Sino-US intellectual property were analyzed, and the coping strategies of trade friction of Sino-US intellectual property were put forward from two levels of government and business, combing with China's actual conditions.%近些来,中美知识产权贸易摩擦日渐成为中美贸易摩擦的焦点,已成为中国企业对美出口的最大障碍.本文对中美知识产权贸易摩擦的特点、原因进行了分析,结合我国的实际情况,从政府及企业两个层面提出了应对中美知识产权贸易摩擦的策略.
PEMFC Optimization Strategy with Auxiliary Power Source in Fuel Cell Hybrid Vehicle
Directory of Open Access Journals (Sweden)
Tinton Dwi Atmaja
2012-02-01
Full Text Available Page HeaderOpen Journal SystemsJournal HelpUser You are logged in as...aulia My Journals My Profile Log Out Log Out as UserNotifications View (27 new ManageJournal Content SearchBrowse By Issue By Author By Title Other JournalsFont SizeMake font size smaller Make font size default Make font size largerInformation For Readers For Authors For LibrariansKeywords CBPNN Displacement FLC LQG/LTR Mixed PMA Ventilation bottom shear stress direct multiple shooting effective fuzzy logic geoelectrical method hourly irregular wave missile trajectory panoramic image predator-prey systems seawater intrusion segmentation structure development pattern terminal bunt manoeuvre Home About User Home Search Current Archives ##Editorial Board##Home > Vol 23, No 1 (2012 > AtmajaPEMFC Optimization Strategy with Auxiliary Power Source in Fuel Cell Hybrid VehicleTinton Dwi Atmaja, Amin AminAbstractone of the present-day implementation of fuel cell is acting as main power source in Fuel Cell Hybrid Vehicle (FCHV. This paper proposes some strategies to optimize the performance of Polymer Electrolyte Membrane Fuel Cell (PEMFC implanted with auxiliary power source to construct a proper FCHV hybridization. The strategies consist of the most updated optimization method determined from three point of view i.e. Energy Storage System (ESS, hybridization topology and control system analysis. The goal of these strategies is to achieve an optimum hybridization with long lifetime, low cost, high efficiency, and hydrogen consumption rate improvement. The energy storage system strategy considers battery, supercapacitor, and high-speed flywheel as the most promising alternative auxiliary power source. The hybridization topology strategy analyzes the using of multiple storage devices injected with electronic components to bear a higher fuel economy and cost saving. The control system strategy employs nonlinear control system to optimize the ripple factor of the voltage and the current
Establishment of an immortalized mouse dermal papilla cell strain with optimized culture strategy
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Haiying Guo
2018-01-01
Full Text Available Dermal papilla (DP plays important roles in hair follicle regeneration. Long-term culture of mouse DP cells can provide enough cells for research and application of DP cells. We optimized the culture strategy for DP cells from three dimensions: stepwise dissection, collagen I coating, and optimized culture medium. Based on the optimized culture strategy, we immortalized primary DP cells with SV40 large T antigen, and established several immortalized DP cell strains. By comparing molecular expression and morphologic characteristics with primary DP cells, we found one cell strain named iDP6 was similar with primary DP cells. Further identifications illustrate that iDP6 expresses FGF7 and α-SMA, and has activity of alkaline phosphatase. During the process of characterization of immortalized DP cell strains, we also found that cells in DP were heterogeneous. We successfully optimized culture strategy for DP cells, and established an immortalized DP cell strain suitable for research and application of DP cells.
Applying the Taguchi method to river water pollution remediation strategy optimization.
Yang, Tsung-Ming; Hsu, Nien-Sheng; Chiu, Chih-Chiang; Wang, Hsin-Ju
2014-04-15
Optimization methods usually obtain the travel direction of the solution by substituting the solutions into the objective function. However, if the solution space is too large, this search method may be time consuming. In order to address this problem, this study incorporated the Taguchi method into the solution space search process of the optimization method, and used the characteristics of the Taguchi method to sequence the effects of the variation of decision variables on the system. Based on the level of effect, this study determined the impact factor of decision variables and the optimal solution for the model. The integration of the Taguchi method and the solution optimization method successfully obtained the optimal solution of the optimization problem, while significantly reducing the solution computing time and enhancing the river water quality. The results suggested that the basin with the greatest water quality improvement effectiveness is the Dahan River. Under the optimal strategy of this study, the severe pollution length was reduced from 18 km to 5 km.
Applying the Taguchi Method to River Water Pollution Remediation Strategy Optimization
Directory of Open Access Journals (Sweden)
Tsung-Ming Yang
2014-04-01
Full Text Available Optimization methods usually obtain the travel direction of the solution by substituting the solutions into the objective function. However, if the solution space is too large, this search method may be time consuming. In order to address this problem, this study incorporated the Taguchi method into the solution space search process of the optimization method, and used the characteristics of the Taguchi method to sequence the effects of the variation of decision variables on the system. Based on the level of effect, this study determined the impact factor of decision variables and the optimal solution for the model. The integration of the Taguchi method and the solution optimization method successfully obtained the optimal solution of the optimization problem, while significantly reducing the solution computing time and enhancing the river water quality. The results suggested that the basin with the greatest water quality improvement effectiveness is the Dahan River. Under the optimal strategy of this study, the severe pollution length was reduced from 18 km to 5 km.