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.

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)

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.

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)

Dynamic optimal strategies in transboundary pollution game under learning by doing

Science.gov (United States)

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.

Uncertainty analysis for effluent trading planning using a Bayesian estimation-based simulation-optimization modeling approach.

Science.gov (United States)

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

Energy Efficiency - Spectral Efficiency Trade-off: A Multiobjective Optimization Approach

KAUST Repository

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

KAUST Repository

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.

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.

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.

Trade Union Organisers in Trade Union Organising Strategies: building workplace unionism or reinforcing bureaucracy

OpenAIRE

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...

Systematic Trading: Calibration Advances through Machine Learning

OpenAIRE

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...

Transitions in optimal adaptive strategies for populations in fluctuating environments

Science.gov (United States)

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 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...

A Power System Optimal Dispatch Strategy Considering the Flow of Carbon Emissions and Large Consumers

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.

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.

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...

An innovative cross-sectoral method for implementation of trade-off adaptation strategy assessment under climate change

Science.gov (United States)

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

A new equilibrium trading model with asymmetric information

Directory of Open Access Journals (Sweden)

Lianzhang Bao

2018-03-01

Full Text Available Taking arbitrage opportunities into consideration in an incomplete market, dealers will pricebonds based on asymmetric information. The dealer with the best offering price wins the bid. The riskpremium in dealer’s offering price is primarily determined by the dealer’s add-on rate of change tothe term structure. To optimize the trading strategy, a new equilibrium trading model is introduced.Optimal sequential estimation scheme for detecting the risk premium due to private inforamtion isproposed based on historical prices, and the best bond pricing formula is given with the accordingoptimal trading strategy. Numerical examples are provided to illustrate the economic insights underthe certain stochastic term structure interest rate models.

The European Union’s Trade Strategy and Its Reflections on Turkey: an Evaluation from the Perspective of Free Trade Agreements

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.

Bubbles, shocks and elementary technical trading strategies

Science.gov (United States)

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.

Containing diffusion: the tobacco industry's multipronged trade strategy to block tobacco standardised packaging.

Science.gov (United States)

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.

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.

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.

Technical Analysis in Forex : A Strategy for Individual Trader in Intra-Day Trading

OpenAIRE

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 ...

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.

Portfolio optimization in the cryptocurrency market : an evaluation of the performance of momentum strategies in the cryptocurrency market and cryptocurrency’s place in an optimized investment portfolio

OpenAIRE

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,...

A mathematical analysis of an exchange-traded horse race betting fund with deterministic payoff betting strategy for institutional investment to challenge EMH

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.

Proceedings of the Emissions trading conference : effective strategies for successful emissions trading in a global market

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

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 ...

Dynamic Optimal Production Strategies Based on the Inventory-Dependent Demand under the Cap-and-Trade Mechanism

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.

Map-Based Power-Split Strategy Design with Predictive Performance Optimization for Parallel Hybrid Electric Vehicles

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.

A Sequence Mining Method to Predict the Bidding Strategy of Trading Agents

Science.gov (United States)

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.

Forecasting stock market averages to enhance profitable trading strategies

OpenAIRE

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 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.

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.

Optimal Initial Public O¤ering design with aftermarket trading.

OpenAIRE

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...

Trading or coercion? Variation in male mating strategies between two communities of East African chimpanzees.

Science.gov (United States)

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.

Pareto Optimal Solutions for Network Defense Strategy Selection Simulator in Multi-Objective Reinforcement Learning

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.

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 ...

Mathematics, Pricing, Market Risk Management and Trading Strategies for Financial Derivatives (2/3)

CERN Multimedia

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

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.

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.

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.

Optimalizace vybrané obchodní strategie na měnovém trhu FOREX

OpenAIRE

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.

An Empirical Study on the Driving Path of Optimizing the Resources Allocation of Foreign Trade Enterprises from the Perspective of Energy Supply-side Reform

Science.gov (United States)

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.

Dynamic Portfolio Strategy Using Clustering Approach.

Science.gov (United States)

Ren, Fei; Lu, Ya-Nan; Li, Sai-Ping; Jiang, Xiong-Fei; Zhong, Li-Xin; Qiu, Tian

2017-01-01

The problem of portfolio optimization is one of the most important issues in asset management. We here propose a new dynamic portfolio strategy based on the time-varying structures of MST networks in Chinese stock markets, where the market condition is further considered when using the optimal portfolios for investment. A portfolio strategy comprises two stages: First, select the portfolios by choosing central and peripheral stocks in the selection horizon using five topological parameters, namely degree, betweenness centrality, distance on degree criterion, distance on correlation criterion and distance on distance criterion. Second, use the portfolios for investment in the investment horizon. The optimal portfolio is chosen by comparing central and peripheral portfolios under different combinations of market conditions in the selection and investment horizons. Market conditions in our paper are identified by the ratios of the number of trading days with rising index to the total number of trading days, or the sum of the amplitudes of the trading days with rising index to the sum of the amplitudes of the total trading days. We find that central portfolios outperform peripheral portfolios when the market is under a drawup condition, or when the market is stable or drawup in the selection horizon and is under a stable condition in the investment horizon. We also find that peripheral portfolios gain more than central portfolios when the market is stable in the selection horizon and is drawdown in the investment horizon. Empirical tests are carried out based on the optimal portfolio strategy. Among all possible optimal portfolio strategies based on different parameters to select portfolios and different criteria to identify market conditions, 65% of our optimal portfolio strategies outperform the random strategy for the Shanghai A-Share market while the proportion is 70% for the Shenzhen A-Share market.

Dynamic Portfolio Strategy Using Clustering Approach.

Directory of Open Access Journals (Sweden)

Fei Ren

Full Text Available The problem of portfolio optimization is one of the most important issues in asset management. We here propose a new dynamic portfolio strategy based on the time-varying structures of MST networks in Chinese stock markets, where the market condition is further considered when using the optimal portfolios for investment. A portfolio strategy comprises two stages: First, select the portfolios by choosing central and peripheral stocks in the selection horizon using five topological parameters, namely degree, betweenness centrality, distance on degree criterion, distance on correlation criterion and distance on distance criterion. Second, use the portfolios for investment in the investment horizon. The optimal portfolio is chosen by comparing central and peripheral portfolios under different combinations of market conditions in the selection and investment horizons. Market conditions in our paper are identified by the ratios of the number of trading days with rising index to the total number of trading days, or the sum of the amplitudes of the trading days with rising index to the sum of the amplitudes of the total trading days. We find that central portfolios outperform peripheral portfolios when the market is under a drawup condition, or when the market is stable or drawup in the selection horizon and is under a stable condition in the investment horizon. We also find that peripheral portfolios gain more than central portfolios when the market is stable in the selection horizon and is drawdown in the investment horizon. Empirical tests are carried out based on the optimal portfolio strategy. Among all possible optimal portfolio strategies based on different parameters to select portfolios and different criteria to identify market conditions, 65% of our optimal portfolio strategies outperform the random strategy for the Shanghai A-Share market while the proportion is 70% for the Shenzhen A-Share market.

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...

COMPANY SIZE, TRADING ACTIVITY AND LIQUIDITY AS A DETERMINANTS OF CROSS-SECTIONAL MOMENTUM TRADING STRATEGY ON RUSSIAN STOCK MARKET

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.

Assessment of trading partners for China's rare earth exports using a decision analytic approach.

Science.gov (United States)

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.

Learning to trade via direct reinforcement.

Science.gov (United States)

Moody, J; Saffell, M

2001-01-01

We present methods for optimizing portfolios, asset allocations, and trading systems based on direct reinforcement (DR). In this approach, investment decision-making is viewed as a stochastic control problem, and strategies are discovered directly. We present an adaptive algorithm called recurrent reinforcement learning (RRL) for discovering investment policies. The need to build forecasting models is eliminated, and better trading performance is obtained. The direct reinforcement approach differs from dynamic programming and reinforcement algorithms such as TD-learning and Q-learning, which attempt to estimate a value function for the control problem. We find that the RRL direct reinforcement framework enables a simpler problem representation, avoids Bellman's curse of dimensionality and offers compelling advantages in efficiency. We demonstrate how direct reinforcement can be used to optimize risk-adjusted investment returns (including the differential Sharpe ratio), while accounting for the effects of transaction costs. In extensive simulation work using real financial data, we find that our approach based on RRL produces better trading strategies than systems utilizing Q-learning (a value function method). Real-world applications include an intra-daily currency trader and a monthly asset allocation system for the S&P 500 Stock Index and T-Bills.

International trade shows: Structure, strategy and performance of exhibitors at individual booths vs. joint booths

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...

Optimal management strategies in variable environments: Stochastic optimal control methods

Science.gov (United States)

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

Retailer's optimal credit period and cycle time in a supply chain for deteriorating items with up-stream and down-stream trade credits

Science.gov (United States)

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.

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.

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.

The Optimal Replenishment Policy under Trade Credit Financing with Ramp Type Demand and Demand Dependent Production Rate

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.

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.

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.

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...

Optimal risky bidding strategy for a generating company by self-organising hierarchical particle swarm optimisation

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.

Externalities, Border Trade and Illegal Production: An Optimal Tax Approach to Alcohol Policy

OpenAIRE

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...

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: ...

COMPANY SIZE, TRADING ACTIVITY AND LIQUIDITY AS A DETERMINANTS OF CROSS-SECTIONAL MOMENTUM TRADING STRATEGY ON RUSSIAN STOCK MARKET. PART 2

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.

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)

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 ...

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...

Two retailer-supplier supply chain models with default risk under trade credit policy.

Science.gov (United States)

Wu, Chengfeng; Zhao, Qiuhong

2016-01-01

The purpose of the paper is to formulate two uncooperative replenishment models with demand and default risk which are the functions of the trade credit period, i.e., a Nash equilibrium model and a supplier-Stackelberg model. Firstly, we present the optimal results of decentralized decision and centralized decision without trade credit. Secondly, we derive the existence and uniqueness conditions of the optimal solutions under the two games, respectively. Moreover, we present a set of theorems and corollary to determine the optimal solutions. Finally, we provide an example and sensitivity analysis to illustrate the proposed strategy and optimal solutions. Sensitivity analysis reveals that the total profits of supply chain under the two games both are better than the results under the centralized decision only if the optimal trade credit period isn't too short. It also reveals that the size of trade credit period, demand, retailer's profit and supplier's profit have strong relationship with the increasing demand coefficient, wholesale price, default risk coefficient and production cost. The major contribution of the paper is that we comprehensively compare between the results of decentralized decision and centralized decision without trade credit, Nash equilibrium and supplier-Stackelberg models with trade credit, and obtain some interesting managerial insights and practical implications.

Analysis of intra-country virtual water trade strategy to alleviate water scarcity in Iran

Science.gov (United States)

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.

Sensitivity analysis of Portfolio Volatility: Importance of Weights, Sectors and the Impact of Trading Strategies

OpenAIRE

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 ...

Bio-Mimic Optimization Strategies in Wireless Sensor Networks: A Survey

Science.gov (United States)

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.

Science.gov (United States)

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.

Rationalities in Trade Union Practices: A Discourse Analytic Perspective on The Strategies of Three Danish Trade Unions for Professionals

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.

Development of renewable energy resources in Afghanistan for economically optimized cross-border electricity trading

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.

Justification of the Trade Enterprises Development Strategy in the Process of Strategic Management of the Marketing Potential

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.

Optimal GENCO bidding strategy

Science.gov (United States)

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

An internet graph model based on trade-off optimization

Science.gov (United States)

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.

Trading Agents

CERN Document Server

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

NSGA-II Algorithm with a Local Search Strategy for Multiobjective Optimal Design of Dry-Type Air-Core Reactor

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.

An optimal control model for reducing and trading of carbon emissions

Science.gov (United States)

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 Strategies for Low Carbon Supply Chain with Strategic Customer Behavior and Green Technology Investment

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.

Reliable Adaptive Data Aggregation Route Strategy for a Trade-off between Energy and Lifetime in WSNs

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.

Optimizing time and resource allocation trade-offs for investment into morphological and behavioral defense

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....

Long-run savings and investment strategy optimization.

Science.gov (United States)

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.

Finding a pareto-optimal solution for multi-region models subject to capital trade and spillover externalities

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.)

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....

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)

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

Reference-dependent electric vehicle production strategy considering subsidies and consumer trade-offs

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

Balancing Biomechanical Constraints: Optimal Escape Speeds When There Is a Trade-off between Speed and Maneuverability.

Science.gov (United States)

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

Mechanical properties of structural amorphous steels: Intrinsic correlations, conflicts, and optimizing strategies

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

Urban and agricultural soils: conflicts and trade-offs in the optimization of ecosystem services

NARCIS (Netherlands)

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

Heuristic Portfolio Trading Rules with Capital Gain Taxes

DEFF Research Database (Denmark)

Fischer, Marcel; Gallmeyer, Michael

in some cases. Overlaying simple tax trading heuristics on these trading strategies improves out-of-sample performance. In particular, the 1/N trading strategy's welfare gains improve when a variety of tax trading heuristics are also imposed. For medium to large transaction costs, no trading strategy can...... outperform a 1/N trading strategy augmented with a tax heuristic, not even the most tax- and transaction-cost efficient buy-and-hold strategy. Overall, the best strategy is 1/N augmented with a heuristic that allows for a fixed deviation in absolute portfolio weights. Our results show that the best trading...

Proceedings of the 1999 natural gas lookout and strategies forum : Price and supply outlook, trading and purchasing strategies

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

Using trading strategies to detect phase transitions in financial markets.

Science.gov (United States)

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

Science.gov (United States)

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.

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 control of anthracnose using mixed strategies.

Science.gov (United States)

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.

Noise-dependent optimal strategies for quantum metrology

Science.gov (United States)

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.

Investment Strategies Optimization based on a SAX-GA Methodology

CERN Document Server

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.

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...

Heuristic Portfolio Trading Rules with Capital Gain Taxes

DEFF Research Database (Denmark)

Fischer, Marcel; Gallmeyer, Michael

2016-01-01

We study the out-of-sample performance of portfolio trading strategies used when an investor faces capital gain taxation and proportional transaction costs. Overlaying simple tax trading heuristics on trading strategies improves out-of-sample performance. For medium to large transaction costs......, no trading strategy can outperform a 1/N trading strategy augmented with a tax heuristic, not even the most tax and transaction cost-efficient buy-and-hold strategy. Overall, the best strategy is 1/N augmented with a heuristic that allows for a fixed deviation in absolute portfolio weights. Our results thus...... show that the best trading strategies balance diversification considerations and tax considerations....

Control of Refrigeration Systems for Trade-off between Energy Consumption and Food Quality Loss

DEFF Research Database (Denmark)

Cai, Junping

In supermarkets, control strategies determine both the energy consumption of refrigeration systems and the quality loss of refrigerated foodstuffs. The question is, what can be done to optimize the balance between quality loss and energy consumption? This thesis tries to answer this question...... by applying two main optimization strategies to traditional refrigeration systems. The first strategy is a new defrost-on-demand scheme, which based on an objective function between quality loss and energy consumption, continuously seeks an optimal time interval for defrosting in dynamic situation. The second...... strategy is through utilization of the thermal mass of the refrigerated foodstuffs, the day-night temperature variation and the capacity control of the compressor, to realize a trade-off between system energy consumption and food quality loss....

Dynamic Volatility Arbitrage: The advents of long/short trading strategies with dynamic participation

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...

Trade, Foreign Direct Investment or Acquisition: Optimal Entry Modes for Multinationals

OpenAIRE

Theo Eicher; Jong Woo Kang

2004-01-01

We examine multinationals’ 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...

Optimal inventory management and order book modeling

KAUST Repository

Baradel, Nicolas

2018-02-16

We model the behavior of three agent classes acting dynamically in a limit order book of a financial asset. Namely, we consider market makers (MM), high-frequency trading (HFT) firms, and institutional brokers (IB). Given a prior dynamic of the order book, similar to the one considered in the Queue-Reactive models [14, 20, 21], the MM and the HFT define their trading strategy by optimizing the expected utility of terminal wealth, while the IB has a prescheduled task to sell or buy many shares of the considered asset. We derive the variational partial differential equations that characterize the value functions of the MM and HFT and explain how almost optimal control can be deduced from them. We then provide a first illustration of the interactions that can take place between these different market participants by simulating the dynamic of an order book in which each of them plays his own (optimal) strategy.

Optimal Advance Selling Strategy under Price Commitment

OpenAIRE

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 ...

Mathematics, Pricing, Market Risk Management and Trading Strategies for Financial Derivatives (1/3)

CERN Multimedia

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...

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

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.

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....

Study on Stochastic Optimal Electric Power Procurement Strategies with Uncertain Market Prices

Science.gov (United States)

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.

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 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.

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.

Exploring trade-offs between VMAT dose quality and delivery efficiency using a network optimization approach

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

Exploring trade-offs between VMAT dose quality and delivery efficiency using a network optimization approach.

Science.gov (United States)

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

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)

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)

Developing an Integrated Design Strategy for Chip Layout Optimization

NARCIS (Netherlands)

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 tax depreciation under a progressive tax system

OpenAIRE

Wielhouwer, J.L.; De Waegenaere, A.M.B.; Kort, P.M.

2002-01-01

The focus of this paper is on the effect of a progressive tax system on optimal tax depreciation. By using dynamic optimization we show that an optimal strategy exists, and we provide an analytical expression for the optimal depreciation charges. Depreciation charges initially decrease over time, and after a number of periods the firm enters a steady state where depreciation is constant and equal to replacement investments. This way, the optimal solution trades off the benefits of accelerated...

Life-history strategies of North American elk: trade-offs associated with reproduction and survival

Science.gov (United States)

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...

An Optimization Scheduling Model for Wind Power and Thermal Power with Energy Storage System considering Carbon Emission Trading

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.

The FTAA and hemispheric integration: building a triple-win strategy for trade and sustainability in the hemisphere

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

Optimal Stochastic Advertising Strategies for the U.S. Beef Industry

OpenAIRE

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.

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.

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.

Emergency strategy optimization for the environmental control system in manned spacecraft

Science.gov (United States)

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.

Optimal Control of Diesel Engines with Waste Heat Recovery System

NARCIS (Netherlands)

Willems, F.P.T.; Donkers, M.C.F.; Kupper, F.

2014-01-01

This study presents an integrated energy and emission management strategy for a Euro-VI diesel engine with Waste Heat Recovery (WHR) system. This Integrated Powertrain Control (IPC) strategy optimizes the CO2-NOx trade-off by minimizing the operational costs associated with fuel and AdBlue

Optimal control of diesel engines with waste heat recovery systems

NARCIS (Netherlands)

Willems, F.P.T.; Donkers, M.C.F.; Kupper, F.; Waschl, H.; Kolmanovsky, I.; Steinbuch, M.; Del Re, L.

2014-01-01

This study presents an integrated energy and emission management strategy for a Euro-VI diesel engine with Waste Heat Recovery (WHR) system. This Integrated Powertrain Control (IPC) strategy optimizes the CO 2 - NO x trade-off by minimizing the operational costs associated with fuel and AdBlue

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.

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.

Mixed integer evolution strategies for parameter optimization.

Science.gov (United States)

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.

Corporate Leverage and Product Differentiation Strategy

OpenAIRE

Arping, Stefan; Lóránth, Gyöngyi

2002-01-01

This article develops a model of the interplay between corporate leverage and product differentiation strategy. Leverage improves managerial discipline, but it can also raise customer concerns about a vendor's long-term viability. We argue that customer concerns about firm viability will be particularly pronounced when products are highly differentiated from competitors' products. In this context, optimal product differentiation strategies solve a trade-off between softening price competition...

Key Trends in the Development of Foreign Trade of France in the Global Competitive Environment

Directory of Open Access Journals (Sweden)

Zvirgzde Kateryna I.

2016-01-01

Full Text Available The article is aimed at analyzing the nature and contemporary trends of foreign trade activity of France. In the process of evolutionary development of the economy of France in content, structure and directions of its foreign trade strategies occurred permanent modifications and transformations, resulting from the need to maintain optimal proportions between material, financial and human resources, production and consumption, commodity supply and purchasing power, as well as receipts and payments in the settlements with other countries. The article is concerned with an integrated analysis of progressive structural reforms in the economic system of France in the last decade, which led to fundamental changes in its foreign trade operations both in terms of monetary magnitude of export-import transactions and their product-species, geographical, institutional and regulatory structures. The nature, key indicators, trends and issues in the foreign trade strategy of France in the face of global volatility as well as ways for its improvement have been researched.

A strategy for optimizing item-pool management

NARCIS (Netherlands)

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

Optimal knockout strategies in genome-scale metabolic networks using particle swarm optimization.

Science.gov (United States)

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.

Mean-variance Optimal Reinsurance-investment Strategy in Continuous Time

OpenAIRE

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.

Optimal generator bidding strategies for power and ancillary services

Science.gov (United States)

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

Intelligent fault recognition strategy based on adaptive optimized multiple centers

Science.gov (United States)

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.

Emissions Trading Regimes and Incentives to Participate in International Climate Agreements

International Nuclear Information System (INIS)

Buchner, B.; Carraro, C.

2003-11-01

This paper analyses whether different emissions trading regimes provide different incentives to participate in a cooperative climate agreement. Different incentive structures are discussed for those countries, namely the US, Russia and China, that are most important in the climate negotiation process. Our analysis confirms the conjecture that, by appropriately designing the emission trading regime, it is possible to enhance the incentives to participate in a climate agreement. Therefore, participation and optimal policy should be jointly analysed. Moreover, our results show that the US, Russia and China have different most preferred climate coalitions and therefore adopt conflicting negotiation strategies

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

Model-based optimization strategy of chiller driven liquid desiccant dehumidifier with genetic algorithm

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

A Unified Trading Model Based on Robust Optimization for Day-Ahead and Real-Time Markets with Wind Power Integration

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.

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 control of LQG problem with an explicit trade-off between mean and variance

Science.gov (United States)

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.

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.

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

A Unified Trading Model Based on Robust Optimization for Day-Ahead and Real-Time Markets with Wind Power Integration

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...

Trade in water and commodities as adaptations to global change

Science.gov (United States)

Lammers, R. B.; Hertel, T. W.; Prousevitch, A.; Baldos, U. L. C.; Frolking, S. E.; Liu, J.; Grogan, D. S.

2015-12-01

The human capacity for altering the water cycle has been well documented and given the expected change due to population, income growth, biofuels, climate, and associated land use change, there remains great uncertainty in both the degree of increased pressure on land and water resources and in our ability to adapt to these changes. Alleviating regional shortages in water supply can be carried out in a spatial hierarchy through i) direct trade of water between all regions, ii) development of infrastructure to improve water availability within regions (e.g. impounding rivers), iii) via inter-basin hydrological transfer between neighboring regions and, iv) via virtual water trade. These adaptation strategies can be managed via market trade in water and commodities to identify those strategies most likely to be adopted. This work combines the physically-based University of New Hampshire Water Balance Model (WBM) with the macro-scale Purdue University Simplified International Model of agricultural Prices Land use and the Environment (SIMPLE) to explore the interaction of supply and demand for fresh water globally. In this work we use a newly developed grid cell-based version of SIMPLE to achieve a more direct connection between the two modeling paradigms of physically-based models with optimization-driven approaches characteristic of economic models. We explore questions related to the global and regional impact of water scarcity and water surplus on the ability of regions to adapt to future change. Allowing for a variety of adaptation strategies such as direct trade of water and expanding the built water infrastructure, as well as indirect trade in commodities, will reduce overall global water stress and, in some regions, significantly reduce their vulnerability to these future changes.

Computing Optimal Stochastic Portfolio Execution Strategies: A Parametric Approach Using Simulations

Science.gov (United States)

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).

Customs Service Modernization: Impact of New Trade Compliance Strategy Needs to Be Assessed.

Science.gov (United States)

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

The end of a successful stage. Fta's in Chile's trade strategy

OpenAIRE

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...

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.

Real-time Trading Strategies for Proactive Distribution Company with Distributed Generation and Demand Response

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...

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.

Dispositional optimism and coping strategies in patients with a kidney transplant.

Science.gov (United States)

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.

Optimal pricing and replenishment policies for instantaneous deteriorating items with backlogging and trade credit under inflation

Science.gov (United States)

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.

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

Protectionism, free trade and preferential trade: the Mexican experience 1970-2005

Directory of Open Access Journals (Sweden)

2007-03-01

Full Text Available This paper is a theoretical and applied analysis of free trade policies and protectionism. First, the evolution of free trade theories, vis-à-vis protectionist ideas, is described, starting from the classical economists, their assumptions and implications for attaining welfare Pareto optimality, full employment and growth. Secondly, a structural analysis of the Mexican economy’s performance in three successive but different periods, regarding trade policies for the last thirty-five years is presented. I conclude that extreme free-trade policies have not been good for economic stability, growth and employment creation in Mexico.

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.

Strategies for the municipal waste management system to take advantage of carbon trading under competing policies: The role of energy from waste in Sydney

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.

Validation of optimization strategies using the linear structured production chains

Science.gov (United States)

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.

FOREX Trades: Can the Takens Algorithm Help to Obtain Steady Profit at Investment Reallocations?

Science.gov (United States)

Petrov, V. Yu.; Tribelsky, M. I.

2015-12-01

We report our preliminary results of application of the Takens algorithm to build a FOREX trade strategy, resulting in a steady long-time gain for a trader. The actual historical rates for pair EUR vs. USD are used. The values of various parameters of the problem including the "stop loss" and "take profit" thresholds are optimized to provide the maximal gain during the training period. Then, these values are employed for trades. We have succeeded to get the steady gain, if the spread is neglected. It proves that the FOREX market is predictable.

The Dynamics of Avian Influenza: Individual-Based Model with Intervention Strategies in Traditional Trade Networks in Phitsanulok Province, Thailand

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.

Continuous Trading Dynamically Effectively Complete Market with Heterogeneous Beliefs

DEFF Research Database (Denmark)

Qin, Zhenjiang

on the heterogeneous posterior variance of dividend throughout [0; T). The market populated with many time-additive exponential-utility investors is dynamically effectively complete, if investors are allowed to trade in only two long-lived securities continuously. The underlying mechanism is that these assumptions...... imply that the Pareto efficient individual consumption plans are measurable with respect to the aggregate consumption. Hence, I may not need a dynamically complete market to facilitate a Pareto efficient allocation of consumption, the securities only have to facilitate an allocation which is measurable...... a sufficient statistic for computation of the price of redundant dividend derivative and the equilibrium portfolios. The investors form their Pareto optimal trading strategies as if they intend to dynamically endogenously replicate the value of the dividend derivative....

A Joint Optimal Decision on Shipment Size and Carbon Reduction under Direct Shipment and Peddling Distribution Strategies

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.

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)

Evaluation of different hedging strategies for commodity price risks of industrial cogeneration plants

International Nuclear Information System (INIS)

Palzer, Andreas; Westner, Günther; Madlener, Reinhard

2013-01-01

In this paper, we design and evaluate eight different strategies for hedging commodity price risks of industrial cogeneration plants. Price developments are parameterized based on EEX data from 2008 to 2011. The probability distributions derived are used to determine the value-at-risk (VaR) of the individual strategies, which are in a final step combined in a mean-variance portfolio analysis for determining the most efficient hedging strategy. We find that the strategy adopted can have a marked influence on the remaining price risk. Quarter futures are found to be particularly well suited for reducing market price risk. In contrast, spot trading of CO 2 certificates is found to be preferable compared to forward market trading. Finally, portfolio optimization shows that a mix of various hedging strategies can further improve the profitability of a heat-based cogeneration plant. - Highlights: • Evaluation of commodity price risk hedging strategies for industrial cogeneration. • Value-at-risk analysis of eight different hedging strategies. • Mean-variance portfolio analysis for determining the optimal hedging strategy mix. • A mix of hedging strategies further improves profitability of heat-based CHP

Optimal Pricing Strategy in Marketing Research Consulting.

OpenAIRE

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...

Trade-off coding for universal qudit cloners motivated by the Unruh effect

International Nuclear Information System (INIS)

Jochym-O'Connor, Tomas; Bradler, Kamil; Wilde, Mark M

2011-01-01

A 'triple trade-off' capacity region of a noisy quantum channel provides a more complete description of its capabilities than does a single capacity formula. However, few full descriptions of a channel's ability have been given due to the difficult nature of the calculation of such regions-it may demand an optimization of information-theoretic quantities over an infinite number of channel uses. This work analyses the d-dimensional Unruh channel, a noisy quantum channel which emerges in relativistic quantum information theory. We show that this channel belongs to the class of quantum channels whose capacity region requires an optimization over a single channel use, and as such is tractable. We determine two triple-trade off regions, the quantum dynamic capacity region and the private dynamic capacity region, of the d-dimensional Unruh channel. Our results show that the set of achievable rate triples using this coding strategy is larger than the set achieved using a time-sharing strategy. Furthermore, we prove that the Unruh channel has a distinct structure made up of universal qudit cloning channels, thus providing a clear relationship between this relativistic channel and the process of stimulated emission present in quantum optical amplifiers. (paper)

Tariffs on power trading

International Nuclear Information System (INIS)

Van de Water, C.J.

1995-01-01

For optimal use of power systems, transmission services must be independent from production. Moreover the costs of electrical energy transmission should be well known and be paid according to a tariff system approximating to the real network costs. These two conditions for power trading will lead to an optimal power system. In a competitive power production market, the transmission and distribution companies will remain monopolistic because they are the only facilitators of power trading. The pricing signals of the transmission and distribution costs determine the playing field for the competitors. These are production offers and bidders. The transmission pricing must for that reason be simple, correct and based on marginal costs to make optimal use of the system

A Stock Trading Recommender System Based on Temporal Association Rule Mining

Directory of Open Access Journals (Sweden)

Binoy B. Nair

2015-04-01

Full Text Available Recommender systems capable of discovering patterns in stock price movements and generating stock recommendations based on the patterns thus discovered can significantly supplement the decision-making process of a stock trader. Such recommender systems are of great significance to a layperson who wishes to profit by stock trading even while not possessing the skill or expertise of a seasoned trader. A genetic algorithm optimized Symbolic Aggregate approXimation (SAX–Apriori based stock trading recommender system, which can mine temporal association rules from the stock price data set to generate stock trading recommendations, is presented in this article. The proposed system is validated on 12 different data sets. The results indicate that the proposed system significantly outperforms the passive buy-and-hold strategy, offering scope for a layperson to successfully invest in capital markets.

Evaluation of optimization strategies and the effect of initial conditions on IMAT optimization using a leaf position optimization algorithm

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.

Price-Taker Offering Strategy in Electricity Pay-as-Bid Markets

DEFF Research Database (Denmark)

Mazzi, Nicolò; Kazempour, Jalal; Pinson, Pierre

2017-01-01

The recent increase in the deployment of renewable energy sources may affect the offering strategy of conventional producers, mainly in the balancing market. The topics of optimal offering strategy and self-scheduling of thermal units have been extensively addressed in the literature. The feasible...... operating region of such units can be modeled using a mixed-integer linear programming approach, and the trading problem as a linear programming problem. However, the existing models mostly assume a uniform pricing scheme in all market stages, while several European balancing markets (e.g., in Germany...... and Italy) are settled under a pay-as-bid pricing scheme. The existing tools for solving the trading problem in pay-as-bid electricity markets rely on non-linear optimization models, which, combined with the unit commitment constraints, result in a mixed-integer non-linear programming problem. In contrast...

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.

Pairs Trading to the Commodities Futures Market Using Cointegration Method

Directory of Open Access Journals (Sweden)

Cüneyt Ungever

2015-10-01

Full Text Available This paper investigates pairs trading strategy by using the cointegration method among the 10 most popular agricultural future markets. It is found that only in 2 pairs shows trading signal. The pairs trading strategy is performed in two stages that are the formation period and the trading period with daily futures data from 2004 to 2015. After the formation period was constructed, it is assumed that the cointegration error continues to hold the trading period same as it does for the formation period. The pairs trading strategy is created by the long position cotton and the short position coffee and also long position cotton and short position the livecattle. It is found that the profitability of this strategy worked well in both formation period and trading period.

Bitcoin trading system

OpenAIRE

Turšič, Samo

2015-01-01

In this thesis an information solution was developed that enables the implementation of different trading strategies and backtesting over cryptocurrency Bitcoin trading data. Supported exchanges are Bitstamp, BTC-e and MtGox. In the field of technical analysis there already exist various solutions for Bitcoin that help traders to trade and advise them on basis of technical indicators and patterns. However, each has its own drawbacks, which we are aiming to fix. A web application was developed...

Bitcoin trading system

OpenAIRE

Turšič, Samo

2014-01-01

In this thesis an information solution was developed that enables the implementation of different trading strategies and backtesting over cryptocurrency Bitcoin trading data. Supported exchanges are Bitstamp, BTC-e and MtGox. In the field of technical analysis there already exist various solutions for Bitcoin that help traders to trade and advise them on basis of technical indicators and patterns. However, each has its own drawbacks, which we are aiming to fix. A web application was developed...

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.)

Optimal Control of Interdependent Epidemics in Complex Networks

OpenAIRE

Chen, Juntao; Zhang, Rui; Zhu, Quanyan

2017-01-01

Optimal control of interdependent epidemics spreading over complex networks is a critical issue. We first establish a framework to capture the coupling between two epidemics, and then analyze the system's equilibrium states by categorizing them into three classes, and deriving their stability conditions. The designed control strategy globally optimizes the trade-off between the control cost and the severity of epidemics in the network. A gradient descent algorithm based on a fixed point itera...

Optimal trade-offs between energy efficiency improvements and additional renewable energy supply: A review of international experiences

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....

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

An optimization strategy for the control of small capacity heat pump integrated air-conditioning system

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.

Optimal execution with price impact under Cumulative Prospect Theory

Science.gov (United States)

Zhao, Jingdong; Zhu, Hongliang; Li, Xindan

2018-01-01

Optimal execution of a stock (or portfolio) has been widely studied in academia and in practice over the past decade, and minimizing transaction costs is a critical point. However, few researchers consider the psychological factors for the traders. What are traders truly concerned with - buying low in the paper accounts or buying lower compared to others? We consider the optimal trading strategies in terms of the price impact and Cumulative Prospect Theory and identify some specific properties. Our analyses indicate that a large proportion of the execution volume is distributed at both ends of the transaction time. But the trader's optimal strategies may not be implemented at the same transaction size and speed in different market environments.

Trading Fees and Slow-Moving Capital

OpenAIRE

Buss, Adrian; Dumas, Bernard J

2015-01-01

In some situations, investment capital seems to move slowly towards profitable trades. We develop a model of a financial market in which capital moves slowly simply because there is a proportional cost to moving capital. We incorporate trading fees in an infinite-horizon dynamic general-equilibrium model in which investors optimally and endogenously decide when and how much to trade. We determine the steady-state equilibrium no-trade zone, study the dynamics of equilibrium trades and prices a...

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.

A universal optimization strategy for ant colony optimization algorithms based on the Physarum-inspired mathematical model

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)

Optimized Strategies for Detecting Extrasolar Space Weather

Science.gov (United States)

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.

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.

Optimal Dynamic Advertising Strategy Under Age-Specific Market Segmentation

Science.gov (United States)

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.

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

Visualising Pareto-optimal trade-offs helps move beyond monetary-only criteria for water management decisions

Science.gov (United States)

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.

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.

Estratégia em negócios internacionais: evidência em uma trading company que atua entre economias emergentes International business strategy: evidence from a trading company that operates in emerging economies

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

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

Automatic CT simulation optimization for radiation therapy: A general strategy.

Science.gov (United States)

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

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....

A decision support system for optimization of regional drinking water supply

NARCIS (Netherlands)

Vink, C.; Schot, P.P.

2000-01-01

Finding a strategy that allows economically efficient drinking water production in regional supply systems at minimal environmental cost is often a complex task. In order to determine the optimal spatial production configuration, a systematic trade off among costs and benefits of possible

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.

Blackjack in Holland Casino's : Basic, optimal and winning strategies

NARCIS (Netherlands)

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

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

Trading river services: optimizing dam decisions at the basin scale to improve socio-ecological resilience

Science.gov (United States)

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

Managing price risk - setting and implementing strategies

International Nuclear Information System (INIS)

Haines, D.

1999-01-01

The three hedging strategies for price risk management within the natural gas industry are described. The three strategies are: (1) speculative trader (characterized by 'trading for profit, i.e. small margin/large volumes); (2) price optimizer (the objective here is to outperform the market in the establishment of a price); and (3) strategic hedger( the characteristic concern in this strategy is to manage long-term company goals, i.e. balance sheet orientation). The strategies are not mutually exclusive, but overlapping areas can be the source of considerable confusion. Any firm can enter into more than one of these strategies. Integrated companies will adopt very different strategies for upstream versus downstream operations. Details of the three strategies are provided

Derivation of Optimal Operating Rules for Large-scale Reservoir Systems Considering Multiple Trade-off

Science.gov (United States)

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.

Effluent trading in river systems through stochastic decision-making process: a case study.

Science.gov (United States)

Zolfagharipoor, Mohammad Amin; Ahmadi, Azadeh

2017-09-01

The objective of this paper is to provide an efficient framework for effluent trading in river systems. The proposed framework consists of two pessimistic and optimistic decision-making models to increase the executability of river water quality trading programs. The models used for this purpose are (1) stochastic fallback bargaining (SFB) to reach an agreement among wastewater dischargers and (2) stochastic multi-criteria decision-making (SMCDM) to determine the optimal treatment strategy. The Monte-Carlo simulation method is used to incorporate the uncertainty into analysis. This uncertainty arises from stochastic nature and the errors in the calculation of wastewater treatment costs. The results of river water quality simulation model are used as the inputs of models. The proposed models are used in a case study on the Zarjoub River in northern Iran to determine the best solution for the pollution load allocation. The best treatment alternatives selected by each model are imported, as the initial pollution discharge permits, into an optimization model developed for trading of pollution discharge permits among pollutant sources. The results show that the SFB-based water pollution trading approach reduces the costs by US$ 14,834 while providing a relative consensus among pollutant sources. Meanwhile, the SMCDM-based water pollution trading approach reduces the costs by US$ 218,852, but it is less acceptable by pollutant sources. Therefore, it appears that giving due attention to stability, or in other words acceptability of pollution trading programs for all pollutant sources, is an essential element of their success.

Many-objective optimization and visual analytics reveal key trade-offs for London's water supply

Science.gov (United States)

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.

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.

Multilevel Optimization Framework for Hierarchical Stiffened Shells Accelerated by Adaptive Equivalent Strategy

Science.gov (United States)

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.

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.

Science.gov (United States)

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.

Trade-off coding for universal qudit cloners motivated by the Unruh effect

Energy Technology Data Exchange (ETDEWEB)

Jochym-O' Connor, Tomas [Department of Physics and Astronomy, Institute for Quantum Computing, University of Waterloo, 200 University Avenue West, Waterloo, Ontario N2 L 3G1 (Canada); Bradler, Kamil; Wilde, Mark M, E-mail: trjochym@uwaterloo.ca [School of Computer Science, McGill University, Montreal, Quebec H3A 2A7 (Canada)

2011-10-14

A 'triple trade-off' capacity region of a noisy quantum channel provides a more complete description of its capabilities than does a single capacity formula. However, few full descriptions of a channel's ability have been given due to the difficult nature of the calculation of such regions-it may demand an optimization of information-theoretic quantities over an infinite number of channel uses. This work analyses the d-dimensional Unruh channel, a noisy quantum channel which emerges in relativistic quantum information theory. We show that this channel belongs to the class of quantum channels whose capacity region requires an optimization over a single channel use, and as such is tractable. We determine two triple-trade off regions, the quantum dynamic capacity region and the private dynamic capacity region, of the d-dimensional Unruh channel. Our results show that the set of achievable rate triples using this coding strategy is larger than the set achieved using a time-sharing strategy. Furthermore, we prove that the Unruh channel has a distinct structure made up of universal qudit cloning channels, thus providing a clear relationship between this relativistic channel and the process of stimulated emission present in quantum optical amplifiers. (paper)

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.

Calibration of optimal execution of financial transactions in the presence of transient market impact

International Nuclear Information System (INIS)

Busseti, Enzo; Lillo, Fabrizio

2012-01-01

Trading large volumes of a financial asset in order driven markets requires the use of algorithmic execution dividing the volume into many transactions in order to minimize costs due to market impact. A proper design of an optimal execution strategy strongly depends on a careful modeling of market impact, i.e. how the price reacts to trades. In this paper we consider a recently introduced market impact model (Bouchaud et al 2004 Quant. Finance, 4 176–90), which has the property of describing both the volume and the temporal dependence of price change due to trading. We show how this model can be used to describe price impact also in aggregated trade time or in real time. We then solve analytically and calibrate with real data the optimal execution problem both for risk neutral and for risk averse investors and we derive an efficient frontier of optimal execution. When we include spread costs the problem must be solved numerically and we show that the introduction of such costs regularizes the solution. (paper)

Identifying optimal agricultural countermeasure strategies for a hypothetical contamination scenario using the strategy model

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

Another look at trading costs and short-term reversal profits

NARCIS (Netherlands)

W.A. de Groot (Wilma); J.J. Huij (Joop); W. Zhou (Weili)

2012-01-01

textabstractSeveral studies report that abnormal returns associated with short-term reversal investment strategies diminish once trading costs are taken into account. We show that the impact of trading costs on the strategies' profitability can largely be attributed to excessively trading in small

A water market simulator considering pair-wise trades between agents

Science.gov (United States)

Huskova, I.; Erfani, T.; Harou, J. J.

2012-04-01

In many basins in England no further water abstraction licences are available. Trading water between water rights holders has been recognized as a potentially effective and economically efficient strategy to mitigate increasing scarcity. A screening tool that could assess the potential for trade through realistic simulation of individual water rights holders would help assess the solution's potential contribution to local water management. We propose an optimisation-driven water market simulator that predicts pair-wise trade in a catchment and represents its interaction with natural hydrology and engineered infrastructure. A model is used to emulate licence-holders' willingness to engage in short-term trade transactions. In their simplest form agents are represented using an economic benefit function. The working hypothesis is that trading behaviour can be partially predicted based on differences in marginal values of water over space and time and estimates of transaction costs on pair-wise trades. We discuss the further possibility of embedding rules, norms and preferences of the different water user sectors to more realistically represent the behaviours, motives and constraints of individual licence holders. The potential benefits and limitations of such a social simulation (agent-based) approach is contrasted with our simulator where agents are driven by economic optimization. A case study based on the Dove River Basin (UK) demonstrates model inputs and outputs. The ability of the model to suggest impacts of water rights policy reforms on trading is discussed.

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.

Does AFTA Create More Trade for Thailand? An Investigation of Some Key Trade Indicators

Directory of Open Access Journals (Sweden)

Piriya Pholphirul

2010-04-01

Full Text Available This paper examines whether the ASEAN Free Trade Agreement (AFTA creates trade for Thailand or actually diverts it away from the country. It does this by analyzing various trade indicators: the Export Similarity Index, the Intra-Industry Trade Index, and Revealed Comparative Advantage (RCA rank correlation. By examining the patterns of trade between Thailand and other members of ASEAN, it reveals a high degree of similarity regarding the trade structure between Thailand and AFTA, which indicates that there will be fewer trade-creation benefits from AFTA and a greater likelihood of trade diversion once the AFTA scheme has been fully implemented. This similarity pattern explains the reasons for future collaboration among member countries and supportive arguments for the future extension of ASEAN ("ASEAN+". Market-penetration and development strategies should be employed by Thai exporters when accessing the ASEAN market.

Department of Trade annual report 1983-84. [Australia

Energy Technology Data Exchange (ETDEWEB)

1984-01-01

The Department of Trade was created on 11 March 1983. It is responsible for the administration of the Government's policies as they relate to international trade, the promotion of Australia's exports and the Australian Trade Commissioner Service. The Department's activities for the financial year 1983/84 are documented in this report. Areas documented are corporate strategy, execution of corporate strategy, management, information services, finance and staffing, Acts administered by the Minister, functions and membership of councils and committees, international trade meetings attended by departmental representatives, departmental publications, and national export award winners.

Waterpipe industry products and marketing strategies: analysis of an industry trade exhibition.

Science.gov (United States)

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/

Integrated Optimization of Bus Line Fare and Operational Strategies Using Elastic Demand

Directory of Open Access Journals (Sweden)

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.

Optimal strategy analysis based on robust predictive control for inventory system with random demand

Science.gov (United States)

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.

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...

Quantifying immediate price impact of trades based on the k-shell decomposition of stock trading networks

Science.gov (United States)

Xie, Wen-Jie; Li, Ming-Xia; Xu, Hai-Chuan; Chen, Wei; Zhou, Wei-Xing; Stanley, H. Eugene

2016-10-01

Traders in a stock market exchange stock shares and form a stock trading network. Trades at different positions of the stock trading network may contain different information. We construct stock trading networks based on the limit order book data and classify traders into k classes using the k-shell decomposition method. We investigate the influences of trading behaviors on the price impact by comparing a closed national market (A-shares) with an international market (B-shares), individuals and institutions, partially filled and filled trades, buyer-initiated and seller-initiated trades, and trades at different positions of a trading network. Institutional traders professionally use some trading strategies to reduce the price impact and individuals at the same positions in the trading network have a higher price impact than institutions. We also find that trades in the core have higher price impacts than those in the peripheral shell.

Integrated Emission Management strategy for cost-optimal engine-aftertreatment operation

NARCIS (Netherlands)

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

Endogenous Quality Effects of Trade Policy

NARCIS (Netherlands)

J.L. Moraga-Gonzalez (José Luis); J.M.A. Viaene (Jean-Marie)

1999-01-01

textabstractWe study the optimal trade policy against a foreign oligopoly with endogenous quality. We show that, under the Most Favoured Nation (MFN) clause, a uniform tariff policy is always welfare improving over the free trade equilibrium. However, a nonuniform tariff policy is always desirable

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.

Trade union revitalisation

DEFF Research Database (Denmark)

Ibsen, Christian Lyhne; Tapia, Maite

2017-01-01

In this article, we review and assess research on the role of trade unions in labour markets and society, the current decline of unions and union revitalisation. The review shows three main trends. First, trade unions are converging into similar strategies of revitalisation. The ‘organising model...... their traditional strongholds of collective bargaining and corporatist policy-making. Second, research has shown that used strategies are not a panacea for success for unions in countries that pearheaded revitalisation. This finding points to the importance of supportive institutional frameworks if unions...... in adverse institutional contexts, can be effective when they reinvent their repertoires of contention, through political action or campaigning along global value chains....

Emission trading in Europe with an exchange rate

International Nuclear Information System (INIS)

Klassen, G.A.J.; Amann, M.; Foersund, F.R.

1994-01-01

The analytical and empirical properties of a new method for emission trading according to a fixed exchange rate are explored. The exchange rate is based on the ratios of the marginal costs of abatement in the optimal solution in order to account for the impact of the location of emission sources on the deposition. It is shown that, generally, this system will not achieve the optimal solution and does not guarantee that environmental deposition constraints are not violated, although total abatement costs are always reduced. A routine was developed to mimic trading as a bilateral, sequential process, subject to an exchange rate. Use has been made of an adapted version of the optimization module in the RAINS (REgional Acidification INformation and Simulation) model. In the example used, results for SO 2 emissions in Europe show that, starting from a uniform reduction, exchange-rate trading achieves higher cost savings than one-to-one trading, without achieving the cost minimum. Sulfur deposition targets are not violated since the initial emission allocation overfulfilled targets at many places. The results are sensitive to: pre-trade emission levels, the transaction costs, the availability of information on potential cost savings and assumptions made on the behavior of trading partners. 6 figs., 3 tabs., 28 refs

Optimal Operation and Value Evaluation of Pumped Storage Power Plants Considering Spot Market Trading and Uncertainty of Bilateral Demand

Science.gov (United States)

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.

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.

Optimal Portfolio Selection Under Concave Price Impact

International Nuclear Information System (INIS)

Ma Jin; Song Qingshuo; Xu Jing; Zhang Jianfeng

2013-01-01

In this paper we study an optimal portfolio selection problem under instantaneous price impact. Based on some empirical analysis in the literature, we model such impact as a concave function of the trading size when the trading size is small. The price impact can be thought of as either a liquidity cost or a transaction cost, but the concavity nature of the cost leads to some fundamental difference from those in the existing literature. We show that the problem can be reduced to an impulse control problem, but without fixed cost, and that the value function is a viscosity solution to a special type of Quasi-Variational Inequality (QVI). We also prove directly (without using the solution to the QVI) that the optimal strategy exists and more importantly, despite the absence of a fixed cost, it is still in a “piecewise constant” form, reflecting a more practical perspective.

Optimal Portfolio Selection Under Concave Price Impact

Energy Technology Data Exchange (ETDEWEB)

Ma Jin, E-mail: jinma@usc.edu [University of Southern California, Department of Mathematics (United States); Song Qingshuo, E-mail: songe.qingshuo@cityu.edu.hk [City University of Hong Kong, Department of Mathematics (Hong Kong); Xu Jing, E-mail: xujing8023@yahoo.com.cn [Chongqing University, School of Economics and Business Administration (China); Zhang Jianfeng, E-mail: jianfenz@usc.edu [University of Southern California, Department of Mathematics (United States)

2013-06-15

In this paper we study an optimal portfolio selection problem under instantaneous price impact. Based on some empirical analysis in the literature, we model such impact as a concave function of the trading size when the trading size is small. The price impact can be thought of as either a liquidity cost or a transaction cost, but the concavity nature of the cost leads to some fundamental difference from those in the existing literature. We show that the problem can be reduced to an impulse control problem, but without fixed cost, and that the value function is a viscosity solution to a special type of Quasi-Variational Inequality (QVI). We also prove directly (without using the solution to the QVI) that the optimal strategy exists and more importantly, despite the absence of a fixed cost, it is still in a 'piecewise constant' form, reflecting a more practical perspective.

Integrated testing strategies can be optimal for chemical risk classification.

Science.gov (United States)

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.

A proposal of optimal sampling design using a modularity strategy

Science.gov (United States)

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 strategies for pricing general insurance

OpenAIRE

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...

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)

Nest site selection by Kentish plover suggests a trade-off between nest-crypsis and predator detection strategies.

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

Optimizing the number and locations of turbines in a wind farm addressing energy-noise trade-off: A hybrid approach

International Nuclear Information System (INIS)

Mittal, Prateek; Mitra, Kishalay; Kulkarni, Kedar

2017-01-01

Highlights: • Concurrent resolution of turbine number and locations during micro-siting. • Effect of noise on energy-noise multi-objective optimization is demonstrated. • A hybrid algorithm is proposed utilizing probabilistic and deterministic methods. • ∼24% improved performance is achieved over the benchmark case study. • ∼29% enhanced efficiency over real-binary genetic algorithm alone can be observed. - Abstract: Micro-siting is an optimal way of placing turbines inside a wind farm while considering various design objectives and constraints. Using a well-established Jensen wake model and ISO-9613-2 noise calculation, this study performs a wind farm layout optimization based on a multi-objective trade-off between minimization of the noise propagation and maximization of the energy generation. A novel hybrid methodology is developed which is a combination of probabilistic real-binary coded multi-objective evolutionary algorithm and a newly proposed deterministic gradient based non-dominated normalized normal constraint method. Based on the Inverted Generational Distance metric, the performance of the proposed method is found to be better than the conventional normalized normal constraint method or the concerned evolutionary method alone. Moreover, in contrast to the previous studies, the generated non-dominated front is capable of providing a trade-off between various alternative energy-noise solutions, along with an additional information about the corresponding turbine numbers and their optimal location coordinates. As a result, the decision maker can choose from different competing wind turbine layouts based on existing noise and other standard regulations.

Design principles and fundamental trade-offs in biomimetic light harvesting

International Nuclear Information System (INIS)

Sarovar, Mohan; Birgitta Whaley, K

2013-01-01

Recent developments in synthetic and supramolecular chemistry have created opportunities to design organic systems with tailored nanoscale structure for various technological applications. A key application area is the capture of light energy and its conversion into electrochemical or chemical forms for photovoltaic or sensing applications. In this work we consider cylindrical assemblies of chromophores that model structures produced by several supramolecular techniques. Our study is especially guided by the versatile structures produced by virus-templated assembly. We use a multi-objective optimization framework to determine design principles and limitations in light harvesting performance for such assemblies, both in the presence and absence of disorder. We identify a fundamental trade-off in cylindrical assemblies that is encountered when attempting to maximize both efficiency of energy transfer and absorption bandwidth. We also rationalize the optimal design strategies and provide explanations for why various structures provide optimal performance. Most importantly, we find that the optimal design strategies depend on the amount of energetic and structural disorder in the system. The aim of these studies is to develop a program of quantum-informed rational design for construction of organic assemblies that have the same degree of tailored nanoscale structure as biological photosynthetic light harvesting complexes, and consequently have the potential to reproduce their remarkable light harvesting performance. (paper)

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.

An Efficient Algorithm for the Optimal Market Timing over Two Stocks

Institute of Scientific and Technical Information of China (English)

Hui Li; Hong-zhi An; Guo-fu Wu

2004-01-01

In this paper,the optimal trading strategy in timing the market by switching between two stocks is given.In order to deal with a large sample size with a fast turnaround computation time,we propose a class of recursive algorithm.A simulation is given to verify the efiectiveness of our method.

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...

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

Modelling and Optimal Control of Typhoid Fever Disease with Cost-Effective Strategies.

Science.gov (United States)

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.

Control strategies for wind farm power optimization: LES study

Science.gov (United States)

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.

Optimal football strategies: AC Milan versus FC Barcelona

OpenAIRE

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.

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.

Stability Analysis and Optimal Control Strategy for Prevention of Pine Wilt Disease

Directory of Open Access Journals (Sweden)

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.

Applications of Classifying Bidding Strategies for the CAT Tournament

Science.gov (United States)

Gruman, Mark L.; Narayana, Manjunath

In the CAT Tournament, specialists facilitate transactions between buyers and sellers with the intention of maximizing profit from commission and other fees. Each specialist must find a well-balanced strategy that allows it to entice buyers and sellers to trade in its market while also retaining the buyers and sellers that are currently subscribed to it. Classification techniques can be used to determine the distribution of bidding strategies used by all traders subscribed to a particular specialist. Our experiments showed that Hidden Markov Model classification yielded the best results. The distribution of strategies, along with other competition-related factors, can be used to determine the optimal action in any given game state. Experimental data shows that the GD and ZIP bidding strategies are more volatile than the RE and ZIC strategies. An MDP framework for determining optimal actions given an accurate distribution of bidding strategies is proposed as a motivator for future work.

Regional Trade Integration and Conflict Resolution

International Development Research Centre (IDRC) Digital Library (Canada)

9 Trading across the Straits: will a free trade agreement between China and Taiwan .... Moeed Yusuf is a consultant on Economic Policy at the SDPI, Islamabad, ...... In the tourism sector, joint marketing and management strategies could bring ...

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.

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).

Optimal robust control strategy of a solid oxide fuel cell system

Science.gov (United States)

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.

Optimal replenishment and credit policy in supply chain inventory model under two levels of trade credit with time- and credit-sensitive demand involving default risk

Science.gov (United States)

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 allocation of physical water resources integrated with virtual water trade in water scarce regions: A case study for Beijing, China.

Science.gov (United States)

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

Upon a Message-Oriented Trading API

Directory of Open Access Journals (Sweden)

Claudiu VINTE

2010-01-01

Full Text Available In this paper, we introduce the premises for a trading system application-programming interface (API based on a message-oriented middleware (MOM, and present the results of our research regarding the design and the implementation of a simulation-trading system employing a service-oriented architecture (SOA and messaging. Our research has been conducted with the aim of creating a simulation-trading platform, within the academic environment, that will provide both the foundation for future experiments with trading systems architectures, components, APIs, and the framework for research on trading strategies, trading algorithm design, and equity markets analysis tools. Mathematics Subject Classification: 68M14 (distributed systems.

Implementation of an optimal control energy management strategy in a hybrid truck

NARCIS (Netherlands)

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

Asset Prices and Trading Volume under Fixed Transactions Costs.

Science.gov (United States)

Lo, Andrew W.; Mamaysky, Harry; Wang, Jiang

2004-01-01

We propose a dynamic equilibrium model of asset prices and trading volume when agents face fixed transactions costs. We show that even small fixed costs can give rise to large "no-trade" regions for each agent's optimal trading policy. The inability to trade more frequently reduces the agents' asset demand and in equilibrium gives rise to a…

An Optimal Operating Strategy for Battery Life Cycle Costs in Electric Vehicles

Directory of Open Access Journals (Sweden)

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.

Are the Economically Optimal Harvesting Strategies of Uneven-Aged Pinus nigra Stands Always Sustainable and Stabilizing?

Directory of Open Access Journals (Sweden)

Carmen Fullana-Belda

2013-10-01

Full Text Available Traditional uneven-aged forest management seeks a balance between equilibrium stand structure and economic profitability, which often leads to harvesting strategies concentrated in the larger diameter classes. The sustainability (i.e., population persistence over time and influence of such economically optimal strategies on the equilibrium position of a stand (given by the stable diameter distribution have not been sufficiently investigated in prior forest literature. This article therefore proposes a discrete optimal control model to analyze the sustainability and stability of the economically optimal harvesting strategies of uneven-aged Pinus nigra stands. For this model, we rely on an objective function that integrates financial data of harvesting operations with a projection matrix model that can describe the population dynamics. The model solution reveals the optimal management schedules for a wide variety of scenarios. To measure the distance between the stable diameter distribution and the economically optimal harvesting strategy distribution, the model uses Keyfitz’s delta, which returns high values for all the scenarios and, thus, suggests that those economically optimal harvesting strategies have an unstabilizing influence on the equilibrium positions. Moreover, the economically optimal harvesting strategies were unsustainable for all the scenarios.

Modern trends of electronic trading by negotiable financial instruments

Directory of Open Access Journals (Sweden)

I.Kravchuk

2018-03-01

Full Text Available International negotiable financial instrument markets have a high level of electronic trading. It is displayed using the consolidated limit order book, the widening the range of trading orders, smart order routing, high speed access to the market on the basis of latency minimizing. The result of electronic trading is the development of high-frequency trading, the positive features of which are the increase of trading activity and market liquidity, and the reducing of transaction costs. The main drawback of high-frequency trading is the potential negative impact on market stability (software failures, the manipulative incentives of algorithmic strategies, in particular, technical arbitrage, the use of homogeneous strategies, cyber risks. The current system of high-frequency trading requires particular actions from the regulators to overcome information gaps and enhanced monitoring to create a regulatory environment that could take into account both the aspects of supporting market development and its stability through appropriate macroprudential instruments, especially the implementation of the stress testing of the high-frequency algorithms in response to the shocks of various origin, taking into account the aggregate market effect of the mutual influence of different algorithmic strategies.

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...

A Parameter Communication Optimization Strategy for Distributed Machine Learning in Sensors.

Science.gov (United States)

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.

Transboundary Pollution, Trade Liberalization and Environmental Taxes

NARCIS (Netherlands)

Baksi, S.; Ray Chaudhuri, A.

2008-01-01

In a bilateral trade framework, we examine the impact of tariff reduction on the optimal pollution tax and social welfare when pollution is transboundary. Strategic considerations lead countries to distort their pollution tax in the non-cooperative equilibrium. Trade liberalization changes the

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...

Optimal Claiming Strategies in Bonus Malus Systems and Implied Markov Chains

Directory of Open Access Journals (Sweden)

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.

Supply Chain Coordination with Carbon Trading Price and Consumers’ Environmental Awareness Dependent Demand

Directory of Open Access Journals (Sweden)

Qinghua Pang

2018-01-01

Full Text Available Carbon emissions reduction in supply chain is an effective method to reduce the greenhouse effect. The paper investigates the impacts of carbon trading price and consumers’ environmental awareness on carbon emissions in supply chain under the cap-and-trade system. Firstly, it analyzes the centralized decision structure and obtains the requirements to coordinate carbon emissions reduction and order quantity in supply chain. Secondly, it proposes the supply chain coordination mechanism with revenue-sharing contract based on quantity discount policy, and the requirements that the contract parameters need to satisfy are also given. Thirdly, assuming the market demand is affected by consumer’s environmental awareness in addition form, the paper proposes the methods to determine the optimal order quantity and the optimal level of carbon emissions through model optimization. Finally, it investigates the impacts of carbon trading price on carbon emissions in supply chain. The results show that clean manufacturer’s optimal per-unit carbon emissions increase as the carbon trading price increases, while nongreen manufacturer’s optimal per-unit carbon emissions decrease as the carbon trading price increases. For the middle emissions manufacturer, the optimal per-unit carbon emissions depend on the relationship between the carbon trading price and the carbon reduction coefficient.

Sustainable Trade Credit and Replenishment Policies under the Cap-And-Trade and Carbon Tax Regulations

Directory of Open Access Journals (Sweden)

Juanjuan Qin

2015-12-01

Full Text Available The paper considers the sustainable trade credit and inventory policies with demand related to credit period and the environmental sensitivity of consumers under the carbon cap-and-trade and carbon tax regulations. First, the decision models are constructed under three cases: without regulation, carbon cap-and-trade regulation, and carbon tax regulation. The optimal solutions of the retailer in the three cases are then discussed under the exogenous and endogenous credit periods. Finally, numerical analysis is conducted to obtain conclusions. The retailer shortens the trade credit period as the environmental sensitivity of the consumer is enhanced. The cap has no effects on the credit period decisions under the carbon cap-and-trade regulation. Carbon trade price and carbon tax have negative effects on the credit period. The retailer under carbon cap-and-trade regulation is more motivated to obey regulations than that under carbon tax regulation when carbon trade price equals carbon tax. Carbon regulations have better effects on carbon emission reduction than with exogenous credit term when the retailer has the power to decide with regards credit policies.

Search Improvement Process-Chaotic Optimization-Particle Swarm Optimization-Elite Retention Strategy and Improved Combined Cooling-Heating-Power Strategy Based Two-Time Scale Multi-Objective Optimization Model for Stand-Alone Microgrid Operation

Directory of Open Access Journals (Sweden)

Fei Wang

2017-11-01

Full Text Available The optimal dispatching model for a stand-alone microgrid (MG is of great importance to its operation reliability and economy. This paper aims at addressing the difficulties in improving the operational economy and maintaining the power balance under uncertain load demand and renewable generation, which could be even worse in such abnormal conditions as storms or abnormally low or high temperatures. A new two-time scale multi-objective optimization model, including day-ahead cursory scheduling and real-time scheduling for finer adjustments, is proposed to optimize the operational cost, load shedding compensation and environmental benefit of stand-alone MG through controllable load (CL and multi-distributed generations (DGs. The main novelty of the proposed model is that the synergetic response of CL and energy storage system (ESS in real-time scheduling offset the operation uncertainty quickly. And the improved dispatch strategy for combined cooling-heating-power (CCHP enhanced the system economy while the comfort is guaranteed. An improved algorithm, Search Improvement Process-Chaotic Optimization-Particle Swarm Optimization-Elite Retention Strategy (SIP-CO-PSO-ERS algorithm with strong searching capability and fast convergence speed, was presented to deal with the problem brought by the increased errors between actual renewable generation and load and prior predictions. Four typical scenarios are designed according to the combinations of day types (work day or weekend and weather categories (sunny or rainy to verify the performance of the presented dispatch strategy. The simulation results show that the proposed two-time scale model and SIP-CO-PSO-ERS algorithm exhibit better performance in adaptability, convergence speed and search ability than conventional methods for the stand-alone MG’s operation.

A guide to multi-objective optimization for ecological problems with an application to cackling goose management

Science.gov (United States)

Williams, Perry J.; Kendall, William L.

2017-01-01

Choices in ecological research and management are the result of balancing multiple, often competing, objectives. Multi-objective optimization (MOO) is a formal decision-theoretic framework for solving multiple objective problems. MOO is used extensively in other fields including engineering, economics, and operations research. However, its application for solving ecological problems has been sparse, perhaps due to a lack of widespread understanding. Thus, our objective was to provide an accessible primer on MOO, including a review of methods common in other fields, a review of their application in ecology, and a demonstration to an applied resource management problem.A large class of methods for solving MOO problems can be separated into two strategies: modelling preferences pre-optimization (the a priori strategy), or modelling preferences post-optimization (the a posteriori strategy). The a priori strategy requires describing preferences among objectives without knowledge of how preferences affect the resulting decision. In the a posteriori strategy, the decision maker simultaneously considers a set of solutions (the Pareto optimal set) and makes a choice based on the trade-offs observed in the set. We describe several methods for modelling preferences pre-optimization, including: the bounded objective function method, the lexicographic method, and the weighted-sum method. We discuss modelling preferences post-optimization through examination of the Pareto optimal set. We applied each MOO strategy to the natural resource management problem of selecting a population target for cackling goose (Branta hutchinsii minima) abundance. Cackling geese provide food security to Native Alaskan subsistence hunters in the goose's nesting area, but depredate crops on private agricultural fields in wintering areas. We developed objective functions to represent the competing objectives related to the cackling goose population target and identified an optimal solution

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 contract for a fund manager, with capital injections and endogenous trading constraints

OpenAIRE

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. ...

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.

Harmonic Patterns in Forex Trading

OpenAIRE

Nemček, Sebastian

2013-01-01

This diploma thesis is committed to examination of validity of Harmonic Patterns in Forex trading. Scott Carney described existing and introduced new Harmonic Patterns in 1999 in his book Harmonic Trader. These patterns use the Fibonacci principle to analyze price action and to provide both bullish and bearish trading signals. The goal of this thesis is to find out whether harmonic trading strategy on selected pairs is profitable in FX market, which patterns are the most profitable and what i...

Optimal Control and Operation Strategy for Wind Turbines Contributing to Grid Primary Frequency Regulation

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.

Strategies for sustainable management of renewable resources during environmental change.

Science.gov (United States)

Lindkvist, Emilie; Ekeberg, Örjan; Norberg, Jon

2017-03-15

As a consequence of global environmental change, management strategies that can deal with unexpected change in resource dynamics are becoming increasingly important. In this paper we undertake a novel approach to studying resource growth problems using a computational form of adaptive management to find optimal strategies for prevalent natural resource management dilemmas. We scrutinize adaptive management, or learning-by-doing, to better understand how to simultaneously manage and learn about a system when its dynamics are unknown. We study important trade-offs in decision-making with respect to choosing optimal actions (harvest efforts) for sustainable management during change. This is operationalized through an artificially intelligent model where we analyze how different trends and fluctuations in growth rates of a renewable resource affect the performance of different management strategies. Our results show that the optimal strategy for managing resources with declining growth is capable of managing resources with fluctuating or increasing growth at a negligible cost, creating in a management strategy that is both efficient and robust towards future unknown changes. To obtain this strategy, adaptive management should strive for: high learning rates to new knowledge, high valuation of future outcomes and modest exploration around what is perceived as the optimal action. © 2017 The Author(s).

Online gaming for learning optimal team strategies in real time

Science.gov (United States)

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.

Quantified moving average strategy of crude oil futures market based on fuzzy logic rules and genetic algorithms

Science.gov (United States)

Liu, Xiaojia; An, Haizhong; Wang, Lijun; Guan, Qing

2017-09-01

The moving average strategy is a technical indicator that can generate trading signals to assist investment. While the trading signals tell the traders timing to buy or sell, the moving average cannot tell the trading volume, which is a crucial factor for investment. This paper proposes a fuzzy moving average strategy, in which the fuzzy logic rule is used to determine the strength of trading signals, i.e., the trading volume. To compose one fuzzy logic rule, we use four types of moving averages, the length of the moving average period, the fuzzy extent, and the recommend value. Ten fuzzy logic rules form a fuzzy set, which generates a rating level that decides the trading volume. In this process, we apply genetic algorithms to identify an optimal fuzzy logic rule set and utilize crude oil futures prices from the New York Mercantile Exchange (NYMEX) as the experiment data. Each experiment is repeated for 20 times. The results show that firstly the fuzzy moving average strategy can obtain a more stable rate of return than the moving average strategies. Secondly, holding amounts series is highly sensitive to price series. Thirdly, simple moving average methods are more efficient. Lastly, the fuzzy extents of extremely low, high, and very high are more popular. These results are helpful in investment decisions.

Enforcement of emissions trading: Sanction regimes of greenhouse gas emissions trading in the EU and China

NARCIS (Netherlands)

Peeters, M.G.W.M.; Chen, Huizhen

2015-01-01

Abstract: This chapter aims to further the debate regarding the role of law for establishing an adequate enforcement strategy for an emissions trading scheme. We focus on sanction regimes within the EU ETS and the Chinese emissions trading pilot projects. Section 2 sets the scene by pointing at the

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 ...

Identifying optimum performance trade-offs using a cognitively bounded rational analysis model of discretionary task interleaving.

Science.gov (United States)

Janssen, Christian P; Brumby, Duncan P; Dowell, John; Chater, Nick; Howes, Andrew

2011-01-01

We report the results of a dual-task study in which participants performed a tracking and typing task under various experimental conditions. An objective payoff function was used to provide explicit feedback on how participants should trade off performance between the tasks. Results show that participants' dual-task interleaving strategy was sensitive to changes in the difficulty of the tracking task and resulted in differences in overall task performance. To test the hypothesis that people select strategies that maximize payoff, a Cognitively Bounded Rational Analysis model was developed. This analysis evaluated a variety of dual-task interleaving strategies to identify the optimal strategy for maximizing payoff in each condition. The model predicts that the region of optimum performance is different between experimental conditions. The correspondence between human data and the prediction of the optimal strategy is found to be remarkably high across a number of performance measures. This suggests that participants were honing their behavior to maximize payoff. Limitations are discussed. Copyright © 2011 Cognitive Science Society, Inc.

Multi-infill strategy for kriging models used in variable fidelity optimization

Directory of Open Access Journals (Sweden)

Chao SONG

2018-03-01

Full Text Available In this paper, a computationally efficient optimization method for aerodynamic design has been developed. The low-fidelity model and the multi-infill strategy are utilized in this approach. Low-fidelity data is employed to provide a good global trend for model prediction, and multiple sample points chosen by different infill criteria in each updating cycle are used to enhance the exploitation and exploration ability of the optimization approach. Take the advantages of low-fidelity model and the multi-infill strategy, and no initial sample for the high-fidelity model is needed. This approach is applied to an airfoil design case and a high-dimensional wing design case. It saves a large number of high-fidelity function evaluations for initial model construction. What’s more, faster reduction of an aerodynamic function is achieved, when compared to ordinary kriging using the multi-infill strategy and variable-fidelity model using single infill criterion. The results indicate that the developed approach has a promising application to efficient aerodynamic design when high-fidelity analyses are involved. Keywords: Aerodynamics, Infill criteria, Kriging models, Multi-infill, Optimization

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.

Enforcement of emissions trading - sanction regimes of greenhouse gas emissions trading in the EU and China

NARCIS (Netherlands)

Peeters, Marjan; Chen, Huizhen; Weishaar, Stefan

2016-01-01

This chapter aims to further the debate regarding the role of law for establishing an adequate enforcement strategy for an emissions trading scheme. We focus on sanction regimes within the EU ETS and the Chinese emissions trading pilot projects. Section 2 sets the scene by pointing at the need of an

Livestock Disease Management for Trading Across Different Regulatory Regimes.

Science.gov (United States)

Bate, Andrew M; Jones, Glyn; Kleczkowski, Adam; Naylor, Rebecca; Timmis, Jon; White, Piran C L; Touza, Julia

2018-02-12

The maintenance of livestock health depends on the combined actions of many different actors, both within and across different regulatory frameworks. Prior work recognised that private risk management choices have the ability to reduce the spread of infection to trading partners. We evaluate the efficiency of farmers' alternative biosecurity choices in terms of their own-benefits from unilateral strategies and quantify the impact they may have in filtering the disease externality of trade. We use bovine viral diarrhoea (BVD) in England and Scotland as a case study, since this provides an example of a situation where contrasting strategies for BVD management occur between selling and purchasing farms. We use an agent-based bioeconomic model to assess the payoff dependence of farmers connected by trade but using different BVD management strategies. We compare three disease management actions: test-cull, test-cull with vaccination and vaccination alone. For a two-farm trading situation, all actions carried out by the selling farm provide substantial benefits to the purchasing farm in terms of disease avoided, with the greatest benefit resulting from test-culling with vaccination on the selling farm. Likewise, unilateral disease strategies by purchasers can be effective in reducing disease risks created through trade. We conclude that regulation needs to balance the trade-off between private gains from those bearing the disease management costs and the positive spillover effects on others.

Long-term damage management strategies for optimizing steam generator performance

International Nuclear Information System (INIS)

Egan, G.R.; Besuner, P.M.; Fox, J.H.; Merrick, E.A.

1991-01-01

Minimizing long-term impact of steam generator operating, maintenance, outage, and replacement costs is the goal of all pressurized water reactor utilities. Recent research results have led to deterministic controls that may be implemented to optimize steam generator performance and to minimize damage accumulation. The real dilemma that utilities encounter is the decision process that needs to be made in the face of uncertain data. Some of these decisions involve the frequency and extent of steam generator eddy current tube inspections; the definition of operating conditions to minimize the rate of corrosion reactions (T (hot) , T (cold) ; and the imposition of strict water quality management guidelines. With finite resources, how can a utility decide which damage management strategy provides the most return for its investment? Aptech Engineering Services, Inc. (APTECH) developed a damage management strategy that starts from a deterministic analysis of a current problem- primary water stress corrosion cracking (PWSCC). The strategy involves a probabilistic treatment that results in long-term performance optimization. By optimization, we refer to minimizing the total cost of operating the steam generator. This total includes the present value costs of operations, maintenance, outages, and replacements. An example of the application of this methodology is presented. (author)

Optimization of Key Parameters of Energy Management Strategy for Hybrid Electric Vehicle Using DIRECT Algorithm

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.

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

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

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.

A buffer material optimal design in the radioactive wastes geological disposal using the satisficing trade-off method and the self-organizing map

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)

A new inertia weight control strategy for particle swarm optimization

Science.gov (United States)

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.

Research and International Trade Policy Negotiations: Knowledge ...

International Development Research Centre (IDRC) Digital Library (Canada)

2009-10-07

Oct 7, 2009 ... ... pillar of Latin America's development strategy into the 21st century. ... and policy advisors involved in trade negotiations and the formulation of trade policy. ... Expanding women's financial inclusion: A win-win for women and ...

Establishment of an immortalized mouse dermal papilla cell strain with optimized culture strategy

Directory of Open Access Journals (Sweden)

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.

Optimal bidding strategies in oligopoly markets considering bilateral contracts and transmission constraints

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 bidding strategies in oligopoly markets considering bilateral contracts and transmission constraints

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)

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.

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.

Optimal trade-credit policy for perishable items deeming imperfect production and stock dependent demand

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.

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.

Optimal Switching Control of Burner Setting for a Compact Marine Boiler Design

DEFF Research Database (Denmark)

Solberg, Brian; Andersen, Palle; Maciejowski, Jan M.

2010-01-01

This paper discusses optimal control strategies for switching between different burner modes in a novel compact  marine boiler design. The ideal behaviour is defined in a performance index the minimisation of which defines an ideal trade-off between deviations in boiler pressure and water level...... approach is based on a generalisation of hysteresis control. The strategies are verified on a simulation model of the compact marine boiler for control of low/high burner load switches.  ...

Web malware spread modelling and optimal control strategies

Science.gov (United States)

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.

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.

Optimization strategies based on sequential quadratic programming applied for a fermentation process for butanol production.

Science.gov (United States)

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.

Exploring optimal fertigation strategies for orange production, using soil-crop modelling

NARCIS (Netherlands)

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

A cognitive decision agent architecture for optimal energy management of microgrids

International Nuclear Information System (INIS)

Velik, Rosemarie; Nicolay, Pascal

2014-01-01

Highlights: • We propose an optimization approach for energy management in microgrids. • The optimizer emulates processes involved in human decision making. • Optimization objectives are energy self-consumption and financial gain maximization. • We gain improved optimization results in significantly reduced computation time. - Abstract: Via the integration of renewable energy and storage technologies, buildings have started to change from passive (electricity) consumers to active prosumer microgrids. Along with this development come a shift from centralized to distributed production and consumption models as well as discussions about the introduction of variable demand–supply-driven grid electricity prices. Together with upcoming ICT and automation technologies, these developments open space to a wide range of novel energy management and energy trading possibilities to optimally use available energy resources. However, what is considered as an optimal energy management and trading strategy heavily depends on the individual objectives and needs of a microgrid operator. Accordingly, elaborating the most suitable strategy for each particular system configuration and operator need can become quite a complex and time-consuming task, which can massively benefit from computational support. In this article, we introduce a bio-inspired cognitive decision agent architecture for optimized, goal-specific energy management in (interconnected) microgrids, which are additionally connected to the main electricity grid. For evaluating the performance of the architecture, a number of test cases are specified targeting objectives like local photovoltaic energy consumption maximization and financial gain maximization. Obtained outcomes are compared against a modified simulating annealing optimization approach in terms of objective achievement and computational effort. Results demonstrate that the cognitive decision agent architecture yields improved optimization results in

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

Biclustering Learning of Trading Rules.

Science.gov (United States)

Huang, Qinghua; Wang, Ting; Tao, Dacheng; Li, Xuelong

2015-10-01

Technical analysis with numerous indicators and patterns has been regarded as important evidence for making trading decisions in financial markets. However, it is extremely difficult for investors to find useful trading rules based on numerous technical indicators. This paper innovatively proposes the use of biclustering mining to discover effective technical trading patterns that contain a combination of indicators from historical financial data series. This is the first attempt to use biclustering algorithm on trading data. The mined patterns are regarded as trading rules and can be classified as three trading actions (i.e., the buy, the sell, and no-action signals) with respect to the maximum support. A modified K nearest neighborhood ( K -NN) method is applied to classification of trading days in the testing period. The proposed method [called biclustering algorithm and the K nearest neighbor (BIC- K -NN)] was implemented on four historical datasets and the average performance was compared with the conventional buy-and-hold strategy and three previously reported intelligent trading systems. Experimental results demonstrate that the proposed trading system outperforms its counterparts and will be useful for investment in various financial markets.

Egg number-egg size: an important trade-off in parasite life history strategies.

Science.gov (United States)

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

Optimal intervention strategies for cholera outbreak by education and chlorination

Science.gov (United States)

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.

Effective Strategy Formation Models for Inventory Management under the Conditions of Uncertainty

Science.gov (United States)

Kosorukov, Oleg Anatolyevich; Sviridova, Olga Alexandrovna

2015-01-01

The article deals with the problem of modeling the commodity flows management of a trading company under the conditions of uncertain demand and long supply. The Author presents an analysis of modifications of diversified inventory management system with random demand, for which one can find the optimal inventory control strategies, including those…

Changes in the business model for Spanish fresh tomato trade

International Nuclear Information System (INIS)

Pablo-Valenciano, J. de; Giacinti-Battistuzzi, M.A.; Tassile, T.; García-Azcárate, T.

2017-01-01

The business model applied to the fresh tomato trade from Almería is well known in Spain and abroad. The changes in demand are forcing export companies to change their trade strategies to become or remain competitive. The purpose of this paper is to know the business structure and its export dynamics in addition to the changes in trade strategies made by companies in Almería during the 2009-2013 period. The methodology is based on the Herfindahl-Hirshman index and the foreign trade competitiveness index, whereas the congruence analysis is based on Pearson’s correlation coefficients and the RV coefficient. We have also applied the dual multiple factor analysis to verify changes made to the trade policy in leading businesses between two periods or scenarios. The research shows that export-driven companies behave as a moderately concentrated structure and there is an increase in the number of exporters. The competitiveness map for Almería reveals the sector’s trend with regard to the most important markets. We have verified the changes made to their trade strategy to adjust to changes in foreign trade between the 2008/09 and 2012/13 campaigns. Finally, it can be pointed out that, in the analyzed period, changes in the business model for fresh tomato trade of Almería have not been significant, being its structure of moderate concentration. In addition, the great majority of variations in strategies of companies to adapt to the competitive environment have been made by leading companies.

Changes in the business model for Spanish fresh tomato trade

Energy Technology Data Exchange (ETDEWEB)

Pablo-Valenciano, J. de; Giacinti-Battistuzzi, M.A.; Tassile, T.; García-Azcárate, T.

2017-09-01

The business model applied to the fresh tomato trade from Almería is well known in Spain and abroad. The changes in demand are forcing export companies to change their trade strategies to become or remain competitive. The purpose of this paper is to know the business structure and its export dynamics in addition to the changes in trade strategies made by companies in Almería during the 2009-2013 period. The methodology is based on the Herfindahl-Hirshman index and the foreign trade competitiveness index, whereas the congruence analysis is based on Pearson’s correlation coefficients and the RV coefficient. We have also applied the dual multiple factor analysis to verify changes made to the trade policy in leading businesses between two periods or scenarios. The research shows that export-driven companies behave as a moderately concentrated structure and there is an increase in the number of exporters. The competitiveness map for Almería reveals the sector’s trend with regard to the most important markets. We have verified the changes made to their trade strategy to adjust to changes in foreign trade between the 2008/09 and 2012/13 campaigns. Finally, it can be pointed out that, in the analyzed period, changes in the business model for fresh tomato trade of Almería have not been significant, being its structure of moderate concentration. In addition, the great majority of variations in strategies of companies to adapt to the competitive environment have been made by leading companies.

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.

Optimizing the control of foot-and-mouth disease in Denmark by simulation – the project outline

DEFF Research Database (Denmark)

Enøe, Claes

2012-01-01

. These control options included different options for emergency vaccination, zoning and culling. Optimal control/eradication strategies was evaluated based on costs, number of culled animals, epidemic duration and time to lift of restrictions on animal movements and trade. An important part of the project...

TRADING RULES ON A SMALL STOCK MARKET

Directory of Open Access Journals (Sweden)

Stefán B. Gunnlaugsson

2018-03-01

Full Text Available In this article, the results of an extensive study of the weak form efficiency of the Iceland stock market are presented. This study almost covers the market’s entire history, with the research starting at the beginning of 1993 and ending in July 2017. Four trading rules based on 70-day moving averages were constructed and compared with the passive investment strategy of buying the market index. All of these trading rules provided significantly better returns than the passive strategy, even when considering trading costs. This result indicates that the Icelandic stock market did not show weak form efficiency, and past returns predicted future returns during the period examined.

Initiative Optimization Operation Strategy and Multi-objective Energy Management Method for Combined Cooling Heating and Power

Institute of Scientific and Technical Information of China (English)

Feng Zhao; Chenghui Zhang; Bo Sun

2016-01-01

This paper proposed an initiative optimization operation strategy and multi-objective energy management method for combined cooling heating and power(CCHP) with storage systems.Initially,the initiative optimization operation strategy of CCHP system in the cooling season,the heating season and the transition season was formulated.The energy management of CCHP system was optimized by the multi-objective optimization model with maximum daily energy efficiency,minimum daily carbon emissions and minimum daily operation cost based on the proposed initiative optimization operation strategy.Furthermore,the pareto optimal solution set was solved by using the niche particle swarm multi-objective optimization algorithm.Ultimately,the most satisfactory energy management scheme was obtained by using the technique for order preference by similarity to ideal solution(TOPSIS) method.A case study of CCHP system used in a hospital in the north of China validated the effectiveness of this method.The results showed that the satisfactory energy management scheme of CCHP system was obtained based on this initiative optimization operation strategy and multi-objective energy management method.The CCHP system has achieved better energy efficiency,environmental protection and economic benefits.

Closed-loop optimization of chromatography column sizing strategies in biopharmaceutical manufacture.

Science.gov (United States)

Allmendinger, Richard; Simaria, Ana S; Turner, Richard; Farid, Suzanne S

2014-10-01

This paper considers a real-world optimization problem involving the identification of cost-effective equipment sizing strategies for the sequence of chromatography steps employed to purify biopharmaceuticals. Tackling this problem requires solving a combinatorial optimization problem subject to multiple constraints, uncertain parameters, and time-consuming fitness evaluations. An industrially-relevant case study is used to illustrate that evolutionary algorithms can identify chromatography sizing strategies with significant improvements in performance criteria related to process cost, time and product waste over the base case. The results demonstrate also that evolutionary algorithms perform best when infeasible solutions are repaired intelligently, the population size is set appropriately, and elitism is combined with a low number of Monte Carlo trials (needed to account for uncertainty). Adopting this setup turns out to be more important for scenarios where less time is available for the purification process. Finally, a data-visualization tool is employed to illustrate how user preferences can be accounted for when it comes to selecting a sizing strategy to be implemented in a real industrial setting. This work demonstrates that closed-loop evolutionary optimization, when tuned properly and combined with a detailed manufacturing cost model, acts as a powerful decisional tool for the identification of cost-effective purification strategies. © 2013 The Authors. Journal of Chemical Technology & Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Game Analysis and Simulation of the River Basin Sustainable Development Strategy Integrating Water Emission Trading

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.

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.

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

Scheduling and Optimization of Fault-Tolerant Embedded Systems with Transparency/Performance Trade-Offs

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....

An Optimal Investment Strategy and Multiperiod Deposit Insurance Pricing Model for Commercial Banks

Directory of Open Access Journals (Sweden)

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.

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 Battery Utilization Over Lifetime for Parallel Hybrid Electric Vehicle to Maximize Fuel Economy

Energy Technology Data Exchange (ETDEWEB)

Patil, Chinmaya; Naghshtabrizi, Payam; Verma, Rajeev; Tang, Zhijun; Smith, Kandler; Shi, Ying

2016-08-01

This paper presents a control strategy to maximize fuel economy of a parallel hybrid electric vehicle over a target life of the battery. Many approaches to maximizing fuel economy of parallel hybrid electric vehicle do not consider the effect of control strategy on the life of the battery. This leads to an oversized and underutilized battery. There is a trade-off between how aggressively to use and 'consume' the battery versus to use the engine and consume fuel. The proposed approach addresses this trade-off by exploiting the differences in the fast dynamics of vehicle power management and slow dynamics of battery aging. The control strategy is separated into two parts, (1) Predictive Battery Management (PBM), and (2) Predictive Power Management (PPM). PBM is the higher level control with slow update rate, e.g. once per month, responsible for generating optimal set points for PPM. The considered set points in this paper are the battery power limits and State Of Charge (SOC). The problem of finding the optimal set points over the target battery life that minimize engine fuel consumption is solved using dynamic programming. PPM is the lower level control with high update rate, e.g. a second, responsible for generating the optimal HEV energy management controls and is implemented using model predictive control approach. The PPM objective is to find the engine and battery power commands to achieve the best fuel economy given the battery power and SOC constraints imposed by PBM. Simulation results with a medium duty commercial hybrid electric vehicle and the proposed two-level hierarchical control strategy show that the HEV fuel economy is maximized while meeting a specified target battery life. On the other hand, the optimal unconstrained control strategy achieves marginally higher fuel economy, but fails to meet the target battery life.

Impact of information cost and switching of trading strategies in an artificial stock market

Science.gov (United States)

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.

Optimization of pocket machining strategy in HSM

OpenAIRE

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 operation strategies of compressed air energy storage (CAES) on electricity spot markets with fluctuating prices

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...

76 FR 15294 - Export Trade Certificate of Review

Science.gov (United States)

2011-03-21

... information on trade opportunities; marketing; negotiations; joint ventures; shipping; export management; export licensing; advertising; documentation and services related to compliance with customs requirements; insurance and financing; trade show exhibitions; organizational development; management and labor strategies...

75 FR 44760 - Export Trade Certificate of Review

Science.gov (United States)

2010-07-29

... information on trade opportunities; marketing; negotiations; joint ventures; shipping; export management; export licensing; advertising; documentation and services related to compliance with customs requirements; insurance and financing; trade show exhibitions; organizational development; management and labor strategies...

Loss-minimal Algorithmic Trading Based on Levy Processes

Directory of Open Access Journals (Sweden)

Farhad Kia

2014-08-01

Full Text Available In this paper we optimize portfolios assuming that the value of the portfolio follows a Lévy process. First we identify the parameters of the underlying Lévy process and then portfolio optimization is performed by maximizing the probability of positive return. The method has been tested by extensive performance analysis on Forex and SP 500 historical time series. The proposed trading algorithm has achieved 4.9\\% percent yearly return on average without leverage which proves its applicability to algorithmic trading.

Child Labor and Trade Liberalization in Indonesia

NARCIS (Netherlands)

K.K. Krisztina (Kis-Katos); R.A. Sparrow (Robert)

2009-01-01

textabstractWe examine the effects of trade liberalization on child work in Indonesia. Our estimation strategy identifies geographical differences in the effects of trade policy through district level exposure to reduction in import tariff barriers. We use a balanced panel of 261 districts, based

Optimal allocation of trend following strategies

Science.gov (United States)

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.

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...

Trade-offs between forest carbon stocks and harvests in a steady state - A multi-criteria analysis.

Science.gov (United States)

Pingoud, Kim; Ekholm, Tommi; Sievänen, Risto; Huuskonen, Saija; Hynynen, Jari

2018-03-15

This paper provides a perspective for comparing trade-offs between harvested wood flows and forest carbon stocks with different forest management regimes. A constant management regime applied to a forest area with an even age-class distribution leads to a steady state, in which the annual harvest and carbon stocks remain constant over time. As both are desirable - carbon stocks for mitigating climate change and harvests for the economic use of wood and displacing fossil fuels - an ideal strategy should be chosen from a set of management regimes that are Pareto-optimal in the sense of multi-criteria decision-making. When choosing between Pareto-optimal alternatives, the trade-off between carbon stock and harvests is unavoidable. This trade-off can be described e.g. in terms of carbon payback times or carbon returns. As numerical examples, we present steady-state harvest levels and carbon stocks in a Finnish boreal forest region for different rotation periods, thinning intensities and collection patterns for harvest residues. In the set of simulated management practices, harvest residue collection presents the most favorable trade-off with payback times around 30-40 years; while Pareto-optimal changes in rotation or thinnings exhibited payback times over 100 years, or alternatively carbon returns below 1%. By extending the rotation period and using less-intensive thinnings compared to current practices, the steady-state carbon stocks could be increased by half while maintaining current harvest levels. Additional cases with longer rotation periods should be also considered, but were here excluded due to the lack of reliable data on older forest stands. Copyright © 2018 Elsevier Ltd. All rights reserved.

Issues and Strategies in Solving Multidisciplinary Optimization Problems

Science.gov (United States)

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

Improving the automated optimization of profile extrusion dies by applying appropriate optimization areas and strategies

Science.gov (United States)

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.

Portfolio optimization using Mixture Design of Experiments. Scheduling trades within electricity markets

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)

Portfolio optimization using Mixture Design of Experiments. Scheduling trades within electricity markets

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)

Control strategy of maximum vertical jumps: The preferred countermovement depth may not be fully optimized for jump height

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.

Control strategy of maximum vertical jumps: The preferred countermovement depth may not be fully optimized for jump height.

Science.gov (United States)

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.

Minimizing the health and climate impacts of emissions from heavy-duty public transportation bus fleets through operational optimization.

Science.gov (United States)

Gouge, Brian; Dowlatabadi, Hadi; Ries, Francis J

2013-04-16

In contrast to capital control strategies (i.e., investments in new technology), the potential of operational control strategies (e.g., vehicle scheduling optimization) to reduce the health and climate impacts of the emissions from public transportation bus fleets has not been widely considered. This case study demonstrates that heterogeneity in the emission levels of different bus technologies and the exposure potential of bus routes can be exploited though optimization (e.g., how vehicles are assigned to routes) to minimize these impacts as well as operating costs. The magnitude of the benefits of the optimization depend on the specific transit system and region. Health impacts were found to be particularly sensitive to different vehicle assignments and ranged from worst to best case assignment by more than a factor of 2, suggesting there is significant potential to reduce health impacts. Trade-offs between climate, health, and cost objectives were also found. Transit agencies that do not consider these objectives in an integrated framework and, for example, optimize for costs and/or climate impacts alone, risk inadvertently increasing health impacts by as much as 49%. Cost-benefit analysis was used to evaluate trade-offs between objectives, but large uncertainties make identifying an optimal solution challenging.

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...

Trade Services System Adaptation for Sustainable Development

Science.gov (United States)

Khrichenkov, A.; Shaufler, V.; Bannikova, L.

2017-11-01

Under market conditions, the trade services system in post-Soviet Russia, being one of the most important city infrastructures, loses its systematic and hierarchic consistency hence provoking the degradation of communicating transport systems and urban planning framework. This article describes the results of the research carried out to identify objects and object parameters that influence functioning of a locally significant trade services system. Based on the revealed consumer behaviour patterns, we propose methods to determine the optimal parameters of objects inside a locally significant trade services system.

Optimal Prices and Trade-in Rebates for Durable, Remanufacturable Products

OpenAIRE

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 ...

Multi-Objective Optimal Design of Renewable Energy Integrated CCHP System Using PICEA-g

Directory of Open Access Journals (Sweden)

Guozheng Li

2018-03-01

Full Text Available The integration of renewable energies into combined cooling, heating, and power (CCHP systems has become increasingly popular in recent years. However, the optimization of renewable energies integrated CCHP (RECCHP systems (i.e., optimal component configurations is far from being well addressed, especially in isolated mode. This study aims to fill this research gap. A multi-objective optimization model characterizing the system reliability, system cost, and environmental sustainability is constructed. In this model, the objectives include minimization of annual total cost (ATC, carbon dioxide emission (CDE, and loss of energy supply probability (LESP. The decision variables representing the configuration of the RECCHP system include the number of photovoltaic (PV panels and wind turbines (WTs, the tilt angle of PV panels, the height of WTs, the maximum fuel consumption, and the capacity of battery and heat storage tanks (HSTs. The multi-objective model is solved by a multi-objective evolutionary algorithm, namely, the preference-inspired coevolutionary algorithm (PICEA-g, resulting in a set of Pareto optimal (trade-off solutions. Then, a decision-making process is demonstrated, selecting a preferred solution amongst those trade-off solutions by further considering the decision-maker preferences. Furthermore, on the optimization of the RECCHP system, operational strategies (i.e., following electric load, FEL, and following thermal load, FTL are considered, respectively. Experimental results show that the FEL and FTL strategies lead to different optimal configurations. In general, the FTL is recommended in summer and winter, while the FEL is more suitable for spring and autumn. Compared with traditional energy systems, RECCHP has better economic and environmental advantages.

The Correlation between Game Theory and International Trade

Directory of Open Access Journals (Sweden)

Simona-Valeria TOMA

2012-08-01

Full Text Available The Correlation between Game Theory and International TradeAbstract:Game theory, in its most basic form, considers two or more players and analyses the different strategies that they can use and the effect that these strategies will have on each player. International trade allows countries to use better their resources (labor, technology or capital. Since countries have different capital or natural resources, some of them will produce a good more efficiently than others and therefore could sell it cheaper than other countries. By using game theory in international trade we could determine if the Heckscher-Ohlin-Samuelson model is correct and what would be the best specialization for each country. The aim of this paper is to test if game theory could be successfully used in a thorough analysis of international trade specialization.

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

Optimization of behavioral, biobehavioral, and biomedical interventions the multiphase optimization strategy (MOST)

CERN Document Server

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 ...

Hereditary Portfolio Optimization with Taxes and Fixed Plus Proportional Transaction Costs—Part II

Directory of Open Access Journals (Sweden)

Mou-Hsiung Chang

2007-01-01

Full Text Available This paper is the continuation of the paper entitled “Hereditary portfolio optimization with taxes and fixed plus proportional transaction costs I” that treats an infinite-time horizon hereditary portfolio optimization problem in a market that consists of one savings account and one stock account. Within the solvency region, the investor is allowed to consume from the savings account and can make transactions between the two assets subject to paying capital-gain taxes as well as a fixed plus proportional transaction cost. The investor is to seek an optimal consumption-trading strategy in order to maximize the expected utility from the total discounted consumption. The portfolio optimization problem is formulated as an infinite dimensional stochastic classical impulse control problem due to the hereditary nature of the stock price dynamics and inventories. This paper contains the verification theorem for the optimal strategy. It also proves that the value function is a viscosity solution of the QVHJBI.

Optimal Sequential Diagnostic Strategy Generation Considering Test Placement Cost for Multimode Systems

Directory of Open Access Journals (Sweden)

Shigang Zhang

2015-10-01

Full Text Available Sequential fault diagnosis is an approach that realizes fault isolation by executing the optimal test step by step. The strategy used, i.e., the sequential diagnostic strategy, has great influence on diagnostic accuracy and cost. Optimal sequential diagnostic strategy generation is an important step in the process of diagnosis system construction, which has been studied extensively in the literature. However, previous algorithms either are designed for single mode systems or do not consider test placement cost. They are not suitable to solve the sequential diagnostic strategy generation problem considering test placement cost for multimode systems. Therefore, this problem is studied in this paper. A formulation is presented. Two algorithms are proposed, one of which is realized by system transformation and the other is newly designed. Extensive simulations are carried out to test the effectiveness of the algorithms. A real-world system is also presented. All the results show that both of them have the ability to solve the diagnostic strategy generation problem, and they have different characteristics.

Optimal Sequential Diagnostic Strategy Generation Considering Test Placement Cost for Multimode Systems

Science.gov (United States)

Zhang, Shigang; Song, Lijun; Zhang, Wei; Hu, Zheng; Yang, Yongmin

2015-01-01

Sequential fault diagnosis is an approach that realizes fault isolation by executing the optimal test step by step. The strategy used, i.e., the sequential diagnostic strategy, has great influence on diagnostic accuracy and cost. Optimal sequential diagnostic strategy generation is an important step in the process of diagnosis system construction, which has been studied extensively in the literature. However, previous algorithms either are designed for single mode systems or do not consider test placement cost. They are not suitable to solve the sequential diagnostic strategy generation problem considering test placement cost for multimode systems. Therefore, this problem is studied in this paper. A formulation is presented. Two algorithms are proposed, one of which is realized by system transformation and the other is newly designed. Extensive simulations are carried out to test the effectiveness of the algorithms. A real-world system is also presented. All the results show that both of them have the ability to solve the diagnostic strategy generation problem, and they have different characteristics. PMID:26457709

Social signals and algorithmic trading of Bitcoin.

Science.gov (United States)

Garcia, David; Schweitzer, Frank

2015-09-01

The availability of data on digital traces is growing to unprecedented sizes, but inferring actionable knowledge from large-scale data is far from being trivial. This is especially important for computational finance, where digital traces of human behaviour offer a great potential to drive trading strategies. We contribute to this by providing a consistent approach that integrates various datasources in the design of algorithmic traders. This allows us to derive insights into the principles behind the profitability of our trading strategies. We illustrate our approach through the analysis of Bitcoin, a cryptocurrency known for its large price fluctuations. In our analysis, we include economic signals of volume and price of exchange for USD, adoption of the Bitcoin technology and transaction volume of Bitcoin. We add social signals related to information search, word of mouth volume, emotional valence and opinion polarization as expressed in tweets related to Bitcoin for more than 3 years. Our analysis reveals that increases in opinion polarization and exchange volume precede rising Bitcoin prices, and that emotional valence precedes opinion polarization and rising exchange volumes. We apply these insights to design algorithmic trading strategies for Bitcoin, reaching very high profits in less than a year. We verify this high profitability with robust statistical methods that take into account risk and trading costs, confirming the long-standing hypothesis that trading-based social media sentiment has the potential to yield positive returns on investment.

Application of optimal control strategies to HIV-malaria co-infection dynamics

Science.gov (United States)

Fatmawati; Windarto; Hanif, Lathifah

2018-03-01

This paper presents a mathematical model of HIV and malaria co-infection transmission dynamics. Optimal control strategies such as malaria preventive, anti-malaria and antiretroviral (ARV) treatments are considered into the model to reduce the co-infection. First, we studied the existence and stability of equilibria of the presented model without control variables. The model has four equilibria, namely the disease-free equilibrium, the HIV endemic equilibrium, the malaria endemic equilibrium, and the co-infection equilibrium. We also obtain two basic reproduction ratios corresponding to the diseases. It was found that the disease-free equilibrium is locally asymptotically stable whenever their respective basic reproduction numbers are less than one. We also conducted a sensitivity analysis to determine the dominant factor controlling the transmission. sic reproduction numbers are less than one. We also conducted a sensitivity analysis to determine the dominant factor controlling the transmission. Then, the optimal control theory for the model was derived analytically by using Pontryagin Maximum Principle. Numerical simulations of the optimal control strategies are also performed to illustrate the results. From the numerical results, we conclude that the best strategy is to combine the malaria prevention and ARV treatments in order to reduce malaria and HIV co-infection populations.

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

Emissions trading in the Netherlands

International Nuclear Information System (INIS)

Zapfel, P.

2002-01-01

In the article 'Emissions trading in the Netherlands. The optimal route towards an international scheme?' (issue 1, 2002) Mulder asks the question to what extent a Dutch national CO2 trading scheme is a worthwhile effort toward an international trading scheme (i.e. is it a first step toward a European-wide emissions trading scheme) when presenting the proposal of the Dutch Commission on CO2 trade and related economic analysis. His conclusion, underlined by modeling results, is that a national scheme along the lines proposed by the Dutch Commission is an expensive policy instrument due to the high transaction costs. The first-best option according to Mulder is to impose CO2-emissions trading with an absolute ceiling on an international level. In the meantime, he states, improving the design of the energy tax system may be an efficient alternative. In this comment I would like to address two issues. First, does the approach proposed by the Dutch Commission make sense from a European perspective towards an EU-wide cap and trade allowance scheme as proposed by the European Commission in October 2001? and Second, what might this Dutch model and philosophy, scaled up to the EU level, look like?

Economic optimization of a global strategy to address the pandemic threat.

Science.gov (United States)

Pike, Jamison; Bogich, Tiffany; Elwood, Sarah; Finnoff, David C; Daszak, Peter

2014-12-30

Emerging pandemics threaten global health and economies and are increasing in frequency. Globally coordinated strategies to combat pandemics, similar to current strategies that address climate change, are largely adaptive, in that they attempt to reduce the impact of a pathogen after it has emerged. However, like climate change, mitigation strategies have been developed that include programs to reduce the underlying drivers of pandemics, particularly animal-to-human disease transmission. Here, we use real options economic modeling of current globally coordinated adaptation strategies for pandemic prevention. We show that they would be optimally implemented within 27 y to reduce the annual rise of emerging infectious disease events by 50% at an estimated one-time cost of approximately $343.7 billion. We then analyze World Bank data on multilateral "One Health" pandemic mitigation programs. We find that, because most pandemics have animal origins, mitigation is a more cost-effective policy than business-as-usual adaptation programs, saving between $344.0.7 billion and $360.3 billion over the next 100 y if implemented today. We conclude that globally coordinated pandemic prevention policies need to be enacted urgently to be optimally effective and that strategies to mitigate pandemics by reducing the impact of their underlying drivers are likely to be more effective than business as usual.

The topography of the environment alters the optimal search strategy for active particles

Science.gov (United States)

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.

Mixed-integer evolution strategies for parameter optimization and their applications to medical image analysis

NARCIS (Netherlands)

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

Reliability–redundancy allocation problem considering optimal redundancy strategy using parallel genetic algorithm

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.

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 combinations of control strategies and cost-effective analysis for visceral leishmaniasis disease transmission.

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.

Optimization of European call options considering physical delivery network and reservoir operation rules

Science.gov (United States)

Cheng, Wei-Chen; Hsu, Nien-Sheng; Cheng, Wen-Ming; Yeh, William W.-G.

2011-10-01

This paper develops alternative strategies for European call options for water purchase under hydrological uncertainties that can be used by water resources managers for decision making. Each alternative strategy maximizes its own objective over a selected sequence of future hydrology that is characterized by exceedance probability. Water trade provides flexibility and enhances water distribution system reliability. However, water trade between two parties in a regional water distribution system involves many issues, such as delivery network, reservoir operation rules, storage space, demand, water availability, uncertainty, and any existing contracts. An option is a security giving the right to buy or sell an asset; in our case, the asset is water. We extend a flow path-based water distribution model to include reservoir operation rules. The model simultaneously considers both the physical distribution network as well as the relationships between water sellers and buyers. We first test the model extension. Then we apply the proposed optimization model for European call options to the Tainan water distribution system in southern Taiwan. The formulation lends itself to a mixed integer linear programming model. We use the weighing method to formulate a composite function for a multiobjective problem. The proposed methodology provides water resources managers with an overall picture of water trade strategies and the consequence of each strategy. The results from the case study indicate that the strategy associated with a streamflow exceedence probability of 50% or smaller should be adopted as the reference strategy for the Tainan water distribution system.

Multi-Objective Design Of Optimal Greenhouse Gas Observation Networks

Science.gov (United States)

Lucas, D. D.; Bergmann, D. J.; Cameron-Smith, P. J.; Gard, E.; Guilderson, T. P.; Rotman, D.; Stolaroff, J. K.

2010-12-01

One of the primary scientific functions of a Greenhouse Gas Information System (GHGIS) is to infer GHG source emission rates and their uncertainties by combining measurements from an observational network with atmospheric transport modeling. Certain features of the observational networks that serve as inputs to a GHGIS --for example, sampling location and frequency-- can greatly impact the accuracy of the retrieved GHG emissions. Observation System Simulation Experiments (OSSEs) provide a framework to characterize emission uncertainties associated with a given network configuration. By minimizing these uncertainties, OSSEs can be used to determine optimal sampling strategies. Designing a real-world GHGIS observing network, however, will involve multiple, conflicting objectives; there will be trade-offs between sampling density, coverage and measurement costs. To address these issues, we have added multi-objective optimization capabilities to OSSEs. We demonstrate these capabilities by quantifying the trade-offs between retrieval error and measurement costs for a prototype GHGIS, and deriving GHG observing networks that are Pareto optimal. [LLNL-ABS-452333: This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Market analyses of livestock trade networks to inform the prevention of joint economic and epidemiological risks.

Science.gov (United States)

Moslonka-Lefebvre, Mathieu; Gilligan, Christopher A; Monod, Hervé; Belloc, Catherine; Ezanno, Pauline; Filipe, João A N; Vergu, Elisabeta

2016-03-01

Conventional epidemiological studies of infections spreading through trade networks, e.g., via livestock movements, generally show that central large-size holdings (hubs) should be preferentially surveyed and controlled in order to reduce epidemic spread. However, epidemiological strategies alone may not be economically optimal when costs of control are factored in together with risks of market disruption from targeting core holdings in a supply chain. Using extensive data on animal movements in supply chains for cattle and swine in France, we introduce a method to identify effective strategies for preventing outbreaks with limited budgets while minimizing the risk of market disruptions. Our method involves the categorization of holdings based on position along the supply chain and degree of market share. Our analyses suggest that trade has a higher risk of propagating epidemics through cattle networks, which are dominated by exchanges involving wholesalers, than for swine. We assess the effectiveness of contrasting interventions from the perspectives of regulators and the market, using percolation analysis. We show that preferentially targeting minor, non-central agents can outperform targeting of hubs when the costs to stakeholders and the risks of market disturbance are considered. Our study highlights the importance of assessing joint economic-epidemiological risks in networks underlying pathogen propagation and trade. © 2016 The Authors.

Market analyses of livestock trade networks to inform the prevention of joint economic and epidemiological risks

Science.gov (United States)

Gilligan, Christopher A.; Belloc, Catherine; Filipe, João A. N.; Vergu, Elisabeta

2016-01-01

Conventional epidemiological studies of infections spreading through trade networks, e.g. via livestock movements, generally show that central large-size holdings (hubs) should be preferentially surveyed and controlled in order to reduce epidemic spread. However, epidemiological strategies alone may not be economically optimal when costs of control are factored in together with risks of market disruption from targeting core holdings in a supply chain. Using extensive data on animal movements in supply chains for cattle and swine in France, we introduce a method to identify effective strategies for preventing outbreaks with limited budgets while minimizing the risk of market disruptions. Our method involves the categorization of holdings based on position along the supply chain and degree of market share. Our analyses suggest that trade has a higher risk of propagating epidemics through cattle networks, which are dominated by exchanges involving wholesalers, than for swine. We assess the effectiveness of contrasting interventions from the perspectives of regulators and the market, using percolation analysis. We show that preferentially targeting minor, non-central agents can outperform targeting of hubs when the costs to stakeholders and the risks of market disturbance are considered. Our study highlights the importance of assessing joint economic–epidemiological risks in networks underlying pathogen propagation and trade. PMID:26984191

Optimizing social participation in community-dwelling older adults through the use of behavioral coping strategies.

Science.gov (United States)

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

Eye Movements Reveal Optimal Strategies for Analogical Reasoning.

Science.gov (United States)

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.

Trade liberalisation, resource sustainability and welfare

DEFF Research Database (Denmark)

Nielsen, Max

2006-01-01

that even though liberalising trade in products supplied by such a fishery might cause steady-state welfare reductions in the supplier countries, these welfare reductions are small compared to the welfare gains from a hypothetical change to optimal management. Hence, the introduction of better fisheries......Recent research has warned that liberalising trade in capture fish products originating from inefficiently managed fisheries might cause over-exploitation, reduced fish stocks and thereby a reduced steady-state of welfare. This paper qualifies the warning in a case study of the East Baltic cod...... market by developing an age-structured bio-economic supply model combined with basic theory of trade between two countries. Welfare effects of trade liberalisation are identified taking fishing quotas, input limitations, mesh-size regulations and shared ownership of stocks into account. It is shown...

Combined optimization model for sustainable energization strategy

Science.gov (United States)

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.

Understanding performance properties of chemical engines under a trade-off optimization: Low-dissipation versus endoreversible model

Science.gov (United States)

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.

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.

SCRUB versus trade: Enemies or allies?

International Nuclear Information System (INIS)

Platt, J.B.

1992-01-01

Under the 1990 Clean Air Act Amendments (CAAA), scrubbing and emission allowance trading will play complementary roles. This paper reviews Phase I announced strategies and presents projections of technology controls, coal switching and industry-wide SO 2 removal costs under different assumptions about trading. The principal uncertainties characterizing today's planning environment are discussed -- ranging from changing expectations for fuel costs to swings in allowance prices and questions about regulation and new operating procedures. Economic forecasting is difficult. A clearer picture of Phase 2 strategies is emerging from EPRI's integrated analysis of fuel, technology and allowance markets -- based on collaboration between A. Van Horn and K. White (management consultants) and T. Hewson (Energy Ventures Analysis). About half the SO 2 reductions required in Phase 2 are likely to come from technology controls and half from coal switching. With trading, the highest cost open-quotes scrubsclose quotes and open-quotes switchesclose quotes can be avoided, more upgrading of low-cost scrubbing is expected, and the role of switching grows to a small extent. Additional benefits from trading, averaging and banking allowances are: better sequencing of technology controls, less stringent specs for equipment, and added flexibility/risk-sharing opportunities in contract arrangements

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

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...

Multi-objective optimization of the control strategy of electric vehicle electro-hydraulic composite braking system with genetic algorithm

Directory of Open Access Journals (Sweden)

Zhang Fengjiao

2015-03-01

Full Text Available Optimization of the control strategy plays an important role in improving the performance of electric vehicles. In order to improve the braking stability and recover the braking energy, a multi-objective genetic algorithm is applied to optimize the key parameters in the control strategy of electric vehicle electro-hydraulic composite braking system. Various limitations are considered in the optimization process, and the optimization results are verified by a software simulation platform of electric vehicle regenerative braking system in typical brake conditions. The results show that optimization objectives achieved a good astringency, and the optimized control strategy can increase the brake energy recovery effectively under the condition of ensuring the braking stability.

Geometric Process-Based Maintenance and Optimization Strategy for the Energy Storage Batteries

Directory of Open Access Journals (Sweden)

Yan Li

2016-01-01

Full Text Available Renewable energy is critical for improving energy structure and reducing environment pollution. But its strong fluctuation and randomness have a serious effect on the stability of the microgrid without the coordination of the energy storage batteries. The main factors that influence the development of the energy storage system are the lack of valid operation and maintenance management as well as the cost control. By analyzing the typical characteristics of the energy storage batteries in their life cycle, the geometric process-based model including the deteriorating system and the improving system is firstly built for describing the operation process, the preventive maintenance process, and the corrective maintenance process. In addition, this paper proposes an optimized management strategy, which aims to minimize the long-run average cost of the energy storage batteries by defining the time interval of the detection and preventive maintenance process as well as the optimal corrective maintenance times, subjected to the state of health and the reliability conditions. The simulation is taken under the built model by applying the proposed energy storage batteries’ optimized management strategy, which verifies the effectiveness and applicability of the management strategy, denoting its obvious practicality on the current application.

Multi-Objective Optimization for Analysis of Changing Trade-Offs in the Nepalese Water-Energy-Food Nexus with Hydropower Development

DEFF Research Database (Denmark)

Dhaubanjar, Sanita; Davidsen, Claus; Bauer-Gottwein, Peter

2017-01-01

transmission constraints using an optimal power flow approach. Basin inflows, hydropower plant specifications, reservoir characteristics, reservoir rules, irrigation water demand, environmental flow requirements, power demand, and transmission line properties are provided as model inputs. The trade......-established water and power system models to develop a decision support tool combining multiple nexus objectives in a linear objective function. To demonstrate our framework, we compare eight Nepalese power development scenarios based on five nexus objectives: minimization of power deficit, maintenance of water...... availability for irrigation to support food self-sufficiency, reduction in flood risk, maintenance of environmental flows, and maximization of power export. The deterministic multi-objective optimization model is spatially resolved to enable realistic representation of the nexus linkages and accounts for power...

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.

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)

Leading Trade Networks in the Context of Globalisation of the World Retail Trade

Directory of Open Access Journals (Sweden)

Kavun Olha O.

2013-12-01

Full Text Available The article considers main tendencies of development of trade networks during 2002 – 2012 and determines that the overwhelming majority of them increased their presence in foreign markets. It analyses specific features of manifestation of the expansion policy by trade structures depending on the region of their origin. It studies motives that make leading retailers go out of boundaries of the national markets. Main of them are sharpening of competition in domestic, more mature markets, due to increase of concentration of network structures and also application of the state policy of restrictions in the trading activity. It considers methods that were selected by major trade networks in 2011 – 2012 for entering foreign markets. It establishes that the most popular was franchising. It determines directions of manifestation of regulation barriers, faced by major trade networks of the world when entering markets of developing countries. It establishes that major national structures, which are the main competitors for international trade networks and which make them develop a more weighted approach to making decisions that are connected with entering a new market and adjustment of existing strategies of development, are represented in markets of individual countries, in particular, in Asia and South Africa.

Optimization of maintenance strategies in case of data uncertainties; Optimierung von Instandhaltungsstrategien bei unscharfen Eingangsdaten

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.

Optimal investment strategies and hedging of derivatives in the presence of transaction costs (Invited Paper)

Science.gov (United States)

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.

Empirical Study on Conservative and Representative Heuristics of Hong Kong Small Investors Adopting Momentum and Contrarian Trading Strategies

OpenAIRE

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...

Optimization as a Reasoning Strategy for Dealing with Socioscientific Decision-Making Situations

Science.gov (United States)

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…

Optimization of control strategies for epidemics in heterogeneous populations with symmetric and asymmetric transmission

OpenAIRE

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...

Trading wind energy on the basis of probabilistic forecasts both of wind generation and of market quantities

DEFF Research Database (Denmark)

Zugno, Marco; Jónsson, Tryggvi; Pinson, Pierre

2013-01-01

in liberalized electricity markets and to assess its performance. At first, the so-called optimal quantile strategy is revisited. It is proved that without market power, i.e. under the price-taker assumption, this strategy maximizes expected market revenues. Forecasts of wind power production, of day......-ahead and real-time market prices and of the system imbalance are inputs to this strategy. Subsequently, constraining of the bid that maximizes the expected revenues is proposed as a way to overcome the strategy's disregard of practical limitations and, at the same time, of risk. Two constraining techniques......Wind power is not easily predictable and non-dispatchable. Nevertheless, wind power producers are increasingly urged to participate in electricity market auctions in the same manner as conventional power producers. The aim of this paper is to propose an operational strategy for trading wind energy...

Applying the Taguchi method to river water pollution remediation strategy optimization.

Science.gov (United States)

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.