Efficient Computation of Optimal Trading Strategies
Boyarshinov, Victor
2010-01-01
Given the return series for a set of instruments, a \\emph{trading strategy} is a switching function that transfers wealth from one instrument to another at specified times. We present efficient algorithms for constructing (ex-post) trading strategies that are optimal with respect to the total return, the Sterling ratio and the Sharpe ratio. Such ex-post optimal strategies are useful analysis tools. They can be used to analyze the "profitability of a market" in terms of optimal trading; to develop benchmarks against which real trading can be compared; and, within an inductive framework, the optimal trades can be used to to teach learning systems (predictors) which are then used to identify future trading opportunities.
Trading Strategy Adipted Optimization of European Call Option
Fukumi, Toshio
2005-01-01
Optimal pricing of European call option is described by linear stochastic differential equation. Trading strategy given by a twin of stochastic variables was integrated w.r.t. Black-Scholes formula to adopt optimal pricing to tarading strategy.
Optimal Trading Strategies as Measures of Market Disequilibrium
2013-01-01
For classification of the high frequency trading quantities, waiting times, price increments within and between sessions are referred to as the a-, b-, and c-increments. Statistics of the a-b-c-increments are computed for the Time & Sales records posted by the Chicago Mercantile Exchange Group for the futures traded on Globex. The Weibull, Kumaraswamy, Riemann and Hurwitz Zeta, parabolic, Zipf-Mandelbrot distributions are tested for the a- and b-increments. A discrete version of the Fisher-Ti...
Trading strategies of corporate insiders
Klein, O.; Maug, E.; Schneider, Christoph
2017-01-01
We test two complementary theories of optimal trading strategies by analyzing the transaction patterns of corporate insiders. According to information-based theories, investors trade faster if they compete with others for exploiting the same information, while liquidity-based theories predict the
Competition between stock exchanges and optimal trading
van Kervel, V.L.
2013-01-01
This doctoral thesis focuses on two topics on trading in financial markets: competition between stock exchanges and optimal trading strategies. Chapter one analyzes the effect on the liquidity of a stock when it is traded on multiple trading venues, and distinguishes between competition from transpa
Evolution of Trading strategies
Vicente, Javier
2007-03-01
We attempt to classify the trading strategies of agents in the London Stock Exchange into broad categories. Our study is based on that that identifies the member of the exchange associated with each transaction. Based on the evolution of the inventory (holdings of the stock) as a function of time, we use clustering methods to classify the strategies into several groups. We study how these groups evolve in time and attempt to correlate the membership of the groups with other market properties, such as price volatility.
Våge, Selina; Storesund, Julia E; Giske, Jarl; Thingstad, T Frede
2014-01-01
Trophic mechanisms that can generate biodiversity in food webs include bottom-up (growth rate regulating) and top-down (biomass regulating) factors. The top-down control has traditionally been analyzed using the concepts of "Keystone Predation" (KP) and "Killing-the-Winner" (KtW), predominately occuring in discussions of macro- and micro-biological ecology, respectively. Here we combine the classical diamond-shaped food web structure frequently discussed in KP analyses and the KtW concept by introducing a defense strategist capable of partial defense. A formalized description of a trade-off between the defense-strategist's competitive and defensive ability is included. The analysis reveals a complex topology of the steady state solution with strong relationships between food web structure and the combination of trade-off, defense strategy and the system's nutrient content. Among the results is a difference in defense strategies corresponding to maximum biomass, production, or net growth rate of invading individuals. The analysis thus summons awareness that biomass or production, parameters typically measured in field studies to infer success of particular biota, are not directly acted upon by natural selection. Under coexistence with a competition specialist, a balance of competitive and defensive ability of the defense strategist was found to be evolutionarily stable, whereas stronger defense was optimal under increased nutrient levels in the absence of the pure competition specialist. The findings of success of different defense strategies are discussed with respect to SAR11, a highly successful bacterial clade in the pelagic ocean.
Directory of Open Access Journals (Sweden)
Selina Våge
Full Text Available Trophic mechanisms that can generate biodiversity in food webs include bottom-up (growth rate regulating and top-down (biomass regulating factors. The top-down control has traditionally been analyzed using the concepts of "Keystone Predation" (KP and "Killing-the-Winner" (KtW, predominately occuring in discussions of macro- and micro-biological ecology, respectively. Here we combine the classical diamond-shaped food web structure frequently discussed in KP analyses and the KtW concept by introducing a defense strategist capable of partial defense. A formalized description of a trade-off between the defense-strategist's competitive and defensive ability is included. The analysis reveals a complex topology of the steady state solution with strong relationships between food web structure and the combination of trade-off, defense strategy and the system's nutrient content. Among the results is a difference in defense strategies corresponding to maximum biomass, production, or net growth rate of invading individuals. The analysis thus summons awareness that biomass or production, parameters typically measured in field studies to infer success of particular biota, are not directly acted upon by natural selection. Under coexistence with a competition specialist, a balance of competitive and defensive ability of the defense strategist was found to be evolutionarily stable, whereas stronger defense was optimal under increased nutrient levels in the absence of the pure competition specialist. The findings of success of different defense strategies are discussed with respect to SAR11, a highly successful bacterial clade in the pelagic ocean.
China's Foreign Trade Strategy
Institute of Scientific and Technical Information of China (English)
Li Zuoyan
2008-01-01
@@ Profile of route map In 1949,right after the establishment of the People's Republic of China (PRC),overall economic blockage and embargo imposed by other countries,except the Soviet Union and eastern European countries,separated China from the global economic and trade community.In such a context,China Council for the Promotion of International Trade (CCPIT) was born in May 1952 to facilitate non-governmental trade with other countries,Japan in particular.
Informed Option Trading Strategies
C.M. de Jong (Cyriel)
2001-01-01
textabstractWe use a sequential trade model to clarify two mechanisms following the introduction of an option that may lead to increased efficiency in the underlying. On the one hand, market makers learn from trades in the option market and set more accurate prices. On the other hand, the proportion
OPTIMAL INVESTMENT WITH NOISE TRADING RISK
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
This paper investigates the optimal dynamic investment for an investor who maximizes constant absolute risk aversion(CARA)utility in a discrete-time market with a riskfree bond and a risky stock.The risky stock is assumed to present both the dividend risk and the price risk.With our assumptions,the dividend risk is equivalent to fundamental risk,and the price risk is equivalent to the noise trading risk.The analytical expression for the optimal investment strategy is obtained by dynamic programming.The main result in this paper highlights the importance of differentiating between noise trading risk and fundamental risk for the optimal dynamic investment.
Study on liquidity-adjusted optimal trading strategy model%流动性调整的最优交易策略模型研究
Institute of Scientific and Technical Information of China (English)
林辉; 张涤新; 杨浩; 丁一
2011-01-01
通过放松理想化市场的假设条件,构建流动性调整的最优交易策略模型,并证明了交易策略在任意初始持仓、不同行情时的性质.研究表明在行情看涨时,若初始持仓过量则应采取"U型"卖出策略;若初始持仓适量,则应采取"递增型"卖出策略;若初始持仓为较少的多头或空头,则应采取先"递增型"买入,而后"递增型"卖出的策略;若逆市持有过量的空头,则应采取"递增型"买入策略.行情看跌情形则与看涨情形具有完全相反的结果.若行情看平,则应采取"递减型"卖出或"递增型"买入策略.本文最后分析了流动性对最优交易策略的影响.%By relaxing the hypothesis of Idealized Market, this paper presents the model of Liquidity-adjusted optimal trading strategy, and proves the characteristic about optimal tradingstrategies under the condition of different market and optional initial holding. The researchindicates that when the market is bullish, traders would take U-shaped selling strategy while initialholding is excessive. Incremental buying strategy may be adopted for appropriate optimal initialholding. ff initial holding amount is less at either long or short position, optimal trading strategy isthat first incremental buying, and then incremental selling. When traders hold excessive amount atshort position against bullish market, they would take incremental buying strategy. However, theoptimal strategies in bearish market address reverse outcomes that in bullish market. If market isneutral, the optimal strategy is degressive selling or incremental buying strategy. Lastly, this paperanalyses how liquidity affects optimal trading strategy.
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.
Trading strategies in the Italian interbank market
Iori, Giulia; Renò, Roberto; Iori, Giulia
2006-01-01
Using a data set which includes all transactions among banks in the Italian money market, we study their trading strategies and the dependence among them. We use the Fourier method to compute the variance-covariance matrix of trading strategies. Our results indicate that well defined patterns arise. Two main communities of banks, which can be coarsely identified as small and large banks, emerge.
Optimal execution in high-frequency trading with Bayesian learning
Du, Bian; Zhu, Hongliang; Zhao, Jingdong
2016-11-01
We consider optimal trading strategies in which traders submit bid and ask quotes to maximize the expected quadratic utility of total terminal wealth in a limit order book. The trader's bid and ask quotes will be changed by the Poisson arrival of market orders. Meanwhile, the trader may update his estimate of other traders' target sizes and directions by Bayesian learning. The solution of optimal execution in the limit order book is a two-step procedure. First, we model an inactive trading with no limit order in the market. The dealer simply holds dollars and shares of stocks until terminal time. Second, he calibrates his bid and ask quotes to the limit order book. The optimal solutions are given by dynamic programming and in fact they are globally optimal. We also give numerical simulation to the value function and optimal quotes at the last part of the article.
Optimal strategies for throwing accurately.
Venkadesan, M; Mahadevan, L
2017-04-01
The accuracy of throwing in games and sports is governed by how errors in planning and initial conditions are propagated by the dynamics of the projectile. In the simplest setting, the projectile path is typically described by a deterministic parabolic trajectory which has the potential to amplify noisy launch conditions. By analysing how parabolic trajectories propagate errors, we show how to devise optimal strategies for a throwing task demanding accuracy. Our calculations explain observed speed-accuracy trade-offs, preferred throwing style of overarm versus underarm, and strategies for games such as dart throwing, despite having left out most biological complexities. As our criteria for optimal performance depend on the target location, shape and the level of uncertainty in planning, they also naturally suggest an iterative scheme to learn throwing strategies by trial and error.
Trade Liberalization and Optimal Environmental Policies in Vertical Related Markets
Directory of Open Access Journals (Sweden)
Yan-Shu Lin
2012-12-01
Full Text Available This paper establishes a symmetric two-country model with vertically related markets. In the downstream market, there is one firm in each country selling a homogeneous good, whose production generates pollution, to its home and the foreign markets a la Brander (1981. In the intermediate good market, there is also one upstream firm in each country, supplying the intermediate good only to its own country’s downstream market. The upstream firms can choose either price or quantity to maximize their profits. With this setting, the paper examines the optimal environmental policy and how it is affected by the tariff on the final good. It is found that, under free trade, the optimal final-good output with imperfect intermediate-good market will have the same output level as that with perfect intermediate-good market after imposing the optimal emission tax. The optimal environmental tax is smaller and the optimal environmental policy is less likely to be a green strategy under trade liberalization if the market structure in the intermediate good market is imperfect than perfect competition. On the other hand, the optimal environmental tax is necessarily higher if the upstream firm chooses price than quantity. Moreover, the optimal environmental policy is less likely to be a green strategy under trade liberalization if the upstream firms choose quantity than price to maximize their profits.
Risky Arbitrage Strategies: Optimal Portfolio Choice and Economic Implications
Liu, Jun; Timmermann, Allan G
2009-01-01
We define risky arbitrages as self-financing trading strategies that have a strictly positive market price but a zero expected cumulative payoff. A continuous time cointegrated system is used to model risky arbitrages as arising from a mean-reverting mispricing component. We derive the optimal trading strategy in closed-form and show that the standard textbook arbitrage strategy is not optimal. In a calibration exercise, we show that the optimal strategy makes a sizeable difference in economi...
Heat Management Strategy Trade Study
Energy Technology Data Exchange (ETDEWEB)
Nick Soelberg; Steve Priebe; Dirk Gombert; Ted Bauer
2009-09-01
This Heat Management Trade Study was performed in 2008-2009 to expand on prior studies in continued efforts to analyze and evaluate options for cost-effectively managing SNF reprocessing wastes. The primary objective was to develop a simplified cost/benefit evaluation for spent nuclear fuel (SNF) reprocessing that combines the characteristics of the waste generated through reprocessing with the impacts of the waste on heating the repository. Under consideration were age of the SNF prior to reprocessing, plutonium and minor actinide (MA) separation from the spent fuel for recycle, fuel value of the recycled Pu and MA, age of the remaining spent fuel waste prior to emplacement in the repository, length of time that active ventilation is employed in the repository, and elemental concentration and heat limits for acceptable glass waste form durability. A secondary objective was to identify and qualitatively analyze remaining issues such as (a) impacts of aging SNF prior to reprocessing on the fuel value of the recovered fissile materials, and (b) impact of reprocessing on the dose risk as developed in the Yucca Mountain Total System Performance Assessment (TSPA). Results of this study can be used to evaluate different options for managing decay heat in waste streams from spent nuclear fuel.
Optimal trading strategies—a time series approach
Bebbington, Peter A.; Kühn, Reimer
2016-05-01
Motivated by recent advances in the spectral theory of auto-covariance matrices, we are led to revisit a reformulation of Markowitz’ mean-variance portfolio optimization approach in the time domain. In its simplest incarnation it applies to a single traded asset and allows an optimal trading strategy to be found which—for a given return—is minimally exposed to market price fluctuations. The model is initially investigated for a range of synthetic price processes, taken to be either second order stationary, or to exhibit second order stationary increments. Attention is paid to consequences of estimating auto-covariance matrices from small finite samples, and auto-covariance matrix cleaning strategies to mitigate against these are investigated. Finally we apply our framework to real world data.
Bubbles, shocks and elementary technical trading strategies
Fry, John
2014-01-01
In this paper we provide a unifying framework for a set of seemingly disparate models for bubbles, shocks and elementary technical trading strategies in financial markets. Markets operate by balancing intrinsic levels of risk and return. This seemingly simple observation is commonly over-looked by academics and practitioners alike. Our model shares its origins in statistical physics with others. However, under our approach, changes in market regime can be explicitly shown to represent a phase transition from random to deterministic behaviour in prices. This structure leads to an improved physical and econometric model. We develop models for bubbles, shocks and elementary technical trading strategies. The list of empirical applications is both interesting and topical and includes real-estate bubbles and the on-going Eurozone crisis. We close by comparing the results of our model with purely qualitative findings from the finance literature.
Optimal Strategy in Basketball
Skinner, Brian
2015-01-01
This book chapter reviews some of the major principles associated with optimal strategy in basketball. In particular, we consider the principles of allocative efficiency (optimal allocation of shots between offensive options), dynamic efficiency (optimal shot selection in the face of pressure from the shot clock), and the risk/reward tradeoff (strategic manipulation of outcome variance). For each principle, we provide a simple example of a strategic problem and show how it can be described analytically. We then review general analytical results and provide an overview of existing statistical studies. A number of open challenges in basketball analysis are highlighted.
Optimal GENCO bidding strategy
Gao, Feng
Electricity industries worldwide are undergoing a period of profound upheaval. The conventional vertically integrated mechanism is being replaced by a competitive market environment. Generation companies have incentives to apply novel technologies to lower production costs, for example: Combined Cycle units. Economic dispatch with Combined Cycle units becomes a non-convex optimization problem, which is difficult if not impossible to solve by conventional methods. Several techniques are proposed here: Mixed Integer Linear Programming, a hybrid method, as well as Evolutionary Algorithms. Evolutionary Algorithms share a common mechanism, stochastic searching per generation. The stochastic property makes evolutionary algorithms robust and adaptive enough to solve a non-convex optimization problem. This research implements GA, EP, and PS algorithms for economic dispatch with Combined Cycle units, and makes a comparison with classical Mixed Integer Linear Programming. The electricity market equilibrium model not only helps Independent System Operator/Regulator analyze market performance and market power, but also provides Market Participants the ability to build optimal bidding strategies based on Microeconomics analysis. Supply Function Equilibrium (SFE) is attractive compared to traditional models. This research identifies a proper SFE model, which can be applied to a multiple period situation. The equilibrium condition using discrete time optimal control is then developed for fuel resource constraints. Finally, the research discusses the issues of multiple equilibria and mixed strategies, which are caused by the transmission network. Additionally, an advantage of the proposed model for merchant transmission planning is discussed. A market simulator is a valuable training and evaluation tool to assist sellers, buyers, and regulators to understand market performance and make better decisions. A traditional optimization model may not be enough to consider the distributed
The construction of optimal hedging portfolio strategies of an investor
African Journals Online (AJOL)
We categorised the investor's portfolio into two folds: the initial investment and the capital gain ... We will also describe the dynamic of our stock price using Binomial lattice model ... equation to derive the optimal values of our trading strategies.
Derivative Trade Optimizing Model Utilizing GP Based on Behavioral Finance Theory
Matsumura, Koki; Kawamoto, Masaru
This paper proposed a new technique which makes the strategy trees for the derivative (option) trading investment decision based on the behavioral finance theory and optimizes it using evolutionary computation, in order to achieve high profitability. The strategy tree uses a technical analysis based on a statistical, experienced technique for the investment decision. The trading model is represented by various technical indexes, and the strategy tree is optimized by the genetic programming(GP) which is one of the evolutionary computations. Moreover, this paper proposed a method using the prospect theory based on the behavioral finance theory to set psychological bias for profit and deficit and attempted to select the appropriate strike price of option for the higher investment efficiency. As a result, this technique produced a good result and found the effectiveness of this trading model by the optimized dealings strategy.
碳排放权交易下的班轮船队配置优化研究%Optimization of Liner Ship Fleet Mix Strategy under Emission Trading System
Institute of Scientific and Technical Information of China (English)
朱墨; 真虹; 甘爱平
2016-01-01
With the trend of imposing market-based mechanisms in shipping industry, this paper proposes an optimization model for liner ship fleet mix strategy under carbon emission trading system, which minimizes the total expected operational costs in multiple periods. The uncertain carbon emission allowance price is described by Geometric Brownian Motion. A numerical experiment with real industrial data is carried out to analyze optimized fleet mix strategy and carbon emission volume. Result shows that by involving liner companies into emission trading system, fleet carbon emissions can be reduced significantly, while companies need to pay for the allowances purchase. Another conclusion that based on sensitivity analysis of bunker prices shows:the impact of emission trading system on motivation to use energy-efficient ships and fleet carbon mitigation increases along with the rising of bunker price.%针对集装箱班轮运输企业建立考虑碳排放权交易机制的船队配置优化模型，以期实现船队营运成本最小化。采用几何布朗运动描述欧洲碳排放权交易价格的波动路径，以使决策根据变化的碳交易价格做出。收集班轮业营运数据设计案例，验证了模型能够应用于实例分析。算例结果显示，即使在近期较低的欧洲碳交易价格水平下，在集装箱班轮行业中实施碳交易机制仍能取得明显的减排效果，但企业也需付出一定的费用；针对燃油价格做敏感性分析得出，随着燃油价格的上升，碳交易机制对促进减排的效果也越加显著。
Evolution Strategies in Optimization Problems
Cruz, Pedro A F
2007-01-01
Evolution Strategies are inspired in biology and part of a larger research field known as Evolutionary Algorithms. Those strategies perform a random search in the space of admissible functions, aiming to optimize some given objective function. We show that simple evolution strategies are a useful tool in optimal control, permitting to obtain, in an efficient way, good approximations to the solutions of some recent and challenging optimal control problems.
Algorithmic trading technology and strategy research on financial markets
Barca Linares, Victor
2017-01-01
Due to the financial digitalization, the human intervention in many operations both functional and those aimed to make profit in the market are likely to be substituted by algorithms and automated processes. This thesis lay the foundations of algorithmic trading developing a framework to automate the whole process of trading financial assets. Also, it researches trading strategies and the real potential to make profit. The framework consists of separated functional modules to acquire ...
Optimal portfolio performance with exchange traded funds
Petronio, Filomena; Lando, Tommaso; Biglova, Almira; Ortobelli, Sergio
2014-01-01
In this paper, the portfolio selection problem in exchange-traded fund (hereafter ETF) markets is considered. Since the ETFs track some market indexes with lower costs than the indexes, their development and popularity is grown enormously in the last decade. Moreover, ETF characteristics also present several advantages for the investors that we briefly examine for the U.S. and European markets of ETFs. In particular, we first introduce a new performance measure consistent with the...
Optimal trading quantity integration as a basis for optimal portfolio management
Directory of Open Access Journals (Sweden)
Saša Žiković
2005-06-01
Full Text Available The author in this paper points out the reason behind calculating and using optimal trading quantity in conjunction with Markowitz’s Modern portfolio theory. In the opening part the author presents an example of calculating optimal weights using Markowitz’s Mean-Variance approach, followed by an explanation of basic logic behind optimal trading quantity. The use of optimal trading quantity is not limited to systems with Bernoulli outcome, but can also be used when trading shares, futures, options etc. Optimal trading quantity points out two often-overlooked axioms: (1 a system with negative mathematical expectancy can never be transformed in a system with positive mathematical expectancy, (2 by missing the optimal trading quantity an investor can turn a system with positive expectancy into a negative one. Optimal trading quantity is that quantity which maximizes geometric mean (growth function of a particular system. To determine the optimal trading quantity for simpler systems, with a very limited number of outcomes, a set of Kelly’s formulas is appropriate. In the conclusion the summary of the paper is presented.
The optimal inventory policy for EPQ model under trade credit
Chung, Kun-Jen
2010-09-01
Huang and Huang [(2008), 'Optimal Inventory Replenishment Policy for the EPQ Model Under Trade Credit without Derivatives International Journal of Systems Science, 39, 539-546] use the algebraic method to determine the optimal inventory replenishment policy for the retailer in the extended model under trade credit. However, the algebraic method has its limit of application such that validities of proofs of Theorems 1-4 in Huang and Huang (2008) are questionable. The main purpose of this article is not only to indicate shortcomings but also to present the accurate proofs for Huang and Huang (2008).
Impact of Misalignment of Trading Agent Strategy across Multiple Markets
Sohn, Jung-Woo; Lee, Sooyeon; Mullen, Tracy
We examine the effect of a market pricing policy designed to attract high-valued traders in a multiple market context using JCAT software. Our experiments show that a simple change to pricing policy can create market performance effects that traditional adaptive trading agents are unable to recognize or capitalize on, but that market-policy-aware trading agents can generally obtain. This suggests as parameterized and tunable markets become more common, trading strategies will increasingly need to be conditional on each individual market’s policies.
Trading Strategy with Stochastic Volatility in a Limit Order Book Market
Ching, Wai-Ki; Gu, Jia-Wen; Siu, Tak-Kuen; Yang, Qing-Qing
2016-01-01
In this paper, we employ the Heston stochastic volatility model to describe the stock's volatility and apply the model to derive and analyze the optimal trading strategies for dealers in a security market. We also extend our study to option market making for options written on stocks in the presence of stochastic volatility. Mathematically, the problem is formulated as a stochastic optimal control problem and the controlled state process is the dealer's mark-to-market wealth. Dealers in the s...
Study on Electricity Purchase Optimization in Coordination of Electricity and Carbon Trading
Liu, Dunnan; Meng, Yaru; Zhang, Shuo
2017-07-01
With the establishment of carbon emissions trading market in China, the power industry has become an important part of the market participants. The power grid enterprises need to optimize their own strategies in the new environment of electricity market and carbon market coordination. First, the influence of electricity and carbon trading coordination on electricity purchase strategy for grid enterprises was analysed in the paper. Then a power purchase optimization model was presented, which used the minimum cost of low carbon, energy saving and environment protection as the goal, the power generation capacity, installed capacity and pollutant emission as the constraints. Finally, a provincial power grid was taken as an example to analyse the model, and the optimization order of power purchase was obtained, which provided a new idea for the low carbon development of power grid enterprises.
Trade Liberalization and Optimal Taxation with Pollution and Heterogeneous Workers
Bontems, Philippe; GOZLAN, Estelle
2014-01-01
In this paper, we address two questions: (i) how should a government pursuing both environmental and redistributive objectives design domestic taxes when redistribution is costly, and (ii) how does trade liberalization affect this optimal tax system, and modify the economy's levels of pollution and inequalities ? Using a general equilibrium model under asymmetric information with two goods, two factors (skilled and unskilled labor) and pollution, we fully characterize the optimal mixed tax sy...
Optimal Strategy and Business Models
DEFF Research Database (Denmark)
Johnson, Peter; Foss, Nicolai Juul
2016-01-01
, it is possible to formalize useful notions of a business model, resources, and competitive advantage. The business model that underpins strategy may be seen as a set of constraints on resources that can be interpreted as controls in optimal control theory. Strategy then might be considered to be the control......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 Hamiltonian...... 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....
Institute of Scientific and Technical Information of China (English)
王慧颖
2014-01-01
In this paper, how luggage trade limited companies integrate and optimize the supply chain is discussed. This pa-per takes A company as an example and analyzes the charac-teristics of the luggage market and its supply chain, presents the internal and external optimization strategy of the supply chain: On the basis of the internal storage management and information construction, we should also optimize the external supply chain---establish dynamic alliance to maintain the important partnership among the supply chain members, and strengthen the integration of online and offline marketing plat-forms, layout the new pattern of O2O, so as to improve whole competing capability and efficiency of the supply chain.%文章就箱包贸易企业如何整合优化供应链进行了探讨。以A企业为例，分析了箱包市场的特点及企业供应链现状，提出了供应链内部和外部优化的策略：在内部仓储管理、信息建设的基础上，再进行外部供应链的优化---建立动态联盟，维持供应链上的重要合作伙伴关系，并加强线上与线下销售平台的融合，布局O2O新模式，以此提升供应链整体的竞争能力和效率。
Fricke, Daniel
2012-12-01
We analyze the correlations in patterns of trading for members of the Italian interbank trading platform e-MID. The trading strategy of a particular member institution is defined as the sequence of (intra-) daily net trading volumes within a certain semester. Based on this definition, we show that there are significant and persistent bilateral correlations between institutions’ trading strategies. In most semesters we find two clusters, with positively (negatively) correlated trading strategies within (between) clusters. We show that the two clusters mostly contain continuous net buyers and net sellers of money, respectively, and that cluster memberships of individual banks are highly persistent. Additionally, we highlight some problems related to our definition of trading strategies. Our findings add further evidence on the fact that preferential lending relationships on the micro-level lead to community structure on the macro-level.
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 growth strategies under divergent predation pressure.
Aikio, S; Herczeg, G; Kuparinen, A; Merilä, J
2013-01-01
The conditions leading to gigantism in nine-spined sticklebacks Pungitius pungitius were analysed by modelling fish growth with the von Bertalanffy model searching for the optimal strategy when the model's growth constant and asymptotic fish size parameters are negatively related to each other. Predator-related mortality was modelled through the increased risk of death during active foraging. The model was parameterized with empirical growth data of fish from four different populations and analysed for optimal growth strategy at different mortality levels. The growth constant and asymptotic fish size were negatively related in most populations. Optimal fish size, fitness and life span decreased with predator-induced mortality. At low mortality, the fitness of pond populations was higher than that of sea populations. The differences disappeared at intermediate mortalities, and sea populations had slightly higher fitness at extremely high mortalities. In the scenario where all populations mature at the same age, the pond populations perform better at low mortalities and the sea populations at high mortalities. It is concluded that a trade-off between growth constant and asymptotic fish size, together with different mortality rates, can explain a significant proportion of body size differentiation between populations. In the present case, it is a sufficient explanation of gigantism in pond P. pungitius. © 2012 The Authors. Journal of Fish Biology © 2012 The Fisheries Society of the British Isles.
Persuasive and Politeness Strategies in Chinese Foreign Trade
Institute of Scientific and Technical Information of China (English)
张芳芳
2013-01-01
During international trade negotiations Chinese salespersons tend to employ a variety of persuasive and politeness strat⁃egies in marketing their products. Persuasion involves face-threatening acts (FTAs), thus politeness strategies which are applied to reduce face-threatening are combined with persuasive communication. This paper, taking Brown and Levinson’s model of po⁃liteness as a reference, makes an analysis on politeness strategies used in persuasive communication of the salespersons.
ASEAN’s Preferential Trade Agreements (PTA Strategy
Directory of Open Access Journals (Sweden)
Guanyi Leu
2011-01-01
Full Text Available This paper provides a diversification explanation in order understand the development of PTAs in Southeast Asia. I argue that an important reason why ASEAN states participate in PTAs has been to diversify existing trade ties and to reduce overdependence on a narrow range of export markets. Southeast Asian countries have formed PTAs with markets with which they had weak or unexplored economic relations, as demonstrated by three case analyses: the ASEAN Free Trade Area (AFTA, the ASEAN-China Free Trade Agreement (ACFTA and the ASEAN-Japan Comprehensive Economic Partnership Agreement (AJCEP. To maximise the economic gains and the diversification effects of PTA participation, ASEAN countries have pursued a strategy of strengthening economic unity while keeping external economic linkages as diversified as possible. Although East Asia, and especially China, was an important alternative market to reduce ASEAN’s dependence on trade with America, ASEAN countries have also pursued PTAs with a number of other trading partners. This paper explains how PTAs have helped ASEAN states to develop more policy autonomy in their trading environment.
Real-Time Trading Strategies of Proactive DISCO with Heterogeneous DG Owners
DEFF Research Database (Denmark)
Zhang, Chunyu; Wang, Qi; Wang, Jianhui;
2016-01-01
procurements from DGOs and the transactions within the real-time market. A one-leader multi-follower-type bilevel model is proposed to embody the PDISCO-DGO gaming structure. The upper-level (UL) problem is to maximize the PDISCO’s profit, while the lower-level (LL) problem indicates the profit maximization......This paper presents a methodology to obtain the optimal trading strategies between the proactive distribution company (PDISCO), heterogeneous distributed generation owners (DGOs) and wholesale market in a real-time trading framework. In this framework, the PDISCO’s decisions cover the power...
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
@@ Jiangsu Province, after executing economic internationalization strategy and establishing the strategic goal of foreign-trade strong province,meaning to pursue a dominating position in the foreign trade relations, has become one of the foreign-trade large provinces of China and provided considerable international competitive power in some important fields.
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
Jiangsu Province, after executing economic internationalization strategy and establishing the strategic goal of foreign-trade strong province,meaning to pursue a dominating position in the foreign trade relations, has become one of the foreign-trade large provinces of China and provided considerable international competitive power in some important fields.……
Regional Virtual Water Trade Strategy in Drought Area in China
Institute of Scientific and Technical Information of China (English)
无
2011-01-01
[Objective]The aim was to analyze the virtual water trade in drought area in China.[Method]Taking agricultural production which was related to water resources as study object and by dint of opportunity cost and comparative advantage theory,water resources have been included into a series of state macro-objective models,such as economic growth,crops safety,and increase of people's well-fare.Virtual water resource strategy was verified effectively and relevant suggestions on virtual water trade in the drought...
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.
Universality of efficiency at unified trade-off optimization.
Zhang, Yanchao; Huang, Chuankun; Lin, Guoxing; Chen, Jincan
2016-03-01
We calculate the efficiency at the unified trade-off optimization criterion (the so-called maximum Ω criterion) representing a compromise between the useful energy and the lost energy of heat engines operating between two reservoirs at different temperatures and chemical potentials, and demonstrate that the linear coefficient 3/4 and quadratic coefficient 1/32 of the efficiency at maximum Ω are universal for heat engines under strong coupling and symmetry conditions. It is further proved that the conclusions obtained here also apply to the ecological optimization criterion.
Watershed-based point sources permitting strategy and dynamic permit-trading analysis.
Ning, Shu-Kuang; Chang, Ni-Bin
2007-09-01
Permit-trading policy in a total maximum daily load (TMDL) program may provide an additional avenue to produce environmental benefit, which closely approximates what would be achieved through a command and control approach, with relatively lower costs. One of the important considerations that might affect the effective trading mechanism is to determine the dynamic transaction prices and trading ratios in response to seasonal changes of assimilative capacity in the river. Advanced studies associated with multi-temporal spatially varied trading ratios among point sources to manage water pollution hold considerable potential for industries and policy makers alike. This paper aims to present an integrated simulation and optimization analysis for generating spatially varied trading ratios and evaluating seasonal transaction prices accordingly. It is designed to configure a permit-trading structure basin-wide and provide decision makers with a wealth of cost-effective, technology-oriented, risk-informed, and community-based management strategies. The case study, seamlessly integrating a QUAL2E simulation model with an optimal waste load allocation (WLA) scheme in a designated TMDL study area, helps understand the complexity of varying environmental resources values over space and time. The pollutants of concern in this region, which are eligible for trading, mainly include both biochemical oxygen demand (BOD) and ammonia-nitrogen (NH3-N). The problem solution, as a consequence, suggests an array of waste load reduction targets in a well-defined WLA scheme and exhibits a dynamic permit-trading framework among different sub-watersheds in the study area. Research findings gained in this paper may extend to any transferable dynamic-discharge permit (TDDP) program worldwide.
Particle swarm optimization based optimal bidding strategy in an ...
African Journals Online (AJOL)
user
Particle swarm optimization based optimal bidding strategy in an open ... relaxation-based approach for strategic bidding in England-Wales pool type electricity market has ... presents the mathematical formulation of optimal bidding problem.
Optimal intervention strategies for tuberculosis
Bowong, Samuel; Aziz Alaoui, A. M.
2013-06-01
This paper deals with the problem of optimal control of a deterministic model of tuberculosis (abbreviated as TB for tubercle bacillus). We first present and analyze an uncontrolled tuberculosis model which incorporates the essential biological and epidemiological features of the disease. The model is shown to exhibit the phenomenon of backward bifurcation, where a stable disease-free equilibrium co-exists with one or more stable endemic equilibria when the associated basic reproduction number is less than the unity. Based on this continuous model, the tuberculosis control is formulated and solved as an optimal control problem, indicating how control terms on the chemoprophylaxis and detection should be introduced in the population to reduce the number of individuals with active TB. Results provide a framework for designing the cost-effective strategies for TB with two intervention methods.
Hedging Strategies for Bayesian Optimization
Brochu, Eric; de Freitas, Nando
2010-01-01
Bayesian optimization with Gaussian processes has become an increasingly popular tool in the machine learning community. It is efficient and can be used when very little is known about the objective function, making it popular in expensive black-box optimization scenarios. It is able to do this by sampling the objective using an acquisition function which incorporates the model's estimate of the objective and the uncertainty at any given point. However, there are several different parameterized acquisition functions in the literature, and it is often unclear which one to use. Instead of using a single acquisition function, we adopt a portfolio of acquisition functions governed by an online multi-armed bandit strategy. We describe the method, which we call GP-Hedge, and show that this method almost always outperforms the best individual acquisition function.
Are random trading strategies more successful than technical ones?
Biondo, Alessio Emanuele; Pluchino, Alessandro; Rapisarda, Andrea; Helbing, Dirk
2013-01-01
In this paper we explore the specific role of randomness in financial markets, inspired by the beneficial role of noise in many physical systems and in previous applications to complex socio-economic systems. After a short introduction, we study the performance of some of the most used trading strategies in predicting the dynamics of financial markets for different international stock exchange indexes, with the goal of comparing them to the performance of a completely random strategy. In this respect, historical data for FTSE-UK, FTSE-MIB, DAX, and S & P500 indexes are taken into account for a period of about 15-20 years (since their creation until today).
Optimal strategies for throwing accurately
Venkadesan, Madhusudhan
2010-01-01
Accuracy of throwing in games and sports is governed by how errors at projectile release are propagated by flight dynamics. To address the question of what governs the choice of throwing strategy, we use a simple model of throwing with an arm modelled as a hinged bar of fixed length that can release a projectile at any angle and angular velocity. We show that the amplification of deviations in launch parameters from a one parameter family of solution curves is quantified by the largest singular value of an appropriate Jacobian. This allows us to predict a preferred throwing style in terms of this singular value, which itself depends on target location and the target shape. Our analysis also allows us to characterize the trade-off between speed and accuracy despite not including any effects of signal-dependent noise. Using nonlinear calculations for propagating finite input-noise, we find that an underarm throw to a target leads to an undershoot, but an overarm throw does not. Finally, we consider the limit of...
Delay-area trade-off for MPRM circuits based on hybrid discrete particle swarm optimization
Institute of Scientific and Technical Information of China (English)
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.
Stochastic Optimal Wind Power Bidding Strategy in Short-Term Electricity Market
DEFF Research Database (Denmark)
Hu, Weihao; Chen, Zhe; Bak-Jensen, Birgitte
2012-01-01
minimization problem for trading wind power in the short-term electricity market is described, to help the wind power owners optimize their bidding strategy. Stochastic optimization and a Monte Carlo method are adopted to find the optimal bidding strategy for trading wind power in the short-term electricity....... Simulation results show that the stochastic optimal bidding strategy for trading wind power in the Danish short-term electricity market is an effective measure to maximize the revenue of the wind power owners.......Due to the fluctuating nature and non-perfect forecast of the wind power, the wind power owners are penalized for the imbalance costs of the regulation, when they trade wind power in the short-term liberalized electricity market. Therefore, in this paper a formulation of an imbalance cost...
Performance Trades Study for Robust Airfoil Shape Optimization
Li, Wu; Padula, Sharon
2003-01-01
From time to time, existing aircraft need to be redesigned for new missions with modified operating conditions such as required lift or cruise speed. This research is motivated by the needs of conceptual and preliminary design teams for smooth airfoil shapes that are similar to the baseline design but have improved drag performance over a range of flight conditions. The proposed modified profile optimization method (MPOM) modifies a large number of design variables to search for nonintuitive performance improvements, while avoiding off-design performance degradation. Given a good initial design, the MPOM generates fairly smooth airfoils that are better than the baseline without making drastic shape changes. Moreover, the MPOM allows users to gain valuable information by exploring performance trades over various design conditions. Four simulation cases of airfoil optimization in transonic viscous ow are included to demonstrate the usefulness of the MPOM as a performance trades study tool. Simulation results are obtained by solving fully turbulent Navier-Stokes equations and the corresponding discrete adjoint equations using an unstructured grid computational fluid dynamics code FUN2D.
Discrete homotopy analysis for optimal trading execution with nonlinear transient market impact
Curato, Gianbiagio; Gatheral, Jim; Lillo, Fabrizio
2016-10-01
Optimal execution in financial markets is the problem of how to trade a large quantity of shares incrementally in time in order to minimize the expected cost. In this paper, we study the problem of the optimal execution in the presence of nonlinear transient market impact. Mathematically such problem is equivalent to solve a strongly nonlinear integral equation, which in our model is a weakly singular Urysohn equation of the first kind. We propose an approach based on Homotopy Analysis Method (HAM), whereby a well behaved initial trading strategy is continuously deformed to lower the expected execution cost. Specifically, we propose a discrete version of the HAM, i.e. the DHAM approach, in order to use the method when the integrals to compute have no closed form solution. We find that the optimal solution is front loaded for concave instantaneous impact even when the investor is risk neutral. More important we find that the expected cost of the DHAM strategy is significantly smaller than the cost of conventional strategies.
Optimal Strategies of High Frequency Trading in a Limit Order Book%基于限价订单簿的最优高频策略及其实证检验
Institute of Scientific and Technical Information of China (English)
刘冰; 孙丰国; 王婧
2015-01-01
In recent years, with the growth of electronic exchanges, anyone is willing to submit limit orders in the system, it can effectively play the role of a market maker. In this project, we used reservation price to control the inventory risk arising from uncertainty in the asset's value. The pricing strategies of dealers have been studied extensively in the micro structure literature. In the first part, we will introduce the basic theory on the microstructure including the exponential utility function and some theory on the limit orders. One of the key steps in the analysis is to use the dynamic programming principle to show that this problem solves the Hamilton–Jacobi–Bellman equation. Based on the model, we explore a simple trading strategy and present an approximate solution and a real trading of the performance of our strategy's profit and loss through the Wind database.%本文针对日内高频交易，引入保留价格具体分析限价单到达率，设计限价单报价的最优高频交易策略，与一般高频交易策略结果进行对比分析，并提供了基于该策略的实证检验分析。理论部分首先对证券价格路径进行了介绍，并通过指数效用函数引出保留价格的基本公式；之后通过对市场微观结构的研究，分析得出限价订单理论上的成交概率；最后通过建立并解出汉密尔顿-雅各比-贝尔曼方程获得最优高频策略，进行计算机模拟并将其与一般高频策略结果进行对比分析，证实了该模型在理论拟合中的优势与策略的稳定性。文中实证分析部分，选取A股市场上的股票，测量股票波动率，并利用理论部分得出的结论，通过Wind终端实时接收数据，检验策略在模拟交易情况下的稳定性与有效性。
Optimization of BEV Charging Strategy
Ji, Wei
This paper presents different approaches to optimize fast charging and workplace charging strategy of battery electric vehicle (BEV) drivers. For the fast charging analysis, a rule-based model was built to simulate BEV charging behavior. Monte Carlo analysis was performed to explore to the potential range of congestion at fast charging stations which could be more than four hours at the most crowded stations. Genetic algorithm was performed to explore the theoretical minimum waiting time at fast charging stations, and it can decrease the waiting time at the most crowded stations to be shorter than one hour. A deterministic approach was proposed as a feasible suggestion that people should consider to take fast charging when the state of charge is approaching 40 miles. This suggestion is hoped to help to minimize potential congestion at fast charging stations. For the workplace charging analysis, scenario analysis was performed to simulate temporal distribution of charging demand under different workplace charging strategies. It was found that if BEV drivers charge as much as possible and as late as possible at workplace, it could increase the utility of solar-generated electricity while relieve grid stress of extra intensive electricity demand at night caused by charging electric vehicles at home.
Topological Optimization of Artificial Microstructure Strategies
2015-04-02
Topographic Optimization Through Artificial Microstructure Strategies During this project as part of DARPA MCMA we aimed to develop and demonstrate...Topographic Optimization Through Artificial Microstructure Strategies Report Title During this project as part of DARPA MCMA we aimed to develop and...Artificial Microstructure Strategies (Yale and Johns Hopkins) During DARPA MCMA we aimed to develop and demonstrate a 3D microstructural
Mathematics, Pricing, Market Risk Management and Trading Strategies for Financial Derivatives (2/3)
CERN. Geneva; Coffey, Brian
2009-01-01
Market Trading and Risk Management of Vanilla FX Options - Measures of Market Risk - Implied Volatility - FX Risk Reversals, FX Strangles - Valuation and Risk Calculations - Risk Management - Market Trading Strategies
Using trading strategies to detect phase transitions in financial markets
Forró, Z.; Woodard, R.; Sornette, D.
2015-04-01
We show that the log-periodic power law singularity model (LPPLS), a mathematical embodiment of positive feedbacks between agents and of their hierarchical dynamical organization, has a significant predictive power in financial markets. We find that LPPLS-based strategies significantly outperform the randomized ones and that they are robust with respect to a large selection of assets and time periods. The dynamics of prices thus markedly deviate from randomness in certain pockets of predictability that can be associated with bubble market regimes. Our hybrid approach, marrying finance with the trading strategies, and critical phenomena with LPPLS, demonstrates that targeting information related to phase transitions enables the forecast of financial bubbles and crashes punctuating the dynamics of prices.
Fractal Formation and Trend Trading Strategy in Futures Market
Masteika, Saulius; Rutkauskas, Aleksandras V.; Lopata, Audrius
The paper presents the details of trend trading algorithm in futures market. A contribution of this paper lies in a modified chart pattern related to a fractal formation, nonlinearity and chaos theory, broadly discussed by Benoit B. Mandelbrot and Bill M. Williams. As typical fractal pattern often is being applied in conjunction with other forms of technical analysis, like moving averages, Elliott Waves analysis or MACD indicators the proposed pattern is presented as a basic indicator itself. The strategy can be applied as up-trend market forecasting tool. The efficiency of the proposed strategy was tested with the most active North American futures contracts using 10 years historical daily data. Experimental results showed better returns if compared to overall market average-CRB index.
Are Random Trading Strategies More Successful than Technical Ones?
Biondo, Alessio Emanuele; Pluchino, Alessandro; Rapisarda, Andrea; Helbing, Dirk
2013-01-01
In this paper we explore the specific role of randomness in financial markets, inspired by the beneficial role of noise in many physical systems and in previous applications to complex socio-economic systems. After a short introduction, we study the performance of some of the most used trading strategies in predicting the dynamics of financial markets for different international stock exchange indexes, with the goal of comparing them to the performance of a completely random strategy. In this respect, historical data for FTSE-UK, FTSE-MIB, DAX, and S & P500 indexes are taken into account for a period of about 15–20 years (since their creation until today). PMID:23874594
Optimal Investment Strategy for Risky Assets
Sergei Maslov; Yi-Cheng Zhang
1998-01-01
We design an optimal strategy for investment in a portfolio of assets subject to a multiplicative Brownian motion. The strategy provides the maximal typical long-term growth rate of investor's capital. We determine the optimal fraction of capital that an investor should keep in risky assets as well as weights of different assets in an optimal portfolio. In this approach both average return and volatility of an asset are relevant indicators determining its optimal weight. Our results are parti...
Optimizing Spectrum Trading in Cognitive Mesh Network Using Machine Learning
Directory of Open Access Journals (Sweden)
Ayoub Alsarhan
2012-01-01
Full Text Available In a cognitive wireless mesh network, licensed users (primary users, PUs may rent surplus spectrum to unlicensed users (secondary users, SUs for getting some revenue. For such spectrum sharing paradigm, maximizing the revenue is the key objective of the PUs while that of the SUs is to meet their requirements. These complex contradicting objectives are embedded in our reinforcement learning (RL model that is developed and implemented as shown in this paper. The objective function is defined as the net revenue gained by PUs from renting some of their spectrum. RL is used to extract the optimal control policy that maximizes the PUs’ profit continuously over time. The extracted policy is used by PUs to manage renting the spectrum to SUs and it helps PUs to adapt to the changing network conditions. Performance evaluation of the proposed spectrum trading approach shows that it is able to find the optimal size and price of spectrum for each primary user under different conditions. Moreover, the approach constitutes a framework for studying, synthesizing and optimizing other schemes. Another contribution is proposing a new distributed algorithm to manage spectrum sharing among PUs. In our scheme, PUs exchange channels dynamically based on the availability of neighbor’s idle channels. In our cooperative scheme, the objective of spectrum sharing is to maximize the total revenue and utilize spectrum efficiently. Compared to the poverty-line heuristic that does not consider the availability of unused spectrum, our scheme has the advantage of utilizing spectrum efficiently.
An Algoritm for the Alocation Optimization of Trading Executions
Directory of Open Access Journals (Sweden)
Claudiu Vinte
2006-04-01
Full Text Available n 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.
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.
Implementation and evaluation of the strategy Pairs Trading for Colombian public debt bonds
Fajardo Rodriguez, Sandra Milena
2017-01-01
Pair trading is a statistical trading strategy based on the concept of mean reverting; investors select two related assets and establish a relation between them buying the underpriced asset and selling the overpriced. When the market returns to the equilibrium the strategy create profit from the short and long position. The empirical application of this paper proposes the evaluation of three methodologies for the implementation of the pair trading strategy using the information of Colombian p...
Stochastic Optimal Wind Power Bidding Strategy in Short-Term Electricity Market
DEFF Research Database (Denmark)
Hu, Weihao; Chen, Zhe; Bak-Jensen, Birgitte
2012-01-01
minimization problem for trading wind power in the short-term electricity market is described, to help the wind power owners optimize their bidding strategy. Stochastic optimization and a Monte Carlo method are adopted to find the optimal bidding strategy for trading wind power in the short-term electricity...... market in order to deal with the uncertainty of the regulation price, the activated regulation of the power system and the forecasted wind power generation. The Danish short-term electricity market and a wind farm in western Denmark are chosen as study cases due to the high wind power penetration here....... Simulation results show that the stochastic optimal bidding strategy for trading wind power in the Danish short-term electricity market is an effective measure to maximize the revenue of the wind power owners....
The Problems and Strategies for Cultural Industry, Trade and City Development in Chengdu
Institute of Scientific and Technical Information of China (English)
徐永安
2010-01-01
This paper defines the importance of cultural industry and trade to the development of the city of Chengdu. It alsot analyzes the present situation and problems of the cultural industry and trade in Chengdu. In the end , the author also puts forward the strategies and measures in the aspect of how to combine the cultural trade with city development.
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...
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.
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.
Enhanced Ocean Predictability Through Optimal Observing Strategies
2016-06-14
Enhanced Ocean Predictability Through Optimal Observing Strategies A. D. Kirwan, Jr. College of Marine Studies University of Delaware Robinson Hall...observation strategies that will maximize the capacity to predict mesoscale and submesoscale conditions so as to provide the best possible nowcasts and...systems approaches on developing optimal observing strategies . The common thread linking both approaches is Lagrangian data, so this phase of the work
EXPORT PROMOTION POLICY, PREREQUISITE OF AN EFFICIENT NATIONAL FOREIGN TRADE STRATEGY
Directory of Open Access Journals (Sweden)
OCTAVIAN-LIVIU OLARU
2012-05-01
Full Text Available The importance of international trade is widely recognized not only by the business sector, but also by governments. Governments all over the world have reviewed and streamlined their foreign trade strategies during the last decades. Nearly all countries have adopted special export promotion and development programmes. These programmes have focused on providing more efficient trade support services in areas such as trade information, financing, logistics, customs procedures and communications. Trade Promotion Organizations (TPOs have a broad mandate to provide or coordinate trade support services in the above mentioned area.
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.
Optimality criteria solution strategies in multiple constraint design optimization
Levy, R.; Parzynski, W.
1981-01-01
Procedures and solution strategies are described to solve the conventional structural optimization problem using the Lagrange multiplier technique. The multipliers, obtained through solution of an auxiliary nonlinear optimization problem, lead to optimality criteria to determine the design variables. It is shown that this procedure is essentially equivalent to an alternative formulation using a dual method Lagrangian function objective. Although mathematical formulations are straight-forward, successful applications and computational efficiency depend upon execution procedure strategies. Strategies examined, with application examples, include selection of active constraints, move limits, line search procedures, and side constraint boundaries.
Zhang, J L; Li, Y P; Huang, G H; Baetz, B W; Liu, J
2017-03-06
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
Linear Tabling Strategies and Optimizations
Zhou, Neng-Fa; Shen, Yi-Dong
2007-01-01
Recently, the iterative approach named linear tabling has received considerable attention because of its simplicity, ease of implementation, and good space efficiency. Linear tabling is a framework from which different methods can be derived based on the strategies used in handling looping subgoals. One decision concerns when answers are consumed and returned. This paper describes two strategies, namely, {\\it lazy} and {\\it eager} strategies, and compares them both qualitatively and quantitatively. The results indicate that, while the lazy strategy has good locality and is well suited for finding all solutions, the eager strategy is comparable in speed with the lazy strategy and is well suited for programs with cuts. Linear tabling relies on depth-first iterative deepening rather than suspension to compute fixpoints. Each cluster of inter-dependent subgoals as represented by a top-most looping subgoal is iteratively evaluated until no subgoal in it can produce any new answers. Naive re-evaluation of all loopi...
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 of...... implications for exhibitors at interna-tional trade shows and export marketing programmes and other marketing programmes offering services to international trade show exhibitors....
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.
Directory of Open Access Journals (Sweden)
Nicolás Acevedo Vélez
2007-04-01
Full Text Available This research shows that it is possible for U.S. cattle feeders to obtain additional profits if a consistent technical strategy for trading is applied to the cattle crush spread. However, when trading costs are introduced, the likelihood of obtaining profit from trading the crush reduces considerably. It also shows that the level of gains from the cattle crush is related to the month the cattle are marketed. When the crush is used as a hedging strategy it decreases the profit from the feeding operation and reduces the volatility of those returns, helping producers to transfer part of the price risk associated with their production. To provide evidence of these findings, this study utilizes daily prices for 1995 to 2006 of the futures contracts of corn, feeder and live cattle to construct the daily cattle crush spread for two different combinations of futures contracts traded in the Chicago Board of Trade and Chicago Mercantile Exchange. These contract combinations suppose that cattle are fed in feedlots for 170 days before being marketed in April and in October. Two different scenarios are also evaluated using the cattle crush spread: one in which the crush is employed as a pre-placement hedging tool and another in which the crush is used as a post-placement hedging method.En este estudio se muestra que es posible para un productor de ganado de carne en EE.UU obtener utilidades adicionales cuando estrategias de operación en el mercado financiero de futuros de Chicago son utilizadas (i.e. la estrategia “cattle crush”. No obstante, los costos de transacción presentes reduce la probabilidad de obtener utilidades mediante la estrategia de análisis técnico. También se muestra que el nivel de ganancia derivado del uso del “cattle crush” está relacionado con el ciclo ganadero en el cual se realice la operación. Cuando el “cattle crush” se utiliza como alternativa para cubrir riesgo, se reduce considerablemente la volatilidad de los
Profits of Trading Strategies Based on Market Sentiments and Technical Analysis
National Research Council Canada - National Science Library
Hai gang Zhou
2009-01-01
.... The results indicate low correlations among the signals generated from the two sources. Trading strategies following signals from market sentiments alone do not generate excess returns over a buy-and-hold strategy, while certain technical signals do...
Multiobjective Optimization Based Vessel Collision Avoidance Strategy Optimization
Directory of Open Access Journals (Sweden)
Qingyang Xu
2014-01-01
Full Text Available The vessel collision accidents cause a great loss of lives and property. In order to reduce the human fault and greatly improve the safety of marine traffic, collision avoidance strategy optimization is proposed to achieve this. In the paper, a multiobjective optimization algorithm NSGA-II is adopted to search for the optimal collision avoidance strategy considering the safety as well as economy elements of collision avoidance. Ship domain and Arena are used to evaluate the collision risk in the simulation. Based on the optimization, an optimal rudder angle is recommended to navigator for collision avoidance. In the simulation example, a crossing encounter situation is simulated, and the NSGA-II searches for the optimal collision avoidance operation under the Convention on the International Regulations for Preventing Collisions at Sea (COLREGS. The simulation studies exhibit the validity of the method.
An agent strategy for automated stock market trading combining price and order book information
Silaghi, G.; Robu, V.
2005-01-01
This paper proposes a novel automated agent strategy for stock market trading, developed in the context of the Penn-Lehman automated trading (PLAT) simulation platform by Kearns, M., and Ortiz, L., (2003). We provide a comprehensive experimental validation of our strategy using historic order book d
Developing & Optimizing a Logical Sourcing Strategy
National Research Council Canada - National Science Library
Lee S Scheible; Chris Bodurow; Karin Daun
2015-01-01
In order to optimize the benefit of the sourcing strategy and ensure delivery of the portfolio, a logical operational process flow must be developed and implemented consistently across all study...
Optimal strategies for flood prevention
Eijgenraam, Carel; Brekelmans, Ruud; den Hertog, Dick; Roos, C.
2016-01-01
Flood prevention policy is of major importance to the Netherlands since a large part of the country is below sea level and high water levels in rivers may also cause floods. In this paper we propose a dike height optimization model to determine economically efficient flood protection standards. We i
Asymptotically Optimal Algorithm for Short-Term Trading Based on the Method of Calibration
V'yugin, Vladimir
2012-01-01
A trading strategy based on a natural learning process, which asymptotically outperforms any trading strategy from RKHS (Reproduced Kernel Hilbert Space), is presented. In this process, the trader rationally chooses his gambles using predictions made by a randomized well calibrated algorithm. Our strategy is based on Dawid's notion of calibration with more general changing checking rules and on some modification of Kakade and Foster's randomized algorithm for computing calibrated forecasts. We use also Vovk's method of defensive forecasting in RKHS.
Trading strategies of institutional investors in a limit order book market
Directory of Open Access Journals (Sweden)
chen Naiwei
2016-01-01
Full Text Available The study aims to examine the trading strategies of institutional investors in limit order book market. The study modifies assumptions of prior studies [1,2] to match actual situations or facilitate calculations. First, to match actual situations or facilitate calculations. First, the investors’ objective in the study is profit maximization rather than minimization of trading costs. Second, time is continuous rather than discrete. Third, price impact functions are non-linear and take the quadratic form that features increasing prices. Study results indicate that institutional investors adopt the increasing trading strategy if the permanent price impact dominate whereas they adopt the decreasing trading strategy if the transient price impact dominates. In addition, the average trading strategy is adopted if and only if the permanent and transient price impacts are combined in some fixed proportions.
The mathematical method to optimize the management of foreign trade activities of the organization
Directory of Open Access Journals (Sweden)
Olga Martyanova
2015-05-01
Full Text Available The article is devoted to development of a mathematical model of optimal control of foreign trade activities of the organization and determine the criteria for its effectiveness in a sanctions policy pursued by Western countries against Russia.
Optimal control of anthracnose using mixed strategies.
Fotsa Mbogne, David Jaures; Thron, Christopher
2015-11-01
In this paper we propose and study a spatial diffusion model for the control of anthracnose disease in a bounded domain. The model is a generalization of the one previously developed in [15]. We use the model to simulate two different types of control strategies against anthracnose disease. Strategies that employ chemical fungicides are modeled using a continuous control function; while strategies that rely on cultivational practices (such as pruning and removal of mummified fruits) are modeled with a control function which is discrete in time (though not in space). For comparative purposes, we perform our analyses for a spatially-averaged model as well as the space-dependent diffusion model. Under weak smoothness conditions on parameters we demonstrate the well-posedness of both models by verifying existence and uniqueness of the solution for the growth inhibition rate for given initial conditions. We also show that the set [0, 1] is positively invariant. We first study control by impulsive strategies, then analyze the simultaneous use of mixed continuous and pulse strategies. In each case we specify a cost functional to be minimized, and we demonstrate the existence of optimal control strategies. In the case of pulse-only strategies, we provide explicit algorithms for finding the optimal control strategies for both the spatially-averaged model and the space-dependent model. We verify the algorithms for both models via simulation, and discuss properties of the optimal solutions. Copyright © 2015 Elsevier Inc. All rights reserved.
Transitions in optimal adaptive strategies for populations in fluctuating environments
Mayer, Andreas; Mora, Thierry; Rivoire, Olivier; Walczak, Aleksandra M.
2017-09-01
Biological populations are subject to fluctuating environmental conditions. Different adaptive strategies can allow them to cope with these fluctuations: specialization to one particular environmental condition, adoption of a generalist phenotype that compromises between conditions, or population-wise diversification (bet hedging). Which strategy provides the largest selective advantage in the long run depends on the range of accessible phenotypes and the statistics of the environmental fluctuations. Here, we analyze this problem in a simple mathematical model of population growth. First, we review and extend a graphical method to identify the nature of the optimal strategy when the environmental fluctuations are uncorrelated. Temporal correlations in environmental fluctuations open up new strategies that rely on memory but are mathematically challenging to study: We present analytical results to address this challenge. We illustrate our general approach by analyzing optimal adaptive strategies in the presence of trade-offs that constrain the range of accessible phenotypes. Our results extend several previous studies and have applications to a variety of biological phenomena, from antibiotic resistance in bacteria to immune responses in vertebrates.
Marketing Strategies in an International Trade Business. Case Company: Koneisto International Oy
Sakulina, Anastasia
2015-01-01
Koneisto International Oy is a trade and brokerage company engaged in foreign trade activities ensuring the circulation of goods between their producers and consumers. The main research problem I will be working on in my thesis is: What specific marketing strategies can Koneisto International Oy use in order to be more present in international trade market? The topic was chosen under an availability of the company to cooperate with me and their interest in the variety of marketing strateg...
Market Efficiency and the Risks and Returns of Dynamic Trading Strategies with Commodity Futures
Switzer, Lorne N.; Jiang, Hui
This paper investigates relationships between profits from dynamic trading strategies, risk premium, convenience yields, and net hedging pressures for commodity futures. As a market efficiency study, it crosses a number of disciplines, including traditional finance, behavioral finance, and behavioral psychology. The term structure of oil, gold, copper and soybeans futures markets contains predictive power for the corresponding term premium. However, only oil futures and soybean futures lead their spot premium. Significant momentum profits are identified in both outright futures and spread trading strategies when the spot premium and the term premium are used to form winner and loser portfolios. Profits from active strategies based on winner and loser portfolios are conditioned on market structure and net hedging pressure effects. Dynamic trading strategies based on contracts with extreme backwardation, extreme contango, and extreme hedging pressures are also tested. On average, spread trading outperforms outright futures trading in capturing the term structure risk and hedging pressure risk. For such strategies, long-short the long-term spread offers the greatest and most significant return and it offers the only exploitable trading profits built on the past hedging pressure. The existence of profits from active trading strategies based on winners is consistent with behavioral finance and behavioral psychology models in which market participants irrationally overreact to information and trends.
Optimal experimental design strategies for detecting hormesis.
Dette, Holger; Pepelyshev, Andrey; Wong, Weng Kee
2011-12-01
Hormesis is a widely observed phenomenon in many branches of life sciences, ranging from toxicology studies to agronomy, with obvious public health and risk assessment implications. We address optimal experimental design strategies for determining the presence of hormesis in a controlled environment using the recently proposed Hunt-Bowman model. We propose alternative models that have an implicit hormetic threshold, discuss their advantages over current models, and construct and study properties of optimal designs for (i) estimating model parameters, (ii) estimating the threshold dose, and (iii) testing for the presence of hormesis. We also determine maximin optimal designs that maximize the minimum of the design efficiencies when we have multiple design criteria or there is model uncertainty where we have a few plausible models of interest. We apply these optimal design strategies to a teratology study and show that the proposed designs outperform the implemented design by a wide margin for many situations.
Sequential optimizing strategy in multi-dimensional bounded forecasting games
Kumon, Masayuki; Takeuchi, Kei
2009-01-01
We propose a sequential optimizing betting strategy in the multi-dimensional bounded forecasting game in the framework of game-theoretic probability of Shafer and Vovk (2001). By studying the asymptotic behavior of its capital process, we prove a generalization of the strong law of large numbers, where the convergence rate of the sample mean vector depends on the growth rate of the quadratic variation process. The growth rate of the quadratic variation process may be slower than the number of rounds or may even be zero. We also introduce an information criterion for selecting efficient betting items. These results are then applied to multiple asset trading strategies in discrete-time and continuous-time games. In the case of continuous-time game we present a measure of the jaggedness of a vector-valued continuous process. Our results are examined by several numerical examples.
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.
Optimal strategies for electric energy contract decision making
Song, Haili
2000-10-01
The power industry restructuring in various countries in recent years has created an environment where trading of electric energy is conducted in a market environment. In such an environment, electric power companies compete for the market share through spot and bilateral markets. Being profit driven, electric power companies need to make decisions on spot market bidding, contract evaluation, and risk management. New methods and software tools are required to meet these upcoming needs. In this research, bidding strategy and contract pricing are studied from a market participant's viewpoint; new methods are developed to guide a market participant in spot and bilateral market operation. A supplier's spot market bidding decision is studied. Stochastic optimization is formulated to calculate a supplier's optimal bids in a single time period. This decision making problem is also formulated as a Markov Decision Process. All the competitors are represented by their bidding parameters with corresponding probabilities. A systematic method is developed to calculate transition probabilities and rewards. The optimal strategy is calculated to maximize the expected reward over a planning horizon. Besides the spot market, a power producer can also trade in the bilateral markets. Bidding strategies in a bilateral market are studied with game theory techniques. Necessary and sufficient conditions of Nash Equilibrium (NE) bidding strategy are derived based on the generators' cost and the loads' willingness to pay. The study shows that in any NE, market efficiency is achieved. Furthermore, all Nash equilibria are revenue equivalent for the generators. The pricing of "Flexible" contracts, which allow delivery flexibility over a period of time with a fixed total amount of electricity to be delivered, is analyzed based on the no-arbitrage pricing principle. The proposed algorithm calculates the price based on the optimality condition of the stochastic optimization formulation
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.
Optimizing Infant Development: Strategies for Day Care.
Chambliss, Catherine
This guide for infant day care providers examines the importance of early experience for brain development and strategies for providing optimal infant care. The introduction discusses the current devaluation of day care and idealization of maternal care and identifies benefits of quality day care experience for intellectual development, sleep…
Optimal Heating Strategies for a Convection Oven
Stigter, J.D.; Scheerlinck, N.; Nicolai, B.M.; Impe, van J.F.
2001-01-01
In this study classical control theory is applied to a heat conduction model with convective boundary conditions. Optimal heating strategies are obtained through solution of an associated algebraic Riccati equation for a finite horizon linear quadratic regulator (LQR). The large dimensional system
Instance Optimality of the Adaptive Maximum Strategy
L. Diening; C. Kreuzer; R. Stevenson
2016-01-01
In this paper, we prove that the standard adaptive finite element method with a (modified) maximum marking strategy is instance optimal for the total error, being the square root of the squared energy error plus the squared oscillation. This result will be derived in the model setting of Poisson’s e
Optimal inspection Strategies for Offshore Structural Systems
DEFF Research Database (Denmark)
Faber, M. H.; Sørensen, John Dalsgaard; Kroon, I. B.
1992-01-01
Optimal planning of inspection and maintenance strategies for structures has become a subject of increasing interest especially for offshore structures for which large costs are associated with structural failure, inspections and repairs. During the last five years a methodology has been formulated...... a mathematical framework for the estimation of the failure and repair costs a.ssociated with systems failure. Further a strategy for selecting the components to inspect based on decision tree analysis is suggested. Methods and analysis schemes are illustrated by a simple example....... to perform optimal inspection and repair strategies for structural components subject to uncertain loading conditions and material behavior. In this paper this methodology is extended to inelude also system failure i.e. failure of a given sub set of all the structural components. This extension ineludes...
Impediments, opportunities and strategies to enhance trade of wild ...
African Journals Online (AJOL)
Prof. Jacob Agea
security in many developing nations as a food or income supplement or a ... to problems faced by poor rural communities. ... What are the challenges and market-related opportunities to trade in .... possible especially through deliberate radio broadcasts, local ..... LEISA, India Newsletter, September 2007:10-11. Holtzman J ...
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.
A Parallel Trade Study Architecture for Design Optimization of Complex Systems
Kim, Hongman; Mullins, James; Ragon, Scott; Soremekun, Grant; Sobieszczanski-Sobieski, Jaroslaw
2005-01-01
Design of a successful product requires evaluating many design alternatives in a limited design cycle time. This can be achieved through leveraging design space exploration tools and available computing resources on the network. This paper presents a parallel trade study architecture to integrate trade study clients and computing resources on a network using Web services. The parallel trade study solution is demonstrated to accelerate design of experiments, genetic algorithm optimization, and a cost as an independent variable (CAIV) study for a space system application.
Mixed integer evolution strategies for parameter optimization.
Li, Rui; Emmerich, Michael T M; Eggermont, Jeroen; Bäck, Thomas; Schütz, M; Dijkstra, J; Reiber, J H C
2013-01-01
Evolution strategies (ESs) are powerful probabilistic search and optimization algorithms gleaned from biological evolution theory. They have been successfully applied to a wide range of real world applications. The modern ESs are mainly designed for solving continuous parameter optimization problems. Their ability to adapt the parameters of the multivariate normal distribution used for mutation during the optimization run makes them well suited for this domain. In this article we describe and study mixed integer evolution strategies (MIES), which are natural extensions of ES for mixed integer optimization problems. MIES can deal with parameter vectors consisting not only of continuous variables but also with nominal discrete and integer variables. Following the design principles of the canonical evolution strategies, they use specialized mutation operators tailored for the aforementioned mixed parameter classes. For each type of variable, the choice of mutation operators is governed by a natural metric for this variable type, maximal entropy, and symmetry considerations. All distributions used for mutation can be controlled in their shape by means of scaling parameters, allowing self-adaptation to be implemented. After introducing and motivating the conceptual design of the MIES, we study the optimality of the self-adaptation of step sizes and mutation rates on a generalized (weighted) sphere model. Moreover, we prove global convergence of the MIES on a very general class of problems. The remainder of the article is devoted to performance studies on artificial landscapes (barrier functions and mixed integer NK landscapes), and a case study in the optimization of medical image analysis systems. In addition, we show that with proper constraint handling techniques, MIES can also be applied to classical mixed integer nonlinear programming problems.
The Short Call Ladder strategy and its application in trading and hedging
Directory of Open Access Journals (Sweden)
Marcel Rešovský
2010-03-01
Full Text Available The paper presents a new approach to the formation of Short Call Ladder (SCL strategy based on the functions of profit. Anoptimal algorithm for the use of this strategy in trading is introduced as well. Furthermore, this paper is focused on the applicationof Short Call Ladder strategy in hedging against a price rise of the underlying asset. In the end, the results are compared with theresults of hedging obtained by Short Combo and Vertical Ratio Call Back Spread option strategy.
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.
Analysis of intra-country virtual water trade strategy to alleviate water scarcity in Iran
Directory of Open Access Journals (Sweden)
M. Faramarzi
2010-04-01
Full Text Available 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 m^{3} to 5.5 billion m^{3} of virtual water by importing wheat from surplus provinces.
Analysis of intra-country virtual water trade strategy to alleviate water scarcity in Iran
Directory of Open Access Journals (Sweden)
M. Faramarzi
2010-08-01
Full Text Available 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 m^{3} to 5.5 billion m^{3} of virtual water by importing wheat from surplus provinces.
Buffer management optimization strategy for satellite ATM
Institute of Scientific and Technical Information of China (English)
Lu Rong; Cao Zhigang
2006-01-01
ECTD (erroneous cell tail drop), a buffer management optimization strategy is suggested which can improve the utilization of buffer resources in satellite ATM (asynchronous transfer mode) networks. The strategy, in which erroneous cells caused by satellite channel and the following cells that belong to the same PDU (protocol data Unit) are discarded, concerns non-real-time data services that use higher layer protocol for retransmission. Based on EPD (early packet drop) policy, mathematical models are established with and without ECTD. The numerical results show that ECTD would optimize buffer management and improve effective throughput (goodput), and the increment of goodput is relative to the CER (cell error ratio) and the PDU length. The higher their values are, the greater the increment. For example,when the average PDU length values are 30 and 90, the improvement of goodput are respectively about 4% and 10%.
Optimal Investment Strategy to Minimize Occupation Time
Bayraktar, Erhan
2008-01-01
We find the optimal investment strategy to minimize the expected time that an individual's wealth stays below zero, the so-called {\\it occupation time}. The individual consumes at a constant rate and invests in a Black-Scholes financial market consisting of one riskless and one risky asset, with the risky asset's price process following a geometric Brownian motion. We also consider an extension of this problem by penalizing the occupation time for the degree to which wealth is negative.
Minimax Strategy of Optimal Unambiguous State Discrimination
Institute of Scientific and Technical Information of China (English)
张文海; 余龙宝; 曹卓良; 叶柳
2012-01-01
In this paper, we consider the minimax strategy to unambiguously discriminate two pure nonorthogonal quantum states without knowing a priori probability. By exploiting the positive-operator valued measure, we derive the upper bound of the minimax measurement of the optimal unambiguous state discrimination. Based on the linear optical devices, we propose an experimentally feasible scheme to implement a minimax measure of a general pair of two nonorthogonal quantum states.
Optimal experimental design strategies for detecting hormesis
2010-01-01
Hormesis is a widely observed phenomenon in many branches of life sciences ranging from toxicology studies to agronomy with obvious public health and risk assessment implications. We address optimal experimental design strategies for determining the presence of hormesis in a controlled environment using the recently proposed Hunt-Bowman model. We propose alternative models that have an implicit hormetic threshold, discuss their advantages over current models, construct and study properties of...
Optimal strategies for pricing general insurance
Emms, P.; Haberman, S.; Savoulli, I.
2006-01-01
Optimal premium pricing policies in a competitive insurance environment are investigated using approximation methods and simulation of sample paths. The market average premium is modelled as a diffusion process, with the premium as the control function and the maximization of the expected total utility of wealth, over a finite time horizon, as the objective. In order to simplify the optimisation problem, a linear utility function is considered and two particular premium strategies are adopted...
Optimal network protection against diverse interdictor strategies
Energy Technology Data Exchange (ETDEWEB)
Ramirez-Marquez, Jose E., E-mail: jmarquez@stevens.ed [Systems Development and Maturity Lab, School of Systems and Enterprises, Stevens Institute of Technology, Castle Point on Hudson, Hoboken, NJ 07030 (United States); Rocco, Claudio M. [Facultad de Ingenieria, Universidad Central de Venezuela, Caracas (Venezuela, Bolivarian Republic of); Levitin, Gregory [Collaborative Autonomic Computing Laboratory, School of Computer Science, University of Electronic Science and Technology of China (China); Israel Electric Corporation, Reliability and Equipment Department, Haifa 31000 (Israel)
2011-03-15
The objective of this paper is to provide optimal protection configurations for a network with components vulnerable to an interdictor with potentially different attacking strategies. Under this new setting, a solution/configuration describes the defender's optimal amount of defense resources allocated to each link against a potential interdictor strategy. Previous to this research decisions were of a binary nature, restricted to defend or not. Obtaining these configurations is important because along with describing the protection scheme, they are also useful for identifying sets of components critical to the successful performance of the network. The application of the approach can be beneficial for networks in telecommunications, energy, and supply chains to name a few. To obtain an optimal solution, the manuscript describes an evolutionary algorithm that considers continuous decision variables. The results obtained for different examples illustrate that equal resource allocation is optimal for the case of homogeneous component vulnerability. These findings are the basis for discussion and for describing future research directives in this area.
Coordinated optimization of weekly reserve, day-ahead and balancing energy trade in hydropower
Fodstad, Marte; Schou Grytli, Eirik; Korpås, Magnus
2017-04-01
We present a model for optimal trade in a weekly power reserve market under day-ahead and balancing market price uncertainty. The model takes the perspective of a price-taking hydropower producer and a case study for the Norwegian market design and a Norwegian multi-reservoir water course for a winter week is presented. We demonstrate how a bid curve for the reserve market can be established through a sensitivity analysis on reserve prices, and observe that the optimal trade in the succeeding day-ahead and balancing market is highly sensitive to the reserve obligation.
On optimal strategies for upgrading networks
Energy Technology Data Exchange (ETDEWEB)
Krumke, S.O.; Noltemeier, H. [Wuerzburg Univ. (Germany). Dept. of Computer Science; Marathe, M.V. [Los Alamos National Lab., NM (United States); Ravi, S.S. [State Univ. of New York, Albany, NY (United States). Dept. of Computer Science; Ravi, R. [Carnegie-Mellon Univ., Pittsburgh, PA (United States). Graduate School of Industrial Administration; Sundaram, R. [Massachusetts Inst. of Tech., Cambridge, MA (United States)
1996-07-02
We study {ital budget constrained optimal network upgrading problems}. Such problems aim at finding optimal strategies for improving a network under some cost measure subject to certain budget constraints. Given an edge weighted graph {ital G(V,E)}, in the {ital edge based upgrading model}, it is assumed that each edge {ital e} of the given network has an associated function {ital c(e)} that specifies for each edge {ital e} the amount by which the length {ital l(e)} is to be reduced. In the {ital node based upgrading model} a node {ital v} can be upgraded at an expense of cost {ital (v)}. Such an upgrade reduces the cost of each edge incident on {ital v} by a fixed factor {rho}, where 0 < {rho} < 1. For a given budget, {ital B}, the goal is to find an improvement strategy such that the total cost of reduction is a most the given budget {ital B} and the cost of a subgraph (e.g. minimum spanning tree) under the modified edge lengths is the best over all possible strategies which obey the budget constraint. Define an ({alpha},{beta})-approximation algorithm as a polynomial-time algorithm that produces a solution within {alpha} times the optimal function value, violating the budget constraint by a factor of at most {Beta}. The results obtained in this paper include the following 1. We show that in general the problem of computing optimal reduction strategy for modifying the network as above is {bold NP}-hard. 2. In the node based model, we show how to devise a near optimal strategy for improving the bottleneck spanning tree. The algorithms have a performance guarantee of (2 ln {ital n}, 1). 3. for the edge based improvement problems we present improved (in terms of performance and time) approximation algorithms. 4. We also present pseudo-polynomial time algorithms (extendible to polynomial time approximation schemes) for a number of edge/node based improvement problems when restricted to the class of treewidth-bounded graphs.
Affordance Learning Based on Subtask's Optimal Strategy
Directory of Open Access Journals (Sweden)
Huaqing Min
2015-08-01
Full Text Available Affordances define the relationships between the robot and environment, in terms of actions that the robot is able to perform. Prior work is mainly about predicting the possibility of a reactive action, and the object's affordance is invariable. However, in the domain of dynamic programming, a robot’s task could often be decomposed into several subtasks, and each subtask could limit the search space. As a result, the robot only needs to replan its sub strategy when an unexpected situation happens, and an object’s affordance might change over time depending on the robot’s state and current subtask. In this paper, we propose a novel affordance model linking the subtask, object, robot state and optimal action. An affordance represents the first action of the optimal strategy under the current subtask when detecting an object, and its influence is promoted from a primitive action to the subtask strategy. Furthermore, hierarchical reinforcement learning and state abstraction mechanism are introduced to learn the task graph and reduce state space. In the navigation experiment, the robot equipped with a camera could learn the objects’ crucial characteristics, and gain their affordances in different subtasks.
Urban and agricultural soils: conflicts and trade-offs in the optimization of ecosystem services
Setälä, H.; Bardgett, R.D.; Birkhofer, K.; Brady, M.; Byrne, L.; de Ruiter, P.C.; de Vries, F.T.; Gardi, C.; Hedlund, K.; Hemerik, L.; Hotes, S.; Liiri, M.; Mortimer, S.R.; Pavao-Zuckerman, M.; Pouyat, R.; Tsiafouli, M.; Van der Putten, W.H.
2014-01-01
[KEYWORDS: Agriculture Ecosystem services Land use Management optimization Soil Urban Trade-off] On-going human population growth and changing patterns of resource consumption are increasing global demand for ecosystem services, many of which are provided by soils. Some of these ecosystem services a
Energy Efficiency - Spectral Efficiency Trade-off: A Multiobjective Optimization Approach
Amin, Osama
2015-04-23
In this paper, we consider the resource allocation problem for energy efficiency (EE) - spectral efficiency (SE) trade-off. Unlike traditional research that uses the EE as an objective function and imposes constraints either on the SE or achievable rate, we propound a multiobjective optimization approach that can flexibly switch between the EE and SE functions or change the priority level of each function using a trade-off parameter. Our dynamic approach is more tractable than the conventional approaches and more convenient to realistic communication applications and scenarios. We prove that the multiobjective optimization of the EE and SE is equivalent to a simple problem that maximizes the achievable rate/SE and minimizes the total power consumption. Then we apply the generalized framework of the resource allocation for the EE-SE trade-off to optimally allocate the subcarriers’ power for orthogonal frequency division multiplexing (OFDM) with imperfect channel estimation. Finally, we use numerical results to discuss the choice of the trade-off parameter and study the effect of the estimation error, transmission power budget and channel-to-noise ratio on the multiobjective optimization.
Trade-Off Analysis vs. Constrained Optimization with an Economic Control Chart Model
1994-01-01
description of this technique can be found in Luenberger (1989) or Reklaitis et al. (1983). Similar to the economic statistical designs, the trade-off...15] Reklaitis , G. V.; Ravindran, A.; and Ragsdell, K. M., Engineering Optimization, Methods and Applications, John Wiley & Sons, New York (1983). [16
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 defense strategy: storage vs. new production.
Shudo, Emi; Iwasa, Yoh
2002-12-07
If hosts produce defense proteins after they are infected by pathogens, it may take hours to days before defense becomes fully active. By producing defense proteins beforehand, and storing them until infection, the host can cope with pathogens with a short time delay. However, producing and storing defense proteins require energy, and the activated defense proteins often cause harm to the host's body as well as to pathogens. Here, we study the optimal strategy for a host who chooses the amount of stored defense proteins, the activation of the stored proteins upon infection, and the new production of the proteins. The optimal strategy is the one that minimizes the sum of the harm by pathogens and the cost of defense. The host chooses the storage size of defense proteins based on the probability distribution of the magnitude of pathogen infection. When the infection size is predictable, all the stored proteins are to be activated upon infection. The optimal strategy is to have no storage and to rely entirely on new production if the expected infection size n(0) is small, but to have a big storage without new production if n(0) is large. The transition from the "new production" phase to "storage" phase occurs at a smaller n(0) when storage cost is small, activation cost is large, pathogen toxicity is large, pathogen growth is fast, the defense is effective, the delay is long, and the infection is more likely. On the other hand, the storage size to produce for a large n(0) decreases with three cost parameters and the defense effectiveness, increases with the likelihood of infection, the toxicity and the growth rate of pathogens, and it is independent of the time delay. When infection size is much smaller than the expected size, some of the stored proteins may stay unused.
Stochastic Optimal Wind Power Bidding Strategy in Short-Term Electricity Market
DEFF Research Database (Denmark)
Hu, Weihao; Chen, Zhe; Bak-Jensen, Birgitte
2012-01-01
Due to the fluctuating nature and non-perfect forecast of the wind power, the wind power owners are penalized for the imbalance costs of the regulation, when they trade wind power in the short-term liberalized electricity market. Therefore, in this paper a formulation of an imbalance cost minimiz....... Simulation results show that the stochastic optimal bidding strategy for trading wind power in the Danish short-term electricity market is an effective measure to maximize the revenue of the wind power owners....
Sundara Rajan, R.; Uthayakumar, R.
2017-04-01
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.
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 m...
Optimizing Gear Shifting Strategy for Off-Road Vehicle with Dynamic Programming
Directory of Open Access Journals (Sweden)
Xinxin Zhao
2014-01-01
Full Text Available Gear shifting strategy of vehicle is important aid for the acquisition of dynamic performance and high economy. A dynamic programming (DP algorithm is used to optimize the gear shifting schedule for off-road vehicle by using an objective function that weighs fuel use and trip time. The optimization is accomplished through discrete dynamic programming and a trade-off between trip time and fuel consumption is analyzed. By using concave and convex surface road as road profile, an optimal gear shifting strategy is used to control the longitudinal behavior of the vehicle. Simulation results show that the trip time can be reduced by powerful gear shifting strategy and fuel consumption can achieve high economy with economical gear shifting strategy in different initial conditions and route cases.
Combined optimization model for sustainable energization strategy
Abtew, Mohammed Seid
Access to energy is a foundation to establish a positive impact on multiple aspects of human development. Both developed and developing countries have a common concern of achieving a sustainable energy supply to fuel economic growth and improve the quality of life with minimal environmental impacts. The Least Developing Countries (LDCs), however, have different economic, social, and energy systems. Prevalence of power outage, lack of access to electricity, structural dissimilarity between rural and urban regions, and traditional fuel dominance for cooking and the resultant health and environmental hazards are some of the distinguishing characteristics of these nations. Most energy planning models have been designed for developed countries' socio-economic demographics and have missed the opportunity to address special features of the poor countries. An improved mixed-integer programming energy-source optimization model is developed to address limitations associated with using current energy optimization models for LDCs, tackle development of the sustainable energization strategies, and ensure diversification and risk management provisions in the selected energy mix. The Model predicted a shift from traditional fuels reliant and weather vulnerable energy source mix to a least cost and reliable modern clean energy sources portfolio, a climb on the energy ladder, and scored multifaceted economic, social, and environmental benefits. At the same time, it represented a transition strategy that evolves to increasingly cleaner energy technologies with growth as opposed to an expensive solution that leapfrogs immediately to the cleanest possible, overreaching technologies.
Local Optimization Strategies in Urban Vehicular Mobility.
Directory of Open Access Journals (Sweden)
Pierpaolo Mastroianni
Full Text Available The comprehension of vehicular traffic in urban environments is crucial to achieve a good management of the complex processes arising from people collective motion. Even allowing for the great complexity of human beings, human behavior turns out to be subject to strong constraints--physical, environmental, social, economic--that induce the emergence of common patterns. The observation and understanding of those patterns is key to setup effective strategies to optimize the quality of life in cities while not frustrating the natural need for mobility. In this paper we focus on vehicular mobility with the aim to reveal the underlying patterns and uncover the human strategies determining them. To this end we analyze a large dataset of GPS vehicles tracks collected in the Rome (Italy district during a month. We demonstrate the existence of a local optimization of travel times that vehicle drivers perform while choosing their journey. This finding is mirrored by two additional important facts, i.e., the observation that the average vehicle velocity increases by increasing the travel length and the emergence of a universal scaling law for the distribution of travel times at fixed traveled length. A simple modeling scheme confirms this scenario opening the way to further predictions.
Life-history strategies of North American elk: trade-offs associated with reproduction and survival
Sabrina Morano; Kelley M. Stewart; James S. Sedinger; Christopher A. Nicolai; Marty Vavra
2013-01-01
The principle of energy allocation states that individuals should attempt to maximize fitness by allocating resources optimally among growth, maintenance, and reproduction. Such allocation may result in trade-offs between survival and reproduction, or between current and future reproduction. We used a marked population of North American elk (Cervus elaphus...
Pricing Strategies under Emissions Trading - an experimental analysis
Energy Technology Data Exchange (ETDEWEB)
Wraake, Markus; Myers, Erica; Mandell, Svante; Holt, Charles; Burtraw, Dallas
2008-10-15
An important feature in the design of an emissions trading program is how emission allowances are initially distributed into the market. The choice between an auction and free allocation should, according to economic theory, not have any influence on the firms' production choices nor on consumer prices. However, many observers are still incredulous that firms should be expected to raise product prices to include the value of emissions allowances they receive for free. Throughout much of Europe and the U.S., energy markets have been deregulated or are in the process of moving toward market liberalization. If market behavior does not conform to predictions of behavior in a competitive market, this may say a great deal about the nature of market liberalization in energy markets as well as about the behavior of environmental markets. If firms are able to voluntarily moderate commodity prices to be below competitive levels, it suggests an ability of these entities to exercise market power or collude - even if this is motivated by a desire to hold back and not pass through the value of emissions allowances in product prices. This paper reports on the use of experimental methods to investigate behavior with respect to how prices will be determined under a cap-and-trade program. We find participants in the experiments employ various approaches. Some participants initially recognize the opportunity cost of emission allowances and included them in their economic choices regardless of how the allowances have been obtained, and other subjects initially do not. However, given a simple economic setting in which payoffs depend on this behavior, we find that subjects learn to consider the value of allowances and overall behavior moves toward that predicted by economic theory. The observations from the experiments may help to understand the ongoing public debate over the interaction of the EU ETS and energy markets. Emission allowance markets are a new phenomenon to many
Simulation of trading strategies in the electricity market
Charkiewicz, Kamil; Nowak, Robert
2011-10-01
The main objective of the energy market existence is reduction of the total cost of production, transport and distribution of energy, and so the prices paid by terminal consumers. Energy market contains few markets that are varying on operational rules, the important segments: the Futures Contract Market and Next Day Market are analyzed in presented approach. The computer system was developed to simulate the Polish Energy Market. This system use the multi-agent approach, where each agent is the separate shared library with defined interface. The software was used to compare strategies for players in energy market, where the strategies uses auto-regression, k-nearest neighbours, neural network and mixed algorithm, to predict the next price.
Optimization of Sensor Monitoring Strategies for Emissions
Klise, K. A.; Laird, C. D.; Downey, N.; Baker Hebert, L.; Blewitt, D.; Smith, G. R.
2016-12-01
Continuous or regularly scheduled monitoring has the potential to quickly identify changes in air quality. However, even with low-cost sensors, only a limited number of sensors can be placed to monitor airborne pollutants. The physical placement of these sensors and the sensor technology used can have a large impact on the performance of a monitoring strategy. Furthermore, sensors can be placed for different objectives, including maximum coverage, minimum time to detection or exposure, or to quantify emissions. Different objectives may require different monitoring strategies, which need to be evaluated by stakeholders before sensors are placed in the field. In this presentation, we outline methods to enhance ambient detection programs through optimal design of the monitoring strategy. These methods integrate atmospheric transport models with sensor characteristics, including fixed and mobile sensors, sensor cost and failure rate. The methods use site specific pre-computed scenarios which capture differences in meteorology, terrain, concentration averaging times, gas concentration, and emission characteristics. The pre-computed scenarios become input to a mixed-integer, stochastic programming problem that solves for sensor locations and types that maximize the effectiveness of the detection program. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.
Optimal allocation of trend following strategies
Grebenkov, Denis S.; Serror, Jeremy
2015-09-01
We consider a portfolio allocation problem for trend following (TF) strategies on multiple correlated assets. Under simplifying assumptions of a Gaussian market and linear TF strategies, we derive analytical formulas for the mean and variance of the portfolio return. We construct then the optimal portfolio that maximizes risk-adjusted return by accounting for inter-asset correlations. The dynamic allocation problem for n assets is shown to be equivalent to the classical static allocation problem for n2 virtual assets that include lead-lag corrections in positions of TF strategies. The respective roles of asset auto-correlations and inter-asset correlations are investigated in depth for the two-asset case and a sector model. In contrast to the principle of diversification suggesting to treat uncorrelated assets, we show that inter-asset correlations allow one to estimate apparent trends more reliably and to adjust the TF positions more efficiently. If properly accounted for, inter-asset correlations are not deteriorative but beneficial for portfolio management that can open new profit opportunities for trend followers. These concepts are illustrated using daily returns of three highly correlated futures markets: the E-mini S&P 500, Euro Stoxx 50 index, and the US 10-year T-note futures.
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.
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...
Optimal portfolio strategies under a shortfall constraint
Directory of Open Access Journals (Sweden)
D Akuma
2009-06-01
Full Text Available 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 financial market is assumed to comprise n risky assets driven by geometric Brownian motion and one risk-free asset. The method of Lagrange multipliers is combined with the Hamilton-Jacobi-Bellman equation to insert the constraint into the resolution framework. The constraint is re-calculated at short intervals of time throughout the investment horizon. A numerical method is applied to obtain an approximate solution to the problem. It is found that the imposition of the constraint curbs investment in the risky assets.
Optimization of Equipment Maintenance Strategy Based on Availability
Institute of Scientific and Technical Information of China (English)
张友诚
2001-01-01
It is very important to optimize maintenance strategy in maintenance plan. Proper parameters play a decisive role for the optimization. In the opinion of writer, availability is a basic parameter, failure consequence cost and failure characteristic are also important parameters. Maintenance strategy can be optimized on the base by means of quantitative analysis and diagram.
Mathematics, Pricing, Market Risk Management and Trading Strategies for Financial Derivatives (1/3)
CERN. Geneva; Coffey, Brian
2009-01-01
Abstract: An introduction to the mathematics and practicalities of market trading and risk management for financial derivatives, the course will focus on examples from the short-term and long term Foreign Exchange (FX) and Interest Rate (IR) derivatives markets. Topics: - Government Bonds and IR Curves - Stochastic FX, Black-Scholes Vanilla FX Options and Martingales - Risk Management and Market Trading for Vanilla FX Options, Market Implied Volatility, Valuation and Risk Management, Market Trading Strategies - Stochastic IR Curves and Implied Volatility, IR Derivatives - Long Term FX Options: Interaction of Stochastic FX and Stochastic IR Vanilla Foreign Exchange (FX) Options - $ Government Bonds, Interest Rate (IR) Curves, Continuous IR - Domestic ($) and Foreign (Yen) Government Bonds, IR curves - Stochastic Spot FX, Forward FX: Ito processes for $ and Yen Investors - Black-Scholes Vanilla FX Options, Connection to Heat/Diffusion Equation - Stochastic Differential Equations with Mart...
An optimal control model for reducing and trading of carbon emissions
Guo, Huaying; Liang, Jin
2016-03-01
A stochastic optimal control model of reducing and trading for carbon emissions is established in this paper. With considerations of reducing the carbon emission growth and the price of the allowances in the market, an optimal policy is searched to have the minimum total costs to achieve the agreement of emission reduction targets. The model turns to a two-dimension HJB equation problem. By the methods of reducing dimension and Cole-Hopf transformation, a semi-closed form solution of the corresponding HJB problem under some assumptions is obtained. For more general cases, the numerical calculations, analysis and comparisons are presented.
The Option Value in Timing Derivative Trades
Drost, Feico; van der Heijden, T.G.E.; Werker, Bas
2015-01-01
Risk-neutral traders executing derivative trades on behalf of portfolio managers maximize their expected profit compared to trading at pre-determined times by timing trades, using the quickly changing risk exposures of derivative baskets. The optimal order submission strategy is a sequence of stop o
Directory of Open Access Journals (Sweden)
Chih-Te Yang
2014-01-01
Full Text Available This paper extends the previous economic order quantity (EOQ models under two-level trade credit such as Goyal (1985, Teng (2002, Huang (2003, 2007, Kreng and Tan (2010, Ouyang et al. (2013, and Teng et al. (2007 to reflect the real-life situations by incorporating the following concepts: (1 the storage capacity is limited, (2 the supplier offers the retailer a partially upstream trade credit linked to order quantity, and (3 both the dispensable assumptions that the upstream trade credit is longer than the downstream trade credit N
Optimal restructuring strategies under various dynamic factors
Institute of Scientific and Technical Information of China (English)
MENG Qing-xuan
2007-01-01
Corporate restructuring was identified as a new industrial force that has great impact on economic values and that therefore has become central in daily financial decision making. This article investigates the optimal restructuring strategies under different dynamic factors and their numerous impacts on firm value. The concept of quasi-leverage is introduced and valuation models are built for corporate debt and equity under imperfect market conditions. The model's input variables include the quasi-leverage and other firm-specific parameters, the output variables include multiple corporate security values. The restructuring cost is formulated in the form of exponential function, which allows us to observe the sensitivity of the variation in security values. The unified model and its analytical solution developed in this research allow us to examine the continuous changes of security values by dynamically changing the coupon rates, riskless interest rate, bankruptcy cost, quasi-leverage, personal tax rate, corporate taxes rate, transaction cost, firm risk, etc., so that the solutions provide useful guidance for financing and restructuring decisions.
Mesh refinement strategy for optimal control problems
Paiva, L. T.; Fontes, F. A. C. C.
2013-10-01
Direct methods are becoming the most used technique to solve nonlinear optimal control problems. Regular time meshes having equidistant spacing are frequently used. However, in some cases these meshes cannot cope accurately with nonlinear behavior. One way to improve the solution is to select a new mesh with a greater number of nodes. Another way, involves adaptive mesh refinement. In this case, the mesh nodes have non equidistant spacing which allow a non uniform nodes collocation. In the method presented in this paper, a time mesh refinement strategy based on the local error is developed. After computing a solution in a coarse mesh, the local error is evaluated, which gives information about the subintervals of time domain where refinement is needed. This procedure is repeated until the local error reaches a user-specified threshold. The technique is applied to solve the car-like vehicle problem aiming minimum consumption. The approach developed in this paper leads to results with greater accuracy and yet with lower overall computational time as compared to using a time meshes having equidistant spacing.
Prosumers strategy for DHC energy flow optimization
Directory of Open Access Journals (Sweden)
Vasek Lubomir
2016-01-01
Full Text Available This article introduces the proposal of discrete model of district heating and cooling system (DHC for energy flow optimization. The aim is to achieve the best solution of the objective function, usually determined by minimizing the production and distribution costs and providing meets the needs of energy consumers. The model also introduces the idea of general prosumers strategy, where all active elements within the modern DHC system are representing by prosumers object. The prosumers are perceived as objects able to actively participate in the planning of production and consumption of energy. It is assumed that the general behaviour of the object in DHC is the same, no matter how they differ in sizes and designs. Thus, all the objects are defined by two characteristics - the ability to produce and consume. The model based on this basic principle, of course, with the most accurate information about the particular values at a time, object properties and other, should provide tools for simulation and control of modern DHC, possibly superior units as Smart Energy Grids - understood as a system integrating Smart Grids (electricity and Smart Thermal Grids (heat a cool.
DEFF Research Database (Denmark)
Dorn, Jochen
not generate enough profit On well-developed markets. Dynamic participation features on cross asset portfolios are at first sight a remedy to that dilemma. Based on volatility thresholds and portfolio re-balancing, the fund engineers try to create a "volatility guaranteed" investment opportunity by surfing...... concepts, next to nothing is known about position reverting strategies and how, and -even more important- in which context they are applied in practice. In the recent market downturn only one sector generated significant profits for the leading investment banks: Volatility trading activities, namely...... 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...
Trading strategy based on dynamic mode decomposition: Tested in Chinese stock market
Cui, Ling-xiao; Long, Wen
2016-11-01
Dynamic mode decomposition (DMD) is an effective method to capture the intrinsic dynamical modes of complex system. In this work, we adopt DMD method to discover the evolutionary patterns in stock market and apply it to Chinese A-share stock market. We design two strategies based on DMD algorithm. The strategy which considers only timing problem can make reliable profits in a choppy market with no prominent trend while fails to beat the benchmark moving-average strategy in bull market. After considering the spatial information from spatial-temporal coherent structure of DMD modes, we improved the trading strategy remarkably. Then the DMD strategies profitability is quantitatively evaluated by performing SPA test to correct the data-snooping effect. The results further prove that DMD algorithm can model the market patterns well in sideways market.
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.
Optimality of feedback control strategies for qubit purification
Wiseman, Howard M.; Bouten, Luc
2007-01-01
Recently two papers [K. Jacobs, Phys. Rev. A {\\bf 67}, 030301(R) (2003); H. M. Wiseman and J. F. Ralph, New J. Physics {\\bf 8}, 90 (2006)] have derived control strategies for rapid purification of qubits, optimized with respect to various goals. In the former paper the proof of optimality was not mathematically rigorous, while the latter gave only heuristic arguments for optimality. In this paper we provide rigorous proofs of optimality in all cases, by applying simple concepts from optimal c...
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.
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.
Maximus-AI: Using Elman Neural Networks for Implementing a SLMR Trading Strategy
Marques, Nuno C.; Gomes, Carlos
This paper presents a stop-loss - maximum return (SLMR) trading strategy based on improving the classic moving average technical indicator with neural networks. We propose an improvement in the efficiency of the long term moving average by using the limited recursion in Elman Neural Networks, jointly with hybrid neuro-symbolic neural network, while still fully keeping all the learning capabilities of non-recursive parts of the network. Simulations using Eurostoxx50 financial index will illustrate the potential of such a strategy for avoiding negative asset returns and decreasing the investment risk.
Optimization strategies for discrete multi-material stiffness optimization
DEFF Research Database (Denmark)
Hvejsel, Christian Frier; Lund, Erik; Stolpe, Mathias
2011-01-01
Design of composite laminated lay-ups are formulated as discrete multi-material selection problems. The design problem can be modeled as a non-convex mixed-integer optimization problem. Such problems are in general only solvable to global optimality for small to moderate sized problems. To attack...... larger problem instances we formulate convex and non-convex continuous relaxations which can be solved using gradient based optimization algorithms. The convex relaxation yields a lower bound on the attainable performance. The optimal solution to the convex relaxation is used as a starting guess...
Developing an Integrated Design Strategy for Chip Layout Optimization
Wits, Wessel Willems; Jauregui Becker, Juan Manuel; van Vliet, Frank Edward; te Riele, G.J.
2011-01-01
This paper presents an integrated design strategy for chip layout optimization. The strategy couples both electric and thermal aspects during the conceptual design phase to improve chip performances; thermal management being one of the major topics. The layout of the chip circuitry is optimized acco
Optimizing metapopulation sustainability through a checkerboard strategy.
Zion, Yossi Ben; Yaari, Gur; Shnerb, Nadav M
2010-01-22
The persistence of a spatially structured population is determined by the rate of dispersal among habitat patches. If the local dynamic at the subpopulation level is extinction-prone, the system viability is maximal at intermediate connectivity where recolonization is allowed, but full synchronization that enables correlated extinction is forbidden. Here we developed and used an algorithm for agent-based simulations in order to study the persistence of a stochastic metapopulation. The effect of noise is shown to be dramatic, and the dynamics of the spatial population differs substantially from the predictions of deterministic models. This has been validated for the stochastic versions of the logistic map, the Ricker map and the Nicholson-Bailey host-parasitoid system. To analyze the possibility of extinction, previous studies were focused on the attractiveness (Lyapunov exponent) of stable solutions and the structure of their basin of attraction (dependence on initial population size). Our results suggest that these features are of secondary importance in the presence of stochasticity. Instead, optimal sustainability is achieved when decoherence is maximal. Individual-based simulations of metapopulations of different sizes, dimensions and noise types, show that the system's lifetime peaks when it displays checkerboard spatial patterns. This conclusion is supported by the results of a recently published Drosophila experiment. The checkerboard strategy provides a technique for the manipulation of migration rates (e.g., by constructing corridors) in order to affect the persistence of a metapopulation. It may be used in order to minimize the risk of extinction of an endangered species, or to maximize the efficiency of an eradication campaign.
Optimizing metapopulation sustainability through a checkerboard strategy.
Directory of Open Access Journals (Sweden)
Yossi Ben Zion
2010-01-01
Full Text Available The persistence of a spatially structured population is determined by the rate of dispersal among habitat patches. If the local dynamic at the subpopulation level is extinction-prone, the system viability is maximal at intermediate connectivity where recolonization is allowed, but full synchronization that enables correlated extinction is forbidden. Here we developed and used an algorithm for agent-based simulations in order to study the persistence of a stochastic metapopulation. The effect of noise is shown to be dramatic, and the dynamics of the spatial population differs substantially from the predictions of deterministic models. This has been validated for the stochastic versions of the logistic map, the Ricker map and the Nicholson-Bailey host-parasitoid system. To analyze the possibility of extinction, previous studies were focused on the attractiveness (Lyapunov exponent of stable solutions and the structure of their basin of attraction (dependence on initial population size. Our results suggest that these features are of secondary importance in the presence of stochasticity. Instead, optimal sustainability is achieved when decoherence is maximal. Individual-based simulations of metapopulations of different sizes, dimensions and noise types, show that the system's lifetime peaks when it displays checkerboard spatial patterns. This conclusion is supported by the results of a recently published Drosophila experiment. The checkerboard strategy provides a technique for the manipulation of migration rates (e.g., by constructing corridors in order to affect the persistence of a metapopulation. It may be used in order to minimize the risk of extinction of an endangered species, or to maximize the efficiency of an eradication campaign.
Research on Design Optimization Strategy in Virtual Product Development
Institute of Scientific and Technical Information of China (English)
潘军; 韩帮军; 范秀敏; 马登哲
2004-01-01
Simulation and optimization are the key points of virtual product development (VPD). Traditional engineering simulation software and optimization methods are inadequate to analyze the optimization problems because of its computational inefficiency. A systematic design optimization strategy by using statistical methods and mathematical optimization technologies is proposed. This method extends the design of experiments (DOE) and the simulation metamodel technologies. Metamodels are built to in place of detailed simulation codes based on effectively DOE, and then be linked to optimization routines for fast analysis, or serve as a bridge for integrating simulation software across different domains. A design optimization of composite material structure is used to demonstrate the newly introduced methodology.
Optimal vaccination strategies and rational behaviour in seasonal epidemics.
Doutor, Paulo; Rodrigues, Paula; Soares, Maria do Céu; Chalub, Fabio A C C
2016-12-01
We consider a SIRS model with time dependent transmission rate. We assume time dependent vaccination which confers the same immunity as natural infection. We study two types of vaccination strategies: (i) optimal vaccination, in the sense that it minimizes the effort of vaccination in the set of vaccination strategies for which, for any sufficiently small perturbation of the disease free state, the number of infectious individuals is monotonically decreasing; (ii) Nash-equilibria strategies where all individuals simultaneously minimize the joint risk of vaccination versus the risk of the disease. The former case corresponds to an optimal solution for mandatory vaccinations, while the second corresponds to the equilibrium to be expected if vaccination is fully voluntary. We are able to show the existence of both optimal and Nash strategies in a general setting. In general, these strategies will not be functions but Radon measures. For specific forms of the transmission rate, we provide explicit formulas for the optimal and the Nash vaccination strategies.
Estimation of optimal feeding strategies for fed-batch bioprocesses.
Franco-Lara, Ezequiel; Weuster-Botz, Dirk
2005-07-01
A generic methodology for feeding strategy optimization is presented. This approach uses a genetic algorithm to search for optimal feeding profiles represented by means of artificial neural networks (ANN). Exemplified on a fed-batch hybridoma cell cultivation, the approach has proven to be able to cope with complex optimization tasks handling intricate constraints and objective functions. Furthermore, the performance of the method is compared with other previously reported standard techniques like: (1) optimal control theory, (2) first order conjugate gradient, (3) dynamical programming, (4) extended evolutionary strategies. The methodology presents no restrictions concerning the number or complexity of the state variables and therefore constitutes a remarkable alternative for process development and optimization.
An optimal replication strategy for data grid systems
Institute of Scientific and Technical Information of China (English)
JIANG Jianjin; YANG Guangwen
2007-01-01
Data access latency is an important metric of system performance in data grid.By means of efficient replication strategy,the amount of data transferred in a wide area network will decrease,and the average access latency of data will decrease ultimately.The motivation of our research is to solve the optimized replica distribution problem in a data grid;that is,the system should utilize many replicas for every data with storage constraints to minimize the average access latency of data.This paper proposes a model of replication strategy in federated data grid and gives the optimized solution.The analysis results and simulation results show that the optimized replication strategy proposed in this paper is superior to LRU caching strategy,uniform replication strategy,proportional replication strategy and square root replication strategy in terms of wide area network bandwidth requirement and in the average access latency of data.
An optimal tuning strategy for tidal turbines
Vennell, Ross
2016-11-01
Tuning wind and tidal turbines is critical to maximizing their power output. Adopting a wind turbine tuning strategy of maximizing the output at any given time is shown to be an extremely poor strategy for large arrays of tidal turbines in channels. This `impatient-tuning strategy' results in far lower power output, much higher structural loads and greater environmental impacts due to flow reduction than an existing `patient-tuning strategy' which maximizes the power output averaged over the tidal cycle. This paper presents a `smart patient tuning strategy', which can increase array output by up to 35% over the existing strategy. This smart strategy forgoes some power generation early in the half tidal cycle in order to allow stronger flows to develop later in the cycle. It extracts enough power from these stronger flows to produce more power from the cycle as a whole than the existing strategy. Surprisingly, the smart strategy can often extract more power without increasing maximum structural loads on the turbines, while also maintaining stronger flows along the channel. This paper also shows that, counterintuitively, for some tuning strategies imposing a cap on turbine power output to limit loads can increase a turbine's average power output.
An optimal tuning strategy for tidal turbines.
Vennell, Ross
2016-11-01
Tuning wind and tidal turbines is critical to maximizing their power output. Adopting a wind turbine tuning strategy of maximizing the output at any given time is shown to be an extremely poor strategy for large arrays of tidal turbines in channels. This 'impatient-tuning strategy' results in far lower power output, much higher structural loads and greater environmental impacts due to flow reduction than an existing 'patient-tuning strategy' which maximizes the power output averaged over the tidal cycle. This paper presents a 'smart patient tuning strategy', which can increase array output by up to 35% over the existing strategy. This smart strategy forgoes some power generation early in the half tidal cycle in order to allow stronger flows to develop later in the cycle. It extracts enough power from these stronger flows to produce more power from the cycle as a whole than the existing strategy. Surprisingly, the smart strategy can often extract more power without increasing maximum structural loads on the turbines, while also maintaining stronger flows along the channel. This paper also shows that, counterintuitively, for some tuning strategies imposing a cap on turbine power output to limit loads can increase a turbine's average power output.
Many-objective optimization and visual analytics reveal key trade-offs for London's water supply
Matrosov, Evgenii S.; Huskova, Ivana; Kasprzyk, Joseph R.; Harou, Julien J.; Lambert, Chris; Reed, Patrick M.
2015-12-01
In this study, we link a water resource management simulator to multi-objective search to reveal the key trade-offs inherent in planning a real-world water resource system. We consider new supplies and demand management (conservation) options while seeking to elucidate the trade-offs between the best portfolios of schemes to satisfy projected water demands. Alternative system designs are evaluated using performance measures that minimize capital and operating costs and energy use while maximizing resilience, engineering and environmental metrics, subject to supply reliability constraints. Our analysis shows many-objective evolutionary optimization coupled with state-of-the art visual analytics can help planners discover more diverse water supply system designs and better understand their inherent trade-offs. The approach is used to explore future water supply options for the Thames water resource system (including London's water supply). New supply options include a new reservoir, water transfers, artificial recharge, wastewater reuse and brackish groundwater desalination. Demand management options include leakage reduction, compulsory metering and seasonal tariffs. The Thames system's Pareto approximate portfolios cluster into distinct groups of water supply options; for example implementing a pipe refurbishment program leads to higher capital costs but greater reliability. This study highlights that traditional least-cost reliability constrained design of water supply systems masks asset combinations whose benefits only become apparent when more planning objectives are considered.
Quality of Employment: Strategies and Interpretations of Spanish Employers and Trade Unions
Directory of Open Access Journals (Sweden)
María Arnal
2013-04-01
Full Text Available This article examines the different discourses of trade unions and employers on quality of employment in Spain. The study takes a qualitative approach, using discussion groups to obtain discursive information about the meanings of quality, assessments and the different strategies employed by social agents. Trade unions use the ‘quality discourse’ as a reason to examine and reconstruct their current role, extending their main concerns and paradigms from those which defend workers’ interests to those which consolidate their criticism of a reprehensible Spanish employer class. Employers’ discourse, on the other hand, is aimed at highlighting the market’s productive purpose, and sustaining their privileged position in labour management, whilst disassociating and distancing themselves from the employment decisions they make.
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......Cities are becoming the locus of climate change policy and planning, both for mitigating greenhouse gas emissions and adapting to the impacts of climate change. These actions involve a number of trade-offs, including densification of the urban structure, concerns over social equity and the proper...... 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....
Optimal relocation strategies for spatially mobile consumers
Iordanov, Iordan
2007-01-01
We develop a model of the behaviour of a dynamically optimizing economic agent who makes consumption-saving and spatial relocation decisions. We formulate an existence result for the model, derive the necessary conditions for optimality and study the behaviour of the economic agent, focusing on the case of a wage distribution with a single maximum.
Strategies for Optimal Design of Structural Systems
DEFF Research Database (Denmark)
Enevoldsen, I.; Sørensen, John Dalsgaard
1992-01-01
Reliability-based design of structural systems is considered. Especially systems where the reliability model is a series system of parallel systems are analysed. A sensitivity analysis for this class of problems is presented. Direct and sequential optimization procedures to solve the optimization...... problems are described. Numerical tests indicate that a sequential technique called the bounds iteration method (BIM) is particularly fast and stable....
Zhang, X.; Cai, X.; Zhu, T.
2013-12-01
Biofuels is booming in recent years due to its potential contributions to energy sustainability, environmental improvement and economic opportunities. Production of biofuels not only competes for land and water with food production, but also directly pushes up food prices when crops such as maize and sugarcane are used as biofuels feedstock. Meanwhile, international trade of agricultural commodities exports and imports water and land resources in a virtual form among different regions, balances overall water and land demands and resource endowment, and provides a promising solution to the increasingly severe food-energy competition. This study investigates how to optimize water and land resources uses for overall welfare at global scale in the framework of 'virtual resources'. In contrast to partial equilibrium models that usually simulate trades year-by-year, this optimization model explores the ideal world where malnourishment is minimized with optimal resources uses and trade flows. Comparing the optimal production and trade patterns with historical data can provide meaningful implications regarding how to utilize water and land resources more efficiently and how the trade flows would be changed for overall welfare at global scale. Valuable insights are obtained in terms of the interactions among food, water and bioenergy systems. A global hydro-economic optimization model is developed, integrating agricultural production, market demands (food, feed, fuel and other), and resource and environmental constraints. Preliminary results show that with the 'free market' mechanism and land as well as water resources use optimization, the malnourished population can be reduced by as much as 65%, compared to the 2000 historical value. Expected results include: 1) optimal trade paths to achieve global malnourishment minimization, 2) how water and land resources constrain local supply, 3) how policy affects the trade pattern as well as resource uses. Furthermore, impacts of
Mahata, Gour Chandra
2015-03-01
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.
Directory of Open Access Journals (Sweden)
Hao Bai
2015-03-01
Full Text Available A virtual power plant takes advantage of interactive communication and energy management systems to optimize and coordinate the dispatch of distributed generation, interruptible loads, energy storage systems and battery switch stations, so as to integrate them as an entity to exchange energy with the power market. This paper studies the optimal dispatch strategy of a virtual power plant, based on a unified electricity market combining day-ahead trading with real-time trading. The operation models of interruptible loads, energy storage systems and battery switch stations are specifically described in the paper. The virtual power plant applies an optimal dispatch strategy to earn the maximal expected profit under some fluctuating parameters, including market price, retail price and load demand. The presented model is a nonlinear mixed-integer programming with inter-temporal constraints and is solved by the fruit fly algorithm.
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.
Trade-offs and efficiencies in optimal budget-constrained multispecies corridor networks
Dilkina, Bistra; Houtman, Rachel; Gomes, Carla P.; Montgomery, Claire A.; McKelvey, Kevin; Kendall, Katherine; Graves, Tabitha A.; Bernstein, Richard; Schwartz, Michael K.
2017-01-01
Conservation biologists recognize that a system of isolated protected areas will be necessary but insufficient to meet biodiversity objectives. Current approaches to connecting core conservation areas through corridors consider optimal corridor placement based on a single optimization goal: commonly, maximizing the movement for a target species across a network of protected areas. We show that designing corridors for single species based on purely ecological criteria leads to extremely expensive linkages that are suboptimal for multispecies connectivity objectives. Similarly, acquiring the least-expensive linkages leads to ecologically poor solutions. We developed algorithms for optimizing corridors for multispecies use given a specific budget. We applied our approach in western Montana to demonstrate how the solutions may be used to evaluate trade-offs in connectivity for 2 species with different habitat requirements, different core areas, and different conservation values under different budgets. We evaluated corridors that were optimal for each species individually and for both species jointly. Incorporating a budget constraint and jointly optimizing for both species resulted in corridors that were close to the individual species movement-potential optima but with substantial cost savings. Our approach produced corridors that were within 14% and 11% of the best possible corridor connectivity for grizzly bears (Ursus arctos) and wolverines (Gulo gulo), respectively, and saved 75% of the cost. Similarly, joint optimization under a combined budget resulted in improved connectivity for both species relative to splitting the budget in 2 to optimize for each species individually. Our results demonstrate economies of scale and complementarities conservation planners can achieve by optimizing corridor designs for financial costs and for multiple species connectivity jointly. We believe that our approach will facilitate corridor conservation by reducing acquisition costs
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.
Strategies in tower solar power plant optimization
Ramos, A.; Ramos, F.
2012-09-01
A method for optimizing a central receiver solar thermal electric power plant is studied. We parametrize the plant design as a function of eleven design variables and reduce the problem of finding optimal designs to the numerical problem of finding the minimum of a function of several variables. This minimization problem is attacked with different algorithms both local and global in nature. We find that all algorithms find the same minimum of the objective function. The performance of each of the algorithms and the resulting designs are studied for two typical cases. We describe a method to evaluate the impact of design variables in the plant performance. This method will tell us what variables are key to the optimal plant design and which ones are less important. This information can be used to further improve the plant design and to accelerate the optimization procedure.
Strategies in tower solar power plant optimization
Ramos, A
2012-01-01
A method for optimizing a central receiver solar thermal electric power plant is studied. We parametrize the plant design as a function of eleven design variables and reduce the problem of finding optimal designs to the numerical problem of finding the minimum of a function of several variables. This minimization problem is attacked with different algorithms both local and global in nature. We find that all algorithms find the same minimum of the objective function. The performance of each of the algorithms and the resulting designs are studied for two typical cases. We describe a method to evaluate the impact of design variables in the plant performance. This method will tell us what variables are key to the optimal plant design and which ones are less important. This information can be used to further improve the plant design and to accelerate the optimization procedure.
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)
2017-08-03
This presentation covers the motivation for this research, optimization under the uncertainty problem formulation, a two-turbine case, the Princess Amalia Wind Farm case, and conclusions and next steps.
Strategies in tower solar power plant optimization
RAMOS, A.; RAMOS, F.
2012-01-01
A method for optimizing a central receiver solar thermal electric power plant is studied. We parametrize the plant design as a function of eleven design variables and reduce the problem of finding optimal designs to the numerical problem of finding the minimum of a function of several variables. This minimization problem is attacked with different algorithms both local and global in nature. We find that all algorithms find the same minimum of the objective function. The performance of each of...
An approximation based global optimization strategy for structural synthesis
Sepulveda, A. E.; Schmit, L. A.
1991-01-01
A global optimization strategy for structural synthesis based on approximation concepts is presented. The methodology involves the solution of a sequence of highly accurate approximate problems using a global optimization algorithm. The global optimization algorithm implemented consists of a branch and bound strategy based on the interval evaluation of the objective function and constraint functions, combined with a local feasible directions algorithm. The approximate design optimization problems are constructed using first order approximations of selected intermediate response quantities in terms of intermediate design variables. Some numerical results for example problems are presented to illustrate the efficacy of the design procedure setforth.
Investment Strategies Optimization based on a SAX-GA Methodology
Canelas, António M L; Horta, Nuno C G
2013-01-01
This book presents a new computational finance approach combining a Symbolic Aggregate approXimation (SAX) technique with an optimization kernel based on genetic algorithms (GA). While the SAX representation is used to describe the financial time series, the evolutionary optimization kernel is used in order to identify the most relevant patterns and generate investment rules. The proposed approach considers several different chromosomes structures in order to achieve better results on the trading platform The methodology presented in this book has great potential on investment markets.
Heuristic Portfolio Trading Rules with Capital Gain Taxes
DEFF Research Database (Denmark)
Fischer, Marcel; Gallmeyer, Michael
We study the out-of-sample performance of portfolio trading strategies when an investor faces capital gain taxation and proportional transaction costs. Under no capital gain taxation and no transaction costs, we show that, consistent with DeMiguel, Garlappi, and Uppal (2009), a simple 1/N trading...... strategy is not dominated out-of-sample by a variety of optimizing trading strategies, except the parametric portfolios of Brandt, Santa-Clara, and Valkanov (2009). With dividend and realization-based capital gain taxes, the welfare costs of the taxes are large with the cost being as large as 30% of wealth...... 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...
Energy Technology Data Exchange (ETDEWEB)
Boonchuay, Chanwit [Energy Field of Study, School of Environment, Resources and Development, Asian Institute of Technology (Thailand); Ongsakul, Weerakorn, E-mail: ongsakul@ait.asi [Energy Field of Study, School of Environment, Resources and Development, Asian Institute of Technology (Thailand)
2011-02-15
In this paper, an optimal risky bidding strategy for a generating company (GenCo) by self-organising hierarchical particle swarm optimisation with time-varying acceleration coefficients (SPSO-TVAC) is proposed. A significant risk index based on mean-standard deviation ratio (MSR) is maximised to provide the optimal bid prices and quantities. The Monte Carlo (MC) method is employed to simulate rivals' behaviour in competitive environment. Non-convex operating cost functions of thermal generating units and minimum up/down time constraints are taken into account. The proposed bidding strategy is implemented in a multi-hourly trading in a uniform price spot market and compared to other particle swarm optimisation (PSO). Test results indicate that the proposed SPSO-TVAC approach can provide a higher MSR than the other PSO methods. It is potentially applicable to risk management of profit variation of GenCo in spot market.
Aggregators’ Optimal Bidding Strategy in Sequential Day-Ahead and Intraday Electricity Spot Markets
Directory of Open Access Journals (Sweden)
Xiaolin Ayón
2017-04-01
Full Text Available This paper proposes a probabilistic optimization method that produces optimal bidding curves to be submitted by an aggregator to the day-ahead electricity market and the intraday market, considering the flexible demand of his customers (based in time dependent resources such as batteries and shiftable demand and taking into account the possible imbalance costs as well as the uncertainty of forecasts (market prices, demand, and renewable energy sources (RES generation. The optimization strategy aims to minimize the total cost of the traded energy over a whole day, taking into account the intertemporal constraints. The proposed formulation leads to the solution of different linear optimization problems, following the natural temporal sequence of electricity spot markets. Intertemporal constraints regarding time dependent resources are fulfilled through a scheduling process performed after the day-ahead market clearing. Each of the different problems is of moderate dimension and requires short computation times. The benefits of the proposed strategy are assessed comparing the payments done by an aggregator over a sample period of one year following different deterministic and probabilistic strategies. Results show that probabilistic strategy reports better benefits for aggregators participating in power markets.
Optimizing the 3R study strategy to learn from text
Reijners, Pauline; Kester, Liesbeth; Wetzels, Sandra; Kirschner, Paul A.
2013-01-01
Reijners, P. B. G., Kester, L., Wetzels, S. A. J., & Kirschner, P. A. (2013, 29 May). Optimizing the 3R study strategy to learn from text. Presentation at plenary meeting Learning & Cogntion, Heerlen, The Netherlands.
Optimizing the 3R study strategy to learn from text
Reijners, Pauline; Kester, Liesbeth; Wetzels, Sandra; Kirschner, Paul A.
2012-01-01
Reijners, P. B. G., Kester, L., Wetzels, S. A. J., & Kirschner, P. A. (2012, 21 November). Optimizing the 3R study strategy to learn from text. Presentation at research meeting Educational and Developmental Psychology, Erasmus University, Rotterdam, The Netherlands.
Optimizing the 3R study strategy to learn from text
Reijners, Pauline; Kester, Liesbeth; Wetzels, Sandra; Kirschner, Paul A.
2013-01-01
Reijners, P. B. G., Kester, L., Wetzels, S. A. J., & Kirschner, P. A. (2013, 7 November). Optimizing the 3R study strategy to learn from text. Paper presented at the ICO National Fall School, Maastricht, The Netherlands.
Strategy optimization for controlled Markov process with descriptive complexity constraint
Institute of Scientific and Technical Information of China (English)
JIA QingShan; ZHAO QianChuan
2009-01-01
Due to various advantages in storage and Implementation,simple strategies are usually preferred than complex strategies when the performances are close.Strategy optimization for controlled Markov process with descriptive complexity constraint provides a general framework for many such problems.In this paper,we first show by examples that the descriptive complexity and the performance of a strategy could be Independent,and use the F-matrix in the No-Free-Lunch Theorem to show the risk that approximating complex strategies may lead to simple strategies that are unboundedly worse in cardinal performance than the original complex strategies.We then develop a method that handles the descriptive complexity constraint directly,which describes simple strategies exactly and only approximates complex strategies during the optimization.The ordinal performance difference between the resulting strategies of this selective approximation method and the global optimum is quantified.Numerical examples on an engine maintenance problem show how this method Improves the solution quality.We hope this work sheds some insights to solving general strategy optimization for controlled Markov procase with descriptive complexity constraint.
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.
Directory of Open Access Journals (Sweden)
kiarash mehrani
2016-07-01
Full Text Available In this study, we analyze contrarian and momentum strategies in periods associated with optimism or pessimism, and we compare them to the normal market sentiment condition. We evaluate the sentiment using the Arms adjusted index. Then, using the vector autoregressive test, we analyze the relationships among sentiment, stock returns, excess returns, and volatility. The results show that the formation of a short-term portfolio in one- and three-month periods of optimism and pessimism do not create additional returns and results in losses. In addition, the outcomes indicate that combining normal market sentiment with behavioral finance strategies increases performances, with more significant results seen using contrarian strategies compared to momentum strategies.
Power consumption optimization strategy for wireless networks
DEFF Research Database (Denmark)
Cornean, Horia; Kumar, Sanjay; Marchetti, Nicola
2011-01-01
in order to reduce the total power consumption in a multi cellular network. We present an algorithm for power optimization under no interference and in presence of interference conditions, targeting to maximize the network capacity. The convergence of the algorithm is guaranteed if the interference...
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.
Optimal Dynamic Advertising Strategy Under Age-Specific Market Segmentation
Krastev, Vladimir
2011-12-01
We consider the model proposed by Faggian and Grosset for determining the advertising efforts and goodwill in the long run of a company under age segmentation of consumers. Reducing this model to optimal control sub problems we find the optimal advertising strategy and goodwill.
Existence of optimal consumption strategies in markets with longevity risk
de Kort, Jan; Vellekoop, M.H.
2017-01-01
Survival bonds are financial instruments with a payoff that depends on human mortality rates. In markets that contain such bonds, agents optimizing expected utility of consumption and terminal wealth can mitigate their longevity risk. To examine how this influences optimal portfolio strategies and c
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...
Health benefit modelling and optimization of vehicular pollution control strategies
Sonawane, Nayan V.; Patil, Rashmi S.; Sethi, Virendra
2012-12-01
This study asserts that the evaluation of pollution reduction strategies should be approached on the basis of health benefits. The framework presented could be used for decision making on the basis of cost effectiveness when the strategies are applied concurrently. Several vehicular pollution control strategies have been proposed in literature for effective management of urban air pollution. The effectiveness of these strategies has been mostly studied as a one at a time approach on the basis of change in pollution concentration. The adequacy and practicality of such an approach is studied in the present work. Also, the assessment of respective benefits of these strategies has been carried out when they are implemented simultaneously. An integrated model has been developed which can be used as a tool for optimal prioritization of various pollution management strategies. The model estimates health benefits associated with specific control strategies. ISC-AERMOD View has been used to provide the cause-effect relation between control options and change in ambient air quality. BenMAP, developed by U.S. EPA, has been applied for estimation of health and economic benefits associated with various management strategies. Valuation of health benefits has been done for impact indicators of premature mortality, hospital admissions and respiratory syndrome. An optimization model has been developed to maximize overall social benefits with determination of optimized percentage implementations for multiple strategies. The model has been applied for sub-urban region of Mumbai city for vehicular sector. Several control scenarios have been considered like revised emission standards, electric, CNG, LPG and hybrid vehicles. Reduction in concentration and resultant health benefits for the pollutants CO, NOx and particulate matter are estimated for different control scenarios. Finally, an optimization model has been applied to determine optimized percentage implementation of specific
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.
Mesh refinement strategy for optimal control problems
Paiva, Luis Tiago; Fontes, Fernando,
2013-01-01
International audience; Direct methods are becoming the most used technique to solve nonlinear optimal control problems. Regular time meshes having equidistant spacing are frequently used. However, in some cases these meshes cannot cope accurately with nonlinear behavior. One way to improve the solution is to select a new mesh with a greater number of nodes. Another way, involves adaptive mesh refinement. In this case, the mesh nodes have non equidistant spacing which allow a non uniform node...
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.
Sleep As A Strategy For Optimizing Performance.
Yarnell, Angela M; Deuster, Patricia
2016-01-01
Recovery is an essential component of maintaining, sustaining, and optimizing cognitive and physical performance during and after demanding training and strenuous missions. Getting sufficient amounts of rest and sleep is key to recovery. This article focuses on sleep and discusses (1) why getting sufficient sleep is important, (2) how to optimize sleep, and (3) tools available to help maximize sleep-related performance. Insufficient sleep negatively impacts safety and readiness through reduced cognitive function, more accidents, and increased military friendly-fire incidents. Sufficient sleep is linked to better cognitive performance outcomes, increased vigor, and better physical and athletic performance as well as improved emotional and social functioning. Because Special Operations missions do not always allow for optimal rest or sleep, the impact of reduced rest and sleep on readiness and mission success should be minimized through appropriate preparation and planning. Preparation includes periods of "banking" or extending sleep opportunities before periods of loss, monitoring sleep by using tools like actigraphy to measure sleep and activity, assessing mental effectiveness, exploiting strategic sleep opportunities, and consuming caffeine at recommended doses to reduce fatigue during periods of loss. Together, these efforts may decrease the impact of sleep loss on mission and performance. 2016.
Discuss Optimal Approaches to Learning Strategy Instruction for EFL Learners
Institute of Scientific and Technical Information of China (English)
邢菊如
2009-01-01
Numerous research studies reveal that learning strategies have played an important role in language learning processes.This paper explores as English teachers.can we impmve students' language proficiency by giving them optimal learning strategy instruction and what approaches are most effective and efficient?
Lu, Can-can; Bai, Long
2017-06-01
The nonlinear dissipation heat devices are proposed by means of generalizing the low-dissipation heat devices to the quadratic order case. The dimensionless formulas of the output (input) power and the efficiency (coefficient of performance) for the nonlinear dissipation heat engines (refrigerators) are derived in terms of characteristic parameters for heat devices and the dimensional analysis. Based on the trade-off criterion, the optimal performance of the nonlinear dissipation heat devices is discussed in depth, and some system-specific properties for the nonlinear dissipation heat devices under the trade-off optimization are also uncovered. Our results may provide practical insight for designing actual heat engines and refrigerators.
Optimal Portfolio Strategy under Rolling Economic Maximum Drawdown Constraints
Xiaojian Yu; Siyu Xie; Weijun Xu
2014-01-01
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 stra...
Quality vs. quantity : energetic and nutritional trade-offs in parental provisioning strategies
Wright, J.; Both, C.; Cotton, P.A.; Bryant, D.
1998-01-01
1. When faced with increased brood demand, parent birds provisioning young in the nest can make a variety of adjustments to their foraging and food allocation strategies. Logical extensions of classic optimal foraging theory predict increased provisioning effort to larger broods to be accompanied
Retailer's optimal policy under inflation in fuzzy environment with trade credit
Yadav, Dharmendra; Singh, S. R.; Kumari, Rachna
2015-03-01
Trade credit plays an important role in financing many industries. In the classical inventory model it is assumed that the buyer must pay for the items as soon as the items are received. In this problem, it is considered that the retailer can pay the supplier either at the end of the credit period or later pay interest on the unpaid amount for the overdue period. Here, the retailer's inventory model for the optimal cycle time and payment time for a retailer is developed. The effects of the inflation rate, deterioration rate and delay in payment have been discussed. The whole study is performed in a fuzzy environment by taking the opportunity cost, interest earned and interest paid rate as a triangular fuzzy number. Fuzzy profit functions, which involve fuzzy arithmetic operation, are defined using the function principle. We use the signed distance method to defuzzify the fuzzy profit function. Moreover, numerical and sensitivity analysis is performed to validate the proposed model.
Comparative analysis of zero aliasing logarithmic mapped optimal trade-off correlation filter
Tehsin, Sara; Rehman, Saad; Bilal, Ahmed; Chaudry, Qaiser; Saeed, Omer; Abbas, Muhammad; Young, Rupert
2017-05-01
Correlation filters are a well established means for target recognition tasks. However, the unintentional effect of circular correlation has a negative influence on the performance of correlation filters as they are implemented in frequency domain. The effects of aliasing are minimized by introducing zero aliasing constraints in the template and test image. In this paper, the comparative analysis of logarithmic zero aliasing optimal trade off correlation filters has been carried out for different types of target distortions. The zero aliasing Maximum Average Correlation Height (MACH) filter has been identified as the best choice based on our research for achieving enhanced results in the presence of any type of variance which are discussed in results section. The reformulation of the MACH expressions with zero aliasing has been made to demonstrate the achievable enhancement to the logarithmic MACH filter in target detection applications.
Estimation and detection information trade-off for x-ray system optimization
Cushing, Johnathan B.; Clarkson, Eric W.; Mandava, Sagar; Bilgin, Ali
2016-05-01
X-ray Computed Tomography (CT) systems perform complex imaging tasks to detect and estimate system parameters, such as a baggage imaging system performing threat detection and generating reconstructions. This leads to a desire to optimize both the detection and estimation performance of a system, but most metrics only focus on one of these aspects. When making design choices there is a need for a concise metric which considers both detection and estimation information parameters, and then provides the user with the collection of possible optimal outcomes. In this paper a graphical analysis of Estimation and Detection Information Trade-off (EDIT) will be explored. EDIT produces curves which allow for a decision to be made for system optimization based on design constraints and costs associated with estimation and detection. EDIT analyzes the system in the estimation information and detection information space where the user is free to pick their own method of calculating these measures. The user of EDIT can choose any desired figure of merit for detection information and estimation information then the EDIT curves will provide the collection of optimal outcomes. The paper will first look at two methods of creating EDIT curves. These curves can be calculated using a wide variety of systems and finding the optimal system by maximizing a figure of merit. EDIT could also be found as an upper bound of the information from a collection of system. These two methods allow for the user to choose a method of calculation which best fits the constraints of their actual system.
Drechsler, Martin
2017-02-01
Auctions have been proposed as alternatives to payments for environmental services when spatial interactions and costs are better known to landowners than to the conservation agency (asymmetric information). Recently, an auction scheme was proposed that delivers optimal conservation in the sense that social welfare is maximized. I examined the social welfare and the budget efficiency delivered by this scheme, where social welfare represents the difference between the monetized ecological benefit and the conservation cost incurred to the landowners and budget efficiency is defined as maximizing the ecological benefit for a given conservation budget. For the analysis, I considered a stylized landscape with land patches that can be used for agriculture or conservation. The ecological benefit was measured by an objective function that increases with increasing number and spatial aggregation of conserved land patches. I compared the social welfare and the budget efficiency of the auction scheme with an agglomeration payment, a policy scheme that considers spatial interactions and that was proposed recently. The auction delivered a higher level of social welfare than the agglomeration payment. However, the agglomeration payment was more efficient budgetarily than the auction, so the comparative performances of the 2 schemes depended on the chosen policy criterion-social welfare or budget efficiency. Both policy criteria are relevant for conservation. Which one should be chosen depends on the problem at hand, for example, whether social preferences should be taken into account in the decision of how much money to invest in conservation or whether the available conservation budget is strictly limited. © 2016 Society for Conservation Biology.
On Global Optimal Sailplane Flight Strategy
Sander, G. J.; Litt, F. X.
1979-01-01
The derivation and interpretation of the necessary conditions that a sailplane cross-country flight has to satisfy to achieve the maximum global flight speed is considered. Simple rules are obtained for two specific meteorological models. The first one uses concentrated lifts of various strengths and unequal distance. The second one takes into account finite, nonuniform space amplitudes for the lifts and allows, therefore, for dolphin style flight. In both models, altitude constraints consisting of upper and lower limits are shown to be essential to model realistic problems. Numerical examples illustrate the difference with existing techniques based on local optimality conditions.
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 stru......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....... 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......, and investments made in the structure. The inspection and maintenance should be performed so that the structural system is operating as much of the time as possible and the cost is kept at a minimum and so that the safety of the structure is satisfactory. Up till now inspection strategies have been based...
Optimality of Spatially Inhomogeneous Search Strategies.
Schwarz, Karsten; Schröder, Yannick; Qu, Bin; Hoth, Markus; Rieger, Heiko
2016-08-05
We consider random search processes alternating stochastically between diffusion and ballistic motion, in which the distribution function of ballistic motion directions varies from point to point in space. The specific space dependence of the directional distribution together with the switching rates between the two modes of motion establishes a spatially inhomogeneous search strategy. We show that the mean first passage times for several standard search problems-narrow escape, reaction partner finding, reaction escape-can be minimized with a directional distribution that is reminiscent of the spatial organization of the cytoskeleton filaments of cells with a centrosome: radial ballistic transport from the center to the periphery and back, and ballistic transport in random directions within a concentric shell of thickness Δ_{opt} along the domain boundary. The results suggest that living cells realize efficient search strategies for various intracellular transport problems economically through a spatial cytoskeleton organization that involves radial microtubules in the central region and only a narrow actin cortex rather than a cell body filled with randomly oriented actin filaments.
Optimality of Spatially Inhomogeneous Search Strategies
Schwarz, Karsten; Schröder, Yannick; Qu, Bin; Hoth, Markus; Rieger, Heiko
2016-08-01
We consider random search processes alternating stochastically between diffusion and ballistic motion, in which the distribution function of ballistic motion directions varies from point to point in space. The specific space dependence of the directional distribution together with the switching rates between the two modes of motion establishes a spatially inhomogeneous search strategy. We show that the mean first passage times for several standard search problems—narrow escape, reaction partner finding, reaction escape—can be minimized with a directional distribution that is reminiscent of the spatial organization of the cytoskeleton filaments of cells with a centrosome: radial ballistic transport from the center to the periphery and back, and ballistic transport in random directions within a concentric shell of thickness Δopt along the domain boundary. The results suggest that living cells realize efficient search strategies for various intracellular transport problems economically through a spatial cytoskeleton organization that involves radial microtubules in the central region and only a narrow actin cortex rather than a cell body filled with randomly oriented actin filaments.
Optimal search strategies on complex networks
Di Patti, Francesca; Piazza, Francesco
2014-01-01
Complex networks are ubiquitous in nature and play a role of paramount importance in many contexts. Internet and the cyberworld, which permeate our everyday life, are self-organized hierarchical graphs. Urban traffic flows on intricate road networks, which impact both transportation design and epidemic control. In the brain, neurons are cabled through heterogeneous connections, which support the propagation of electric signals. In all these cases, the true challenge is to unveil the mechanisms through which specific dynamical features are modulated by the underlying topology of the network. Here, we consider agents randomly hopping along the links of a graph, with the additional possibility of performing long-range hops to randomly chosen disconnected nodes with a given probability. We show that an optimal combination of the two jump rules exists that maximises the efficiency of target search, the optimum reflecting the topology of the network.
Optimization of energy planning strategies in municipalities
DEFF Research Database (Denmark)
Petersen, Jens-Phillip
The paper evaluates the current status of community energy planning in northern Europe via a review of literature, practice and the performance of a barrier analysis for successful community energy planning. Main findings of the paper are that current community energy planning lacks a systematic...... approach, suffers from insufficient information, tools and resources. Municipalities are often unable to take on a steering role in community energy planning. To overcome these barriers and guide municipalities in the pre-project phase, a decision-support methodology, based on community energy profiles...... (CEP), is presented. The methodology was applied in a case study in Germany. With CEPs, a possibility to merge qualitative data from local settings into generic energy modelling is shown, which could contribute to improved community energy strategies....
Optimal Portfolio Strategy under Rolling Economic Maximum Drawdown Constraints
Directory of Open Access Journals (Sweden)
Xiaojian Yu
2014-01-01
Full Text Available This paper deals with the problem of optimal portfolio strategy under the constraints of rolling economic maximum drawdown. A more practical strategy is developed by using rolling Sharpe ratio in computing the allocation proportion in contrast to existing models. Besides, another novel strategy named “REDP strategy” is further proposed, which replaces the rolling economic drawdown of the portfolio with the rolling economic drawdown of the risky asset. The simulation tests prove that REDP strategy can ensure the portfolio to satisfy the drawdown constraint and outperforms other strategies significantly. An empirical comparison research on the performances of different strategies is carried out by using the 23-year monthly data of SPTR, DJUBS, and 3-month T-bill. The investment cases of single risky asset and two risky assets are both studied in this paper. Empirical results indicate that the REDP strategy successfully controls the maximum drawdown within the given limit and performs best in both return and risk.
Directory of Open Access Journals (Sweden)
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.
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.)
Impact of information cost and switching of trading strategies in an artificial stock market
Liu, Yi-Fang; Zhang, Wei; Xu, Chao; Vitting Andersen, Jørgen; Xu, Hai-Chuan
2014-08-01
This paper studies the switching of trading strategies and its effect on the market volatility in a continuous double auction market. We describe the behavior when some uninformed agents, who we call switchers, decide whether or not to pay for information before they trade. By paying for the information they behave as informed traders. First we verify that our model is able to reproduce some of the stylized facts in real financial markets. Next we consider the relationship between switching and the market volatility under different structures of investors. We find that there exists a positive relationship between the market volatility and the percentage of switchers. We therefore conclude that the switchers are a destabilizing factor in the market. However, for a given fixed percentage of switchers, the proportion of switchers that decide to buy information at a given moment of time is negatively related to the current market volatility. In other words, if more agents pay for information to know the fundamental value at some time, the market volatility will be lower. This is because the market price is closer to the fundamental value due to information diffusion between switchers.
Optimized Information Transmission Scheduling Strategy Oriented to Advanced Metering Infrastructure
Directory of Open Access Journals (Sweden)
Weiming Tong
2013-01-01
Full Text Available Advanced metering infrastructure (AMI is considered to be the first step in constructing smart grid. AMI allows customers to make real-time choices about power utilization and enables power utilities to increase the effectiveness of the regional power grids by managing demand load during peak times and reducing unneeded power generation. These initiatives rely heavily on the prompt information transmission inside AMI. Aiming at the information transmission problem, this paper researches the communication scheduling strategy in AMI at a macroscopic view. First, the information flow of AMI is analyzed, and the power users are classified into several grades by their importance. Then, the defect of conventional information transmission scheduling strategy is analyzed. On this basis, two optimized scheduling strategies are proposed. In the wide area, an optimized scheduling strategy based on user importance and time critical is proposed to guarantee the important power users’ information transmission being handled promptly. In the local area, an optimized scheduling strategy based on device and information importance and time critical is proposed to guarantee the important devices and information in AMI user end system being handled promptly. At last, the two optimized scheduling strategies are simulated. The simulation results show that they can effectively improve the real-time performance and reliability of AMI information transmission.
Strategies for optimizing nitrogen use by ruminants
DEFF Research Database (Denmark)
Calsamiglia, S; Ferret, A; Reynolds, C K
2010-01-01
The efficiency of N utilization in ruminants is typically low (around 25%) and highly variable (10% to 40%) compared with the higher efficiency of other production animals. The low efficiency has implications for the production performance and environment. Many efforts have been devoted to improv......The efficiency of N utilization in ruminants is typically low (around 25%) and highly variable (10% to 40%) compared with the higher efficiency of other production animals. The low efficiency has implications for the production performance and environment. Many efforts have been devoted...... to improving the efficiency of N utilization in ruminants, and while major improvements in our understanding of N requirements and metabolism have been achieved, the overall efficiency remains low. In general, maximal efficiency of N utilization will only occur at the expense of some losses in production...... performance. However, optimal production and N utilization may be achieved through the understanding of the key mechanisms involved in the control of N metabolism. Key factors in the rumen include the efficiency of N capture in the rumen (grams of bacterial N per grams of rumen available N...
Optimization of Secondary Concentrators with the Continuous Information Entropy Strategy
Schmidt, Tobias Christian; Ries, Harald
2010-10-01
In this contribution, a method for global optimization of noisy functions, the Continuous Information Entropy Strategy (CIES), is explained and its applicability for the optimization of solar concentrators is shown. The CIES is efficient because all decisions made during optimizations are based on criteria that are derived from the concept of information entropy. Two secondary concentrators have been optimized with the CIES. The optimized secondary concentrators convert circular light distributions of round focal spots to square light distributions to match with the shape of square PV cells. The secondary concentrators are highly efficient and have geometrical concentration ratios of 2.25 and 8 respectively. Part of this material has been published in: T. C. Schmidt, "Information Entropy-Based Decision Making in Optimization", Ph.D. Thesis, Philipps University Marburg, 2010.
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.
Optimization model of vaccination strategy for dengue transmission
Widayani, H.; Kallista, M.; Nuraini, N.; Sari, M. Y.
2014-02-01
Dengue fever is emerging tropical and subtropical disease caused by dengue virus infection. The vaccination should be done as a prevention of epidemic in population. The host-vector model are modified with consider a vaccination factor to prevent the occurrence of epidemic dengue in a population. An optimal vaccination strategy using non-linear objective function was proposed. The genetic algorithm programming techniques are combined with fourth-order Runge-Kutta method to construct the optimal vaccination. In this paper, the appropriate vaccination strategy by using the optimal minimum cost function which can reduce the number of epidemic was analyzed. The numerical simulation for some specific cases of vaccination strategy is shown.
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....... Basically, the control strategies determine the steady state operating points of the wind turbines. Except the control strategies of the individual wind turbines, the wind farm models are similar. Each model consists of a row of 5MW reference wind turbines. In the models we are able to optimize...
Waterpipe industry products and marketing strategies: analysis of an industry trade exhibition.
Jawad, Mohammed; Nakkash, Rima T; Hawkins, Ben; Akl, Elie A
2015-12-01
Understanding product development and marketing strategies of transnational tobacco companies (TTCs) has been of vital importance in developing an effective tobacco control policy. However, comparatively little is known of the waterpipe tobacco industry, which TTCs have recently entered. This study aimed to gain an understanding of waterpipe tobacco products and marketing strategies by visiting a waterpipe trade exhibition. In April 2014, the first author attended an international waterpipe trade exhibition, recording descriptions of products and collecting all available marketing items. We described the purpose and function of all products, and performed a thematic analysis of messages in marketing material. We classified waterpipe products into four categories and noted product variation within categories. Electronic waterpipe products (which mimic electronic cigarettes) rarely appeared on waterpipe tobacco marketing material, but were displayed just as widely. Claims of reduced harm, safety and quality were paramount on marketing materials, regardless of whether they were promoting consumption products (tobacco, tobacco substitutes), electronic waterpipes or accessories. Waterpipe products are diverse in nature and are marketed as healthy and safe products. Furthermore, the development of electronic waterpipe products appears to be closely connected with the electronic cigarette industry, rather than the waterpipe tobacco manufacturers. Tobacco control policy must evolve to take account of the vast and expanding array of waterpipe products, and potentially also charcoal products developed for waterpipe smokers. We recommend that tobacco substitutes be classified as tobacco products. Continued surveillance of the waterpipe industry is warranted. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/
Optimal generator bidding strategies for power and ancillary services
Morinec, Allen G.
As the electric power industry transitions to a deregulated market, power transactions are made upon price rather than cost. Generator companies are interested in maximizing their profits rather than overall system efficiency. A method to equitably compensate generation providers for real power, and ancillary services such as reactive power and spinning reserve, will ensure a competitive market with an adequate number of suppliers. Optimizing the generation product mix during bidding is necessary to maximize a generator company's profits. The objective of this research work is to determine and formulate appropriate optimal bidding strategies for a generation company in both the energy and ancillary services markets. These strategies should incorporate the capability curves of their generators as constraints to define the optimal product mix and price offered in the day-ahead and real time spot markets. In order to achieve such a goal, a two-player model was composed to simulate market auctions for power generation. A dynamic game methodology was developed to identify Nash Equilibria and Mixed-Strategy Nash Equilibria solutions as optimal generation bidding strategies for two-player non-cooperative variable-sum matrix games with incomplete information. These games integrated the generation product mix of real power, reactive power, and spinning reserve with the generators's capability curves as constraints. The research includes simulations of market auctions, where strategies were tested for generators with different unit constraints, costs, types of competitors, strategies, and demand levels. Studies on the capability of large hydrogen cooled synchronous generators were utilized to derive useful equations that define the exact shape of the capability curve from the intersections of the arcs defined by the centers and radial vectors of the rotor, stator, and steady-state stability limits. The available reactive reserve and spinning reserve were calculated given a
Energy Technology Data Exchange (ETDEWEB)
NONE
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 design of coordination control strategy for distributed generation system
Institute of Scientific and Technical Information of China (English)
WANG Ai-hua; Norapon Kanjanapadit
2009-01-01
This paper presents a novel design procedure for optimizing the power distribution strategy in distributed generation system. A coordinating controller, responsible to distribute the total load power request among multiple DG units, is suggested based on the conception of hierarchical control structure in the dynamic system.The optimal control problem was formulated as a nonlinear optimization problem subject to set of constraints.The resulting problem was solved using the Kutm-Tucker method. Computer simulation results demonstrate that the proposed method can provide better efficiency in terms of reducing total costs compared to existing methods.In addition, the proposed optimal load distribution strategy can be easily implemented in real-time thanks to the simplicity of closed-form solutions.
Optimal Watermark Embedding and Detection Strategies Under Limited Detection Resources
Merhav, Neri
2007-01-01
An information-theoretic approach is proposed to watermark embedding and detection under limited detector resources. First, we consider the attack-free scenario under which asymptotically optimal decision regions in the Neyman-Pearson sense are proposed, along with the optimal embedding rule. Later, we explore the case of zero-mean i.i.d. Gaussian covertext distribution with unknown variance under the attack-free scenario. For this case, we propose a lower bound on the exponential decay rate of the false-negative probability and prove that the optimal embedding and detecting strategy is superior to the customary linear, additive embedding strategy in the exponential sense. Finally, these results are extended to the case of memoryless attacks and general worst case attacks. Optimal decision regions and embedding rules are offered, and the worst attack channel is identified.
NEW OPTIMAL LARGE ANGLE MANEUVER STRATEGY FOR SINGLE FLEXIBLE LINK
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
A component synthesis vibration suppression (CSVS) method for flexible structures is put forward. It can eliminate any unwanted orders of flexible vibration modes while achieves desired rigid motion. This method has robustness to uncertainty of frequency, which makes it practical in engineering. Several time optimal and time-fuel optimal control strategies are designed for a kind of single flexible link. Simulation results validate the feasibility of our method.
Optimal Control Strategies in Delayed Sharing Information Structures
Nayyar, Ashutosh; Teneketzis, Demosthenis
2010-01-01
The $n$-step delayed sharing information structure is investigated. This information structure comprises of $K$ controllers that share their information with a delay of $n$ time steps. This information structure is a link between the classical information structure, where information is shared perfectly between the controllers, and a non-classical information structure, where there is no "lateral" sharing of information among the controllers. Structural results for optimal control strategies for systems with such information structures are presented. A sequential methodology for finding the optimal strategies is also derived. The solution approach provides an insight for identifying structural results and sequential decomposition for general decentralized stochastic control problems.
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.
Wang, Jiang; Liu, Hong
2013-10-01
Lead compound optimization plays an important role in new drug discovery and development. The strategies for changing metabolic pathways can modulate pharmacokinetic properties, prolong the half life, improve metabolism stability and bioavailability of lead compounds. The strategies for changing metabolic pathways and improving metabolism stability are reviewed. These methods include blocking metabolic site, reduing lipophilicity, changing ring size, bioisosterism, and prodrug.
A Computationally Efficient Aggregation Optimization Strategy of Model Predictive Control
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
Model Predictive Control (MPC) is a popular technique and has been successfully used in various industrial applications. However, the big drawback of MPC involved in the formidable on-line computational effort limits its applicability to relatively slow and/or small processes with a moderate number of inputs. This paper develops an aggregation optimization strategy for MPC that can improve the computational efficiency of MPC. For the regulation problem, an input decaying aggregation optimization algorithm is presented by aggregating all the original optimized variables on control horizon with the decaying sequence in respect of the current control action.
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
A Competitive and Experiential Assignment in Search Engine Optimization Strategy
Clarke, Theresa B.; Clarke, Irvine, III
2014-01-01
Despite an increase in ad spending and demand for employees with expertise in search engine optimization (SEO), methods for teaching this important marketing strategy have received little coverage in the literature. Using Bloom's cognitive goals hierarchy as a framework, this experiential assignment provides a process for educators who may be…
A Competitive and Experiential Assignment in Search Engine Optimization Strategy
Clarke, Theresa B.; Clarke, Irvine, III
2014-01-01
Despite an increase in ad spending and demand for employees with expertise in search engine optimization (SEO), methods for teaching this important marketing strategy have received little coverage in the literature. Using Bloom's cognitive goals hierarchy as a framework, this experiential assignment provides a process for educators who may be new…
A Competitive and Experiential Assignment in Search Engine Optimization Strategy
Clarke, Theresa B.; Clarke, Irvine, III
2014-01-01
Despite an increase in ad spending and demand for employees with expertise in search engine optimization (SEO), methods for teaching this important marketing strategy have received little coverage in the literature. Using Bloom's cognitive goals hierarchy as a framework, this experiential assignment provides a process for educators who may be new…
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)
OPTIMAL TARIFF SETTING AND ANALYSIS OF INTERNATIONAL TRADE STRATEGIC DETERMINATION%最优关税制定及国际贸易战略决定分析
Institute of Scientific and Technical Information of China (English)
龙麒圣; 李克强
2012-01-01
International trade is wide spread today, therefore interactions in tariffs strategy among countries are quite common in the international market. This paper discussed the problem of government tariff setting in international trade by establishing asymmetric quartet two-stage nested game model. Theoretical analysis showed that developing national trade was better than seclusion and there was an optimal tariff in trade which was superior to that of non-tariff, which would damage interest of others. In an asymmetric model of two countries and a single product with tariff barriers, free trade was not a rational choice under normal circumstances. The Nash equilibrium solution of two countries were both adopting optimal tariff policy, forming Prisoner＇s Dilemma, which could explain the prevalence of trade protection policy in reality.%当今世界国际贸易关系广泛存在，在不完全竞争的国际市场中充满了国家之间贸易政策的关税战略互动．本文建立了非对称的四方两阶段嵌套博弈模型，讨论了国际贸易中的政府关税设定．理论分析结果表明，对任意贸易国而言，开展国际贸易都优于闭关锁国；且存在一个最优关税优于无关税的自由贸易，但这将会损害他国利益．在具有关税壁垒的非对称的两国单一产品贸易模型中，自由贸易在通常情况下并非各国的理性选择，博弈中两国的纳什均衡解是双方均采用最优关税政策，形成囚徒困境，这解释了现实中贸易保护政策盛行的原因．
Immune clonal selection optimization method with combining mutation strategies
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
In artificial immune optimization algorithm, the mutation of immune cells has been considered as the key operator that determines the algorithm performance. Traditional immune optimization algorithms have used a single mutation operator, typically a Gaussian. Using a variety of mutation operators that can be combined during evolution to generate different probability density function could hold the potential for producing better solutions with less computational effort. In view of this, a linear combination mutation operator of Gaussian and Cauchy mutation is presented in this paper, and a novel clonal selection optimization method based on clonal selection principle is proposed also. The simulation results show the combining mutation strategy can obtain the same performance as the best of pure strategies or even better in some cases.
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...
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...
DEFF Research Database (Denmark)
Steiner, Uli; Pfeiffer, Thomas
2007-01-01
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, such as...... 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....
Optimal switching strategies for stochastic geocentric/egocentric navigation
Peleg, O
2015-01-01
Animals use a combination of egocentric navigation driven by the internal integration of environmental cues, interspersed with geocentric course correction and reorientation, often with uncertainty in sensory acquisition of information, planning and execution. Inspired directly by observations of dung beetle navigational strategies that show switching between geocentric and egocentric strategies, we consider the question of optimal strategies for the navigation of an agent along a preferred direction in the presence of multiple sources of noise. We address this using a model that takes the form of a correlated random walk at short time scales that is interspersed with reorientation events that yields a biased random walks at long time scales. We identify optimal alternation schemes and characterize their robustness in the context of noisy sensory acquisition, and performance errors linked with variations in environmental conditions and agent-environment interactions.
Solution of Chemical Dynamic Optimization Using the Simultaneous Strategies
Institute of Scientific and Technical Information of China (English)
LIU Xinggao; CHEN Long; HU Yunqing
2013-01-01
An approach of simultaneous strategies with two novel techniques is proposed to improve the solution accuracy of chemical dynamic optimization problems.The first technique is to handle constraints on control variables based on the finite-element collocation so as to control the approximation error for discrete optimal problems,where a set of control constraints at element knots are integrated with the procedure for optimization leading to a significant gain in the accuracy of the simultaneous strategies.The second technique is to make the mesh refinement more feasible and reliable by introducing length constraints and guideline in designing appropriate element length boundaries,so that the proposed approach becomes more efficient in adjusting elements to track optimal control profile breakpoints and ensure accurate state and control profiles.Four classic benchmarks of dynamic optimization problems are used as illustrations,and the proposed approach is compared with literature reports.The research results reveal that the proposed approach is preferable in improving the solution accuracy of chemical dynamic optimization problem.
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.
Gavrishchaka, Valeriy V.; Kovbasinskaya, Maria; Monina, Maria
2008-11-01
Novelty detection is a very desirable additional feature of any practical classification or forecasting system. Novelty and rare patterns detection is the main objective in such applications as fault/abnormality discovery in complex technical and biological systems, fraud detection and risk management in financial and insurance industry. Although many interdisciplinary approaches for rare event modeling and novelty detection have been proposed, significant data incompleteness due to the nature of the problem makes it difficult to find a universal solution. Even more challenging and much less formalized problem is novelty detection in complex strategies and models where practical performance criteria are usually multi-objective and the best state-of-the-art solution is often not known due to the complexity of the task and/or proprietary nature of the application area. For example, it is much more difficult to detect a series of small insider trading or other illegal transactions mixed with valid operations and distributed over long time period according to a well-designed strategy than a single, large fraudulent transaction. Recently proposed boosting-based optimization was shown to be an effective generic tool for the discovery of stable multi-component strategies/models from the existing parsimonious base strategies/models in financial and other applications. Here we outline how the same framework can be used for novelty and fraud detection in complex strategies and models.
Bio-Mimic Optimization Strategies in Wireless Sensor Networks: A Survey
Directory of Open Access Journals (Sweden)
Md. Akhtaruzzaman Adnan
2013-12-01
Full Text Available 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.
Bio-mimic optimization strategies in wireless sensor networks: a survey.
Adnan, Md Akhtaruzzaman; Abdur Razzaque, Mohammd; Ahmed, Ishtiaque; Isnin, Ismail Fauzi
2013-12-24
For the past 20 years, many authors have focused their investigations on wireless sensor networks. Various issues related to wireless sensor networks such as energy minimization (optimization), compression schemes, self-organizing network algorithms, routing protocols, quality of service management, security, energy harvesting, etc., have been extensively explored. The three most important issues among these are energy efficiency, quality of service and security management. To get the best possible results in one or more of these issues in wireless sensor networks optimization is necessary. Furthermore, in number of applications (e.g., body area sensor networks, vehicular ad hoc networks) these issues might conflict and require a trade-off amongst them. Due to the high energy consumption and data processing requirements, the use of classical algorithms has historically been disregarded. In this context contemporary researchers started using bio-mimetic strategy-based optimization techniques in the field of wireless sensor networks. These techniques are diverse and involve many different optimization algorithms. As far as we know, most existing works tend to focus only on optimization of one specific issue of the three mentioned above. It is high time that these individual efforts are put into perspective and a more holistic view is taken. In this paper we take a step in that direction by presenting a survey of the literature in the area of wireless sensor network optimization concentrating especially on the three most widely used bio-mimetic algorithms, namely, particle swarm optimization, ant colony optimization and genetic algorithm. In addition, to stimulate new research and development interests in this field, open research issues, challenges and future research directions are highlighted.
Directory of Open Access Journals (Sweden)
Srdjan Redzepagic
2009-06-01
Full Text Available The determination of trends and prediction of stock prices is one of the main tasks of the MACD (Moving Average Convergence Divergence and the RVI (Relative Volatility Index indicators of the technical analysis. The research covers the sample representing stocks which are continually traded on the financial market of the Republic of Serbia. Subject of this research is to determine the possibility of MACD and RVI indicators application in investment decision making processes on the financial market of the Republic of Serbia. The main goal of the research is to identify the most profitable parameters of the MACD and RVI indicators as functions of investment strategy optimization on the financial market. The main hypothesis of the research is that the application of the MACD and RVI indicators of technical analysis significantly contributes to investment strategy optimization on the financial market. The applied methodology during the research includes analyses, synthesis and statistical/ mathematical methods with special focus on the method of moving averages. Research results indicate significant possibilities in application of MACD and RVI indicators of technical analysis as functions of making optimum decisions on investment. According to the obtained results it is concluded that the application of the optimized MACD and RVI indicators of technical analysis in decision making process on investing on the financial market significantly contributes maximization of profitability on investments.
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.
Cellular trade-offs and optimal resource allocation during cyanobacterial diurnal growth.
Reimers, Alexandra-M; Knoop, Henning; Bockmayr, Alexander; Steuer, Ralf
2017-07-18
Cyanobacteria are an integral part of Earth's biogeochemical cycles and a promising resource for the synthesis of renewable bioproducts from atmospheric CO2 Growth and metabolism of cyanobacteria are inherently tied to the diurnal rhythm of light availability. As yet, however, insight into the stoichiometric and energetic constraints of cyanobacterial diurnal growth is limited. Here, we develop a computational framework to investigate the optimal allocation of cellular resources during diurnal phototrophic growth using a genome-scale metabolic reconstruction of the cyanobacterium Synechococcus elongatus PCC 7942. We formulate phototrophic growth as an autocatalytic process and solve the resulting time-dependent resource allocation problem using constraint-based analysis. Based on a narrow and well-defined set of parameters, our approach results in an ab initio prediction of growth properties over a full diurnal cycle. The computational model allows us to study the optimality of metabolite partitioning during diurnal growth. The cyclic pattern of glycogen accumulation, an emergent property of the model, has timing characteristics that are in qualitative agreement with experimental findings. The approach presented here provides insight into the time-dependent resource allocation problem of phototrophic diurnal growth and may serve as a general framework to assess the optimality of metabolic strategies that evolved in phototrophic organisms under diurnal conditions.
An optimal routing strategy on scale-free networks
Yang, Yibo; Zhao, Honglin; Ma, Jinlong; Qi, Zhaohui; Zhao, Yongbin
Traffic is one of the most fundamental dynamical processes in networked systems. With the traditional shortest path routing (SPR) protocol, traffic congestion is likely to occur on the hub nodes on scale-free networks. In this paper, we propose an improved optimal routing (IOR) strategy which is based on the betweenness centrality and the degree centrality of nodes in the scale-free networks. With the proposed strategy, the routing paths can accurately bypass hub nodes in the network to enhance the transport efficiency. Simulation results show that the traffic capacity as well as some other indexes reflecting transportation efficiency are further improved with the IOR strategy. Owing to the significantly improved traffic performance, this study is helpful to design more efficient routing strategies in communication or transportation systems.
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...
Research of stochastic weight strategy for extended particle swarm optimizer
Institute of Scientific and Technical Information of China (English)
XU Jun-jie; YUE Xin; XIN Zhan-hong
2008-01-01
To improve the performance of extended particle swarm optimizer, a novel means of stochastic weight deployment is proposed for the iterative equation of velocity updation. In this scheme, one of the weights is specified to a random number within the range of [0, 1] and the other two remain constant configurations. The simulations show that this weight strategy outperforms the previous deterministic approach with respect to success rate and convergence speed. The experi- ments also reveal that if the weight for global best neighbor is specified to a stochastic number, extended particle swarm optimizer achieves high and robust performance on the given multi-modal function.
Optimal search strategies on complex multi-linked networks
Di Patti, Francesca; Fanelli, Duccio; Piazza, Francesco
2015-01-01
In this paper we consider the problem of optimal search strategies on multi-linked networks, i.e. graphs whose nodes are endowed with several independent sets of links. We focus preliminarily on agents randomly hopping along the links of a graph, with the additional possibility of performing non-local hops to randomly chosen nodes with a given probability. We show that an optimal combination of the two jump rules exists that maximises the efficiency of target search, the optimum reflecting the topology of the network. We then generalize our results to multi-linked networks with an arbitrary number of mutually interfering link sets. PMID:25950716
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
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...... 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....
Survey of E-Commerce Modeling and Optimization Strategies
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
Electronic commerce is impacting almost all commercial activities. The resulting emerging commercial activities bring with them many new modeling and optimization problems. This survey reviews pioneering works in this new area, covering topics in advertising strategy, web page design, automatic pricing, auction methods, brokerage strategy, and customer behavior analysis. Mathematical models for problems in these areas and their solution algorithms are discussed. In addition to presenting and commenting on these works, we also discuss possible extensions and related problems. The objective of this survey is to encourage more researchers to pay attention to this emerging area.
Acceleration of quantum optimal control theory algorithms with mixing strategies.
Castro, Alberto; Gross, E K U
2009-05-01
We propose the use of mixing strategies to accelerate the convergence of the common iterative algorithms utilized in quantum optimal control theory (QOCT). We show how the nonlinear equations of QOCT can be viewed as a "fixed-point" nonlinear problem. The iterative algorithms for this class of problems may benefit from mixing strategies, as it happens, e.g., in the quest for the ground-state density in Kohn-Sham density-functional theory. We demonstrate, with some numerical examples, how the same mixing schemes utilized in this latter nonlinear problem may significantly accelerate the QOCT iterative procedures.
Optimal intervention strategies for cholera outbreak by education and chlorination
Bakhtiar, Toni
2016-01-01
This paper discusses the control of infectious diseases in the framework of optimal control approach. A case study on cholera control was studied by considering two control strategies, namely education and chlorination. We distinct the former control into one regarding person-to-person behaviour and another one concerning person-to-environment conduct. Model are divided into two interacted populations: human population which follows an SIR model and pathogen population. Pontryagin maximum principle was applied in deriving a set of differential equations which consists of dynamical and adjoin systems as optimality conditions. Then, the fourth order Runge-Kutta method was exploited to numerically solve the equation system. An illustrative example was provided to assess the effectiveness of the control strategies toward a set of control scenarios.
A NEW STOCHASTIC OPTIMAL CONTROL STRATEGY FOR HYSTERETIC MR DAMPERS
Institute of Scientific and Technical Information of China (English)
YingZuguang; NiYiqing; KoJanming
2004-01-01
A new stochastic optimal control strategy for randomly excited quasi-integrable Hamiltonian systems using magneto-theological (MR) dampers is proposed. The dynamic behavior of an MR damper is characterized by the Bouc-Wen hysteretic model. The control force produced by the MR damper is separated into a passive part incorporated in the uncontrolled system and a semi-active part to be determined. The system combining the Bouc-Wen hysteretic force is converted into an equivalent non-hysteretic nonlinear stochastic control system. Then Ito stochastic differential equations are derived from the equivalent system by using the stochastic averaging method. A dynamical programming equation for the controlled diffusion processes is established based on the stochastic dynamical programming principle. The non-clipping nonlinear optimal control law is obtained for a certain performance index by minimizing the dynamical programming equation. Finally, an example is given to illustrate the application and effectiveness of the proposed control strategy.
Using Cotton Model Simulations to Estimate Optimally Profitable Irrigation Strategies
Mauget, S. A.; Leiker, G.; Sapkota, P.; Johnson, J.; Maas, S.
2011-12-01
In recent decades irrigation pumping from the Ogallala Aquifer has led to declines in saturated thickness that have not been compensated for by natural recharge, which has led to questions about the long-term viability of agriculture in the cotton producing areas of west Texas. Adopting irrigation management strategies that optimize profitability while reducing irrigation waste is one way of conserving the aquifer's water resource. Here, a database of modeled cotton yields generated under drip and center pivot irrigated and dryland production scenarios is used in a stochastic dominance analysis that identifies such strategies under varying commodity price and pumping cost conditions. This database and analysis approach will serve as the foundation for a web-based decision support tool that will help producers identify optimal irrigation treatments under specified cotton price, electricity cost, and depth to water table conditions.
Study on Stochastic Optimal Electric Power Procurement Strategies with Uncertain Market Prices
Sakchai, Siripatanakulkhajorn; Saisho, Yuichi; Fujii, Yasumasa; Yamaji, Kenji
The player in deregulated electricity markets can be categorized into three groups of GENCO (Generator Companies), TRNASCO (Transmission Companies), DISCO (Distribution Companies). This research focuses on the role of Distribution Companies, which purchase electricity from market at randomly fluctuating prices, and provide it to their customers at given fixed prices. Therefore Distribution companies have to take the risk stemming from price fluctuation of electricity instead of the customers. This entails the necessity to develop a certain method to make an optimal strategy for electricity procurement. In such a circumstance, this research has the purpose for proposing the mathematical method based on stochastic dynamic programming to evaluate the value of a long-term bilateral contract of electricity trade, and also a project of combination of the bilateral contract and power generation with their own generators for procuring electric power in deregulated market.
Optimization of reliability allocation strategies through use of genetic algorithms
Energy Technology Data Exchange (ETDEWEB)
Campbell, J.E.; Painton, L.A.
1996-08-01
This paper examines a novel optimization technique called genetic algorithms and its application to the optimization of reliability allocation strategies. Reliability allocation should occur in the initial stages of design, when the objective is to determine an optimal breakdown or allocation of reliability to certain components or subassemblies in order to meet system specifications. The reliability allocation optimization is applied to the design of a cluster tool, a highly complex piece of equipment used in semiconductor manufacturing. The problem formulation is presented, including decision variables, performance measures and constraints, and genetic algorithm parameters. Piecewise ``effort curves`` specifying the amount of effort required to achieve a certain level of reliability for each component of subassembly are defined. The genetic algorithm evolves or picks those combinations of ``effort`` or reliability levels for each component which optimize the objective of maximizing Mean Time Between Failures while staying within a budget. The results show that the genetic algorithm is very efficient at finding a set of robust solutions. A time history of the optimization is presented, along with histograms or the solution space fitness, MTBF, and cost for comparative purposes.
Success and failure of technical trading strategies in the cocoa futures market
Boswijk, P.; Griffioen, G.A.W.; Hommes, C.
2001-01-01
A large set of 5350 trend following technical trading rules is applied to LIFFE and CSCE cocoa futures prices, and to the Pound-Dollar exchange rate, in the period 1983:1-1997:6. We find that 72% of the trading rules generates positive profits, even when correcting for transaction and borrowing
DEFF Research Database (Denmark)
Wang, Qi
and DR resources, and upwardly trading in the TL real-time market, resulting in a proactive manner. The DL aggregator (DA) is dened to manage these small-scale and dispersed DGs and DRs. A methodology is proposed in this thesis for a proactive DISCO (PDISCO) to strategically trade with DAs...
Success and failure of technical trading strategies in the cocoa futures market
Boswijk, P.; Griffioen, G.A.W.; Hommes, C.
2001-01-01
A large set of 5350 trend following technical trading rules is applied to LIFFE and CSCE cocoa futures prices, and to the Pound-Dollar exchange rate, in the period 1983:1-1997:6. We find that 72% of the trading rules generates positive profits, even when correcting for transaction and borrowing cost
Optimal sampling strategies for detecting zoonotic disease epidemics.
Ferguson, Jake M; Langebrake, Jessica B; Cannataro, Vincent L; Garcia, Andres J; Hamman, Elizabeth A; Martcheva, Maia; Osenberg, Craig W
2014-06-01
The early detection of disease epidemics reduces the chance of successful introductions into new locales, minimizes the number of infections, and reduces the financial impact. We develop a framework to determine the optimal sampling strategy for disease detection in zoonotic host-vector epidemiological systems when a disease goes from below detectable levels to an epidemic. We find that if the time of disease introduction is known then the optimal sampling strategy can switch abruptly between sampling only from the vector population to sampling only from the host population. We also construct time-independent optimal sampling strategies when conducting periodic sampling that can involve sampling both the host and the vector populations simultaneously. Both time-dependent and -independent solutions can be useful for sampling design, depending on whether the time of introduction of the disease is known or not. We illustrate the approach with West Nile virus, a globally-spreading zoonotic arbovirus. Though our analytical results are based on a linearization of the dynamical systems, the sampling rules appear robust over a wide range of parameter space when compared to nonlinear simulation models. Our results suggest some simple rules that can be used by practitioners when developing surveillance programs. These rules require knowledge of transition rates between epidemiological compartments, which population was initially infected, and of the cost per sample for serological tests.
Wilasang, Chaiwat; Wiratsudakul, Anuwat; Chadsuthi, Sudarat
2016-01-01
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. PMID:27110273
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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.
Statistical Arbitrage and Optimal Trading with Transaction Costs in Futures Markets
Tsagaris, Theodoros
2008-01-01
We consider the Brownian market model and the problem of expected utility maximization of terminal wealth. We, specifically, examine the problem of maximizing the utility of terminal wealth under the presence of transaction costs of a fund/agent investing in futures markets. We offer some preliminary remarks about statistical arbitrage strategies and we set the framework for futures markets, and introduce concepts such as margin, gearing and slippage. The setting is of discrete time, and the price evolution of the futures prices is modelled as discrete random sequence involving Ito's sums. We assume the drift and the Brownian motion driving the return process are non-observable and the transaction costs are represented by the bid-ask spread. We provide explicit solution to the optimal portfolio process, and we offer an example using logarithmic utility.
Incorporate Energy Strategy into Particle Swarm Optimizer Algorithm
Institute of Scientific and Technical Information of China (English)
ZHANG Lun; DONG De-cun; LU Yan; CHEN Lan
2008-01-01
The issue of optimizing the dynamic parameters in Particle Swarm Optimizer (PSO) is addressed in this paper.An algorithm is designed which makes all particles originally endowed with a certain level energy, what here we define as EPSO (Energy Strategy PSO).During the iterative process of PSO algorithm, the Inertia Weight is updated according to the calculation of the particle's energy.The portion ratio of the current residual energy to the initial endowed energy is used as the parameter Inertia Weight which aims to update the particles' velocity efficiently.By the simulation in a graph theoritical and a functional optimization problem respectively, it could be easily found that the rate of convergence in EPSO is obviously increased.
Infomax strategies for an optimal balance between exploration and exploitation
Reddy, Gautam; Vergassola, Massimo
2016-01-01
Proper balance between exploitation and exploration is what makes good decisions, which achieve high rewards like payoff or evolutionary fitness. The Infomax principle postulates that maximization of information directs the function of diverse systems, from living systems to artificial neural networks. While specific applications are successful, the validity of information as a proxy for reward remains unclear. Here, we consider the multi-armed bandit decision problem, which features arms (slot-machines) of unknown probabilities of success and a player trying to maximize cumulative payoff by choosing the sequence of arms to play. We show that an Infomax strategy (Info-p) which optimally gathers information on the highest mean reward among the arms saturates known optimal bounds and compares favorably to existing policies. The highest mean reward considered by Info-p is not the quantity actually needed for the choice of the arm to play, yet it allows for optimal tradeoffs between exploration and exploitation.
Optimal Constrained Resource Allocation Strategies under Low Risk Circumstances
Andreica, Mugurel Ionut; Visan, Costel
2009-01-01
In this paper we consider multiple constrained resource allocation problems, where the constraints can be specified by formulating activity dependency restrictions or by using game-theoretic models. All the problems are focused on generic resources, with a few exceptions which consider financial resources in particular. The problems consider low-risk circumstances and the values of the uncertain variables which are used by the algorithms are the expected values of the variables. For each of the considered problems we propose novel algorithmic solutions for computing optimal resource allocation strategies. The presented solutions are optimal or near-optimal from the perspective of their time complexity. The considered problems have applications in a broad range of domains, like workflow scheduling in industry (e.g. in the mining and metallurgical industry) or the financial sector, motion planning, facility location and data transfer or job scheduling and resource management in Grids, clouds or other distribute...
Optimizing selection of decentralized stormwater management strategies in urbanized regions
Yu, Z.; Montalto, F.
2011-12-01
A variety of decentralized stormwater options are available for implementation in urbanized regions. These strategies, which include bio-retention, porous pavement, green roof etc., vary in terms of cost, ability to reduce runoff, and site applicability. This paper explores the tradeoffs between different types of stormwater control meastures that could be applied in a typical urban study area. A nested optimization strategy first identifies the most cost-effective (e.g. runoff reduction / life cycle cost invested ) options for individual land parcel typologies, and then scales up the results with detailed attention paid to uncertainty in adoption rates, life cycle costs, and hydrologic performance. The study is performed with a custom built stochastic rainfall-runoff model (Monte Carlo techniques are used to quantify uncertainties associated with phased implementation of different strategies and different land parcel typologies under synthetic precipitation ensembles). The results are presented as a comparison of cost-effectiveness over the time span of 30 years, and state an optimized strategy on the cumulative cost-effectiveness over the period.
Optimization of the Import Policy as a Factor of Foreign Trade Safety
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Vlasiuk Taras O.
2015-03-01
Full Text Available The article considers the issues of ensuring the state foreign trade safety by using the tools of import policy. The analysis of the current condition of Ukraine import and import policy was carried out, the individual tools of the import policy were analyzed, a list of problems with the import that threaten separate industries of Ukraine was given, the measures, which implementation will positively affect the level of foreign trade safety of the state, were proposed.
VI International Workshop on Nature Inspired Cooperative Strategies for Optimization
Otero, Fernando; Masegosa, Antonio
2014-01-01
Biological and other natural processes have always been a source of inspiration for computer science and information technology. Many emerging problem solving techniques integrate advanced evolution and cooperation strategies, encompassing a range of spatio-temporal scales for visionary conceptualization of evolutionary computation. This book is a collection of research works presented in the VI International Workshop on Nature Inspired Cooperative Strategies for Optimization (NICSO) held in Canterbury, UK. Previous editions of NICSO were held in Granada, Spain (2006 & 2010), Acireale, Italy (2007), Tenerife, Spain (2008), and Cluj-Napoca, Romania (2011). NICSO 2013 and this book provides a place where state-of-the-art research, latest ideas and emerging areas of nature inspired cooperative strategies for problem solving are vigorously discussed and exchanged among the scientific community. The breadth and variety of articles in this book report on nature inspired methods and applications such as Swarm In...
Managing Carbon Footprints under the Trade Credit
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Xiaohong Chen
2017-07-01
Full Text Available We investigate how the retailer adjusts optimal ordering policy in the presence of cap-and-trade system and trade credit, and the corresponding changes of the retailer’s total costs and carbon footprint. Trade credit is one of the most used short-term financing tools. Our study shows that carbon emissions trading will shorten the ordering cycle for products that emit more carbon dioxide during the storage stage, and therefore reduce the buying behavior stimulation effect of trade credit on these products. Under the cap-and-trade system, the retailer’s total cost may increase or decrease, depending on the combination of carbon cap allocated to the retailer and the carbon price. Moreover, trade credit and the corresponding cost of capital affect the retailer’s carbon emission reduction strategy by changing the retailers’ consolidated cost during the ordering and inventory holding stages.
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...
Directory of Open Access Journals (Sweden)
Dr.B.Subramanyam
2013-02-01
Full Text Available In this paper, Particle Swarm optimization(PSO and Artificial Bee Colony (ABC algorithms are used to determine the optimal bidding strategy in competitive auction market implementation. The deregulated power industry meets the challenges of increase their profits and also minimize the associadted risks of the system. Themarket includes generating companies(Gencos and large Consumers. The demand prediction of the system has been determined by the neural network, which is trained by using the previous day demand dataset, the training process is achieved by the back propagation algorithm. The fitness of the system compared with PSO and ABC technique, the maximized fitness is the optimal bidding strategy of the system . The results for two techniques will be analyzed in this paper. The implementation of the two techniques could be implemented in theMATLAB Platform.
Nonlinear trading models through Sharpe Ratio maximization.
Choey, M; Weigend, A S
1997-08-01
While many trading strategies are based on price prediction, traders in financial markets are typically interested in optimizing risk-adjusted performance such as the Sharpe Ratio, rather than the price predictions themselves. This paper introduces an approach which generates a nonlinear strategy that explicitly maximizes the Sharpe Ratio. It is expressed as a neural network model whose output is the position size between a risky and a risk-free asset. The iterative parameter update rules are derived and compared to alternative approaches. The resulting trading strategy is evaluated and analyzed on both computer-generated data and real world data (DAX, the daily German equity index). Trading based on Sharpe Ratio maximization compares favorably to both profit optimization and probability matching (through cross-entropy optimization). The results show that the goal of optimizing out-of-sample risk-adjusted profit can indeed be achieved with this nonlinear approach.
Optimizing strategy software for repetitive construction projects within multi-mode resources
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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.
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Liwei Ju
2016-01-01
Full Text Available In China, the rapid construction of ultra-high-voltage (UHV transmission lines promotes interregional resource optimizing configuration and interregional power system planning. This paper analyzes external environment of interregional power system planning from geographical, technical, and policy environments. Then, the paper takes the minimum system investment cost as the optimization objective and constructs the optimization model of interregional power system planning considering carbon emissions trading (CET and renewable energy quota mechanism (REQ. Finally, this paper sets base scenario, carbon emissions trading scenario, renewable energy quota mechanism scenario, and comprehensive scenario for case simulation. The results show that interregional power system planning could connect power grids in different regions, enlarge wind power consumption space, and relieve the inconformity problem between power resource and load demand. CET and REQ can increase the installed proportion of clean energy and reduce carbon dioxide emissions, but the cost of transmission lines construction and system reserve will increase correspondingly. The optimization effect of REQ on power system planning is better than CET. When they are both introduced, the power structure will reach the best, carbon dioxide emissions will achieve the minimum, and comprehensive benefits will become more balanced.
Particle Swarm Optimization With Interswarm Interactive Learning Strategy.
Qin, Quande; Cheng, Shi; Zhang, Qingyu; Li, Li; Shi, Yuhui
2016-10-01
The learning strategy in the canonical particle swarm optimization (PSO) algorithm is often blamed for being the primary reason for loss of diversity. Population diversity maintenance is crucial for preventing particles from being stuck into local optima. In this paper, we present an improved PSO algorithm with an interswarm interactive learning strategy (IILPSO) by overcoming the drawbacks of the canonical PSO algorithm's learning strategy. IILPSO is inspired by the phenomenon in human society that the interactive learning behavior takes place among different groups. Particles in IILPSO are divided into two swarms. The interswarm interactive learning (IIL) behavior is triggered when the best particle's fitness value of both the swarms does not improve for a certain number of iterations. According to the best particle's fitness value of each swarm, the softmax method and roulette method are used to determine the roles of the two swarms as the learning swarm and the learned swarm. In addition, the velocity mutation operator and global best vibration strategy are used to improve the algorithm's global search capability. The IIL strategy is applied to PSO with global star and local ring structures, which are termed as IILPSO-G and IILPSO-L algorithm, respectively. Numerical experiments are conducted to compare the proposed algorithms with eight popular PSO variants. From the experimental results, IILPSO demonstrates the good performance in terms of solution accuracy, convergence speed, and reliability. Finally, the variations of the population diversity in the entire search process provide an explanation why IILPSO performs effectively.
Energy Optimal Control Strategy of PHEV Based on PMP Algorithm
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Tiezhou Wu
2017-01-01
Full Text Available Under the global voice of “energy saving” and the current boom in the development of energy storage technology at home and abroad, energy optimal control of the whole hybrid electric vehicle power system, as one of the core technologies of electric vehicles, is bound to become a hot target of “clean energy” vehicle development and research. This paper considers the constraints to the performance of energy storage system in Parallel Hybrid Electric Vehicle (PHEV, from which lithium-ion battery frequently charges/discharges, PHEV largely consumes energy of fuel, and their are difficulty in energy recovery and other issues in a single cycle; the research uses lithium-ion battery combined with super-capacitor (SC, which is hybrid energy storage system (Li-SC HESS, working together with internal combustion engine (ICE to drive PHEV. Combined with PSO-PI controller and Li-SC HESS internal power limited management approach, the research proposes the PHEV energy optimal control strategy. It is based on revised Pontryagin’s minimum principle (PMP algorithm, which establishes the PHEV vehicle simulation model through ADVISOR software and verifies the effectiveness and feasibility. Finally, the results show that the energy optimization control strategy can improve the instantaneity of tracking PHEV minimum fuel consumption track, implement energy saving, and prolong the life of lithium-ion batteries and thereby can improve hybrid energy storage system performance.
Cost Effectiveness Analysis of Optimal Malaria Control Strategies in Kenya
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Gabriel Otieno
2016-03-01
Full Text Available Malaria remains a leading cause of mortality and morbidity among the children under five and pregnant women in sub-Saharan Africa, but it is preventable and controllable provided current recommended interventions are properly implemented. Better utilization of malaria intervention strategies will ensure the gain for the value for money and producing health improvements in the most cost effective way. The purpose of the value for money drive is to develop a better understanding (and better articulation of costs and results so that more informed, evidence-based choices could be made. Cost effectiveness analysis is carried out to inform decision makers on how to determine where to allocate resources for malaria interventions. This study carries out cost effective analysis of one or all possible combinations of the optimal malaria control strategies (Insecticide Treated Bednets—ITNs, Treatment, Indoor Residual Spray—IRS and Intermittent Preventive Treatment for Pregnant Women—IPTp for the four different transmission settings in order to assess the extent to which the intervention strategies are beneficial and cost effective. For the four different transmission settings in Kenya the optimal solution for the 15 strategies and their associated effectiveness are computed. Cost-effective analysis using Incremental Cost Effectiveness Ratio (ICER was done after ranking the strategies in order of the increasing effectiveness (total infections averted. The findings shows that for the endemic regions the combination of ITNs, IRS, and IPTp was the most cost-effective of all the combined strategies developed in this study for malaria disease control and prevention; for the epidemic prone areas is the combination of the treatment and IRS; for seasonal areas is the use of ITNs plus treatment; and for the low risk areas is the use of treatment only. Malaria transmission in Kenya can be minimized through tailor-made intervention strategies for malaria control
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.
Hemoglobin optimization and transfusion strategies in patients undergoing cardiac surgery
Institute of Scientific and Technical Information of China (English)
Mahdi; Najafi; David; Faraoni
2015-01-01
Although red blood cells(RBCs) transfusion is sometimes associated with adverse reactions,anemia could also lead to increased morbidity and mortality in highrisk patients. For these reasons,the definition of perioperative strategies that aims to detect and treat preoperative anemia,prevent excessive blood loss,and define "optimal" transfusion algorithms is crucial. Although the treatment with preoperative iron and erythropoietin has been recommended in some specific conditions,several controversies exist regarding the benefit-to-risk balance associated with these treatments. Further studies are needed to better define the indications,dosage,and route of administration for preoperative iron with or without erythropoietin supplementation. Although restrictive transfusion strategies in patients undergoing cardiac surgery have been shown to effectively reduce the incidence and the amount of RBCs transfusion without increase in side effects,some high-risk patients(e.g.,symptomatic acute coronary syndrome) could benefit from higher hemoglobin concentrations. Despite all efforts made last decade,a significant amount of work remains to be done to improve hemoglobin optimization and transfusion strategies in patients undergoing cardiac surgery.
Evolving Nash-optimal poker strategies using evolutionary computation
Institute of Scientific and Technical Information of China (English)
Hanyang QUEK; Chunghoong WOO; Kaychen TAN; Arthur TAY
2009-01-01
This paper focuses on the development of a competitive computer player for the one versus one Texas Hold'em poker using evolutionary algorithms (EA). A Texas Hold'em game engine is first constructed where an efficient odds" calculator is programmed to allow for the abstraction of a player's cards, which yield important but complex information. Effort is directed to realize an optimal player that will play close to the Nash equilibrium (NE) by proposing a new fitness criterion. Preliminary studies on a simplified version of poker highlighted the intransitivity nature of poker.The evolved player displays strategies that are logical but reveals insights that are hard to comprehend e.g., bluffing.The player is then benchmarked against Poki and PSOpti,which is the best heads-up Texas Hold'em artificial intelligence to date and plays closest to the optimal Nash equilibrium. Despite the much constrained chromosomal strategy representation, simulated results verified that evolutionary algorithms are effective in creating strategies that are comparable to Poki and PSOpti in the absence of expert knowledge.
Optimal Bidding Strategy for Renewable Microgrid with Active Network Management
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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.
Inkpen, S Andrew
2016-06-01
Experimental ecologists often invoke trade-offs to describe the constraints they encounter when choosing between alternative experimental designs, such as between laboratory, field, and natural experiments. In making these claims, they tend to rely on Richard Levins' analysis of trade-offs in theoretical model-building. But does Levins' framework apply to experiments? In this paper, I focus this question on one desideratum widely invoked in the modelling literature: generality. Using the case of generality, I assess whether Levins-style treatments of modelling provide workable resources for assessing trade-offs in experimental design. I argue that, of four strategies modellers employ to increase generality, only one may be unproblematically applied to experimental design. Furthermore, modelling desiderata do not have obvious correlates in experimental design, and when we define these desiderata in a way that seem consistent with ecologists' usage, the trade-off framework falls apart. I conclude that a Levins-inspired framework for modelling does not provide the content for a similar approach to experimental practice; this does not, however, mean that it cannot provide the form.
Computer teaching process optimization strategy analysis of thinking ability
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Luo Liang
2016-01-01
Full Text Available As is known to all, computer is a college student in a university course, one of the basic course in the process of education for college students which lay a theoretical foundation for the next professional learning. At the same time, in recent years, countries and universities attach great importance to and focus on computer teaching for young college students, the purpose is to improve students’ thinking ability, eventually to promote college students’ ability to use computational thinking to solve and analyze the problems of daily life. Therefore, this article on how to the calculation of optimization in the process of computer teaching college students thinking ability on further discussion and analysis, and then explore the strategies and methods, so as to promote the computer teaching in the process of the cultivation of thinking ability and optimize the computer
Strategy of Concurrent Optimization for an Assembly Sequence
Institute of Scientific and Technical Information of China (English)
YANG Bo; LIU Lu-ning; ZE Xiang-bo
2005-01-01
An effective constraint release based approach to realize concurrent optimization for an assembly sequence is proposed. To quantify the measurement of assembly efficiency, a mathematical model of concurrency evaluation index was put forward at first, and then a technology to quantify assembly constraints was developed by application of some fuzzy logic algorithms. In the process of concurrent optimization of the assembly sequence, two kinds of constraints were involved. One was self-constraints of components, which was used to evaluate the assemble capability of components under the condition of full-freedom. Another was an assembly constraint between components represented by geometric constraints between points, lines and planes under physical restriction conditions. The concept of connection strength degree (CSD) was introduced as one efficient indicator and the value of it was evaluated by the intersection of the two constraints mentioned above. The equivalent constraints describing the connection weights between components were realized by a well designed constraints reduction, and then the connection weights based complete assembly liaison graph was applied to release virtual connections between components. Under a given threshold value, a decomposition and reconstituting strategy for the graph with the focus on high assembly concurrency was used to realize an optimized assembly concurrency evaluation index. Finally, the availability of the approach was illustrated in an example to optimize the assembly of a shift pump.
Trade-off Assessment of Simplified Routing Models for Short-Term Hydropower Reservoir Optimization
Issao Kuwajima, Julio; Schwanenberg, Dirk; Alvardo Montero, Rodolfo; Mainardi Fan, Fernando; Assis dos Reis, Alberto
2014-05-01
Short-term reservoir optimization, also referred to as model predictive control, integrates model-based forecasts and optimization algorithms to meet multiple management objectives such as water supply, navigation, hydroelectricity generation, environmental obligations and flood protection. It is a valuable decision support tool to handle water-stress conditions or flooding events, and supports decision makers to minimize their impact. If the reservoir management includes downstream control, for example for mitigation flood damages in inundation areas downstream of the operated dam, the flow routing between the dam and the downstream inundation area is of major importance. The unsteady open channel flow in river reaches can be described by the one-dimensional Saint-Venant equations. However, owing to the mathematical complexity of those equations, some simplifications may be required to speed up the computation within the optimization procedure. Another strategy to limit the model runtime is a schematization on a course computational grid. In particular the last measure can introduce significant numerical diffusion into the solution. This is a major drawback, in particular if the reservoir release has steep gradients which we often find in hydropower reservoirs. In this work, four different routing models are assessed concerning their implementation in the predictive control of the Três Marias Reservoir located at the Upper River São Francisco in Brazil: i) a fully dynamic model using the software package SOBEK; ii) a semi-distributed rainfall-runoff model with Muskingum-Cunge routing for the flow reaches of interest, the MGB-IPH (Modelo Hidrológico de Grandes Bacias - Instituto de Pesquisas Hidráulicas); iii) a reservoir routing approach; and iv) a diffusive wave model. The last two models are implemented in the RTC-Tool toolbox. The overall model accuracy between the simplified models in RTC-Tools (iii, iv) and the more sophisticated SOBEK model (i) are
Issues and Strategies in Solving Multidisciplinary Optimization Problems
Patnaik, Surya
2013-01-01
Optimization research at NASA Glenn Research Center has addressed the design of structures, aircraft and airbreathing propulsion engines. The accumulated multidisciplinary design activity is collected under a testbed entitled COMETBOARDS. Several issues were encountered during the solution of the problems. Four issues and the strategies adapted for their resolution are discussed. This is followed by a discussion on analytical methods that is limited to structural design application. An optimization process can lead to an inefficient local solution. This deficiency was encountered during design of an engine component. The limitation was overcome through an augmentation of animation into optimization. Optimum solutions obtained were infeasible for aircraft and airbreathing propulsion engine problems. Alleviation of this deficiency required a cascading of multiple algorithms. Profile optimization of a beam produced an irregular shape. Engineering intuition restored the regular shape for the beam. The solution obtained for a cylindrical shell by a subproblem strategy converged to a design that can be difficult to manufacture. Resolution of this issue remains a challenge. The issues and resolutions are illustrated through a set of problems: Design of an engine component, Synthesis of a subsonic aircraft, Operation optimization of a supersonic engine, Design of a wave-rotor-topping device, Profile optimization of a cantilever beam, and Design of a cylindrical shell. This chapter provides a cursory account of the issues. Cited references provide detailed discussion on the topics. Design of a structure can also be generated by traditional method and the stochastic design concept. Merits and limitations of the three methods (traditional method, optimization method and stochastic concept) are illustrated. In the traditional method, the constraints are manipulated to obtain the design and weight is back calculated. In design optimization, the weight of a structure becomes the
Optimized Control Strategy For Over Loaded Offshore Wind Turbines
DEFF Research Database (Denmark)
Odgaard, Peter Fogh; Knudsen, Torben; Wisniewski, Rafal
2015-01-01
Abstract Optimized control strategy for overloaded offshore wind turbines Introduction Operation and maintenance cost are an important part of cost of energy especially for offshore wind farms. Typically unplanned service is called for due to detection off excessive loads on components, e...... controller tuning for a given wind turbine. It also enables a very safe and robust comparison between a new control strategy and the present one. Main body of abstract Is it true that power de-rating indeed the best way to reduce loads? The power de-rating approach has the drawback of only indirectly...... and service at offshore location, where accessibility can be problematic. The controller objectives are focused directly on the actual objective like lowering of fore aft fatigue loads, instead of using an indirect objective of de-rating the power production of the wind turbine. This means what the wind...
Process of Market Strategy Optimization Using Distributed Computing Systems
Directory of Open Access Journals (Sweden)
Nowicki Wojciech
2015-12-01
Full Text Available If market repeatability is assumed, it is possible with some real probability to deduct short term market changes by making some calculations. The algorithm, based on logical and statistically reasonable scheme to make decisions about opening or closing position on a market, is called an automated strategy. Due to market volatility, all parameters are changing from time to time, so there is need to constantly optimize them. This article describes a team organization process when researching market strategies. Individual team members are merged into small groups, according to their responsibilities. The team members perform data processing tasks through a cascade organization, providing solutions to speed up work related to the use of remote computing resources. They also work out how to store results in a suitable way, according to the type of task, and facilitate the publication of a large amount of results.
Determining the Bayesian optimal sampling strategy in a hierarchical system.
Energy Technology Data Exchange (ETDEWEB)
Grace, Matthew D.; Ringland, James T.; Boggs, Paul T.; Pebay, Philippe Pierre
2010-09-01
Consider a classic hierarchy tree as a basic model of a 'system-of-systems' network, where each node represents a component system (which may itself consist of a set of sub-systems). For this general composite system, we present a technique for computing the optimal testing strategy, which is based on Bayesian decision analysis. In previous work, we developed a Bayesian approach for computing the distribution of the reliability of a system-of-systems structure that uses test data and prior information. This allows for the determination of both an estimate of the reliability and a quantification of confidence in the estimate. Improving the accuracy of the reliability estimate and increasing the corresponding confidence require the collection of additional data. However, testing all possible sub-systems may not be cost-effective, feasible, or even necessary to achieve an improvement in the reliability estimate. To address this sampling issue, we formulate a Bayesian methodology that systematically determines the optimal sampling strategy under specified constraints and costs that will maximally improve the reliability estimate of the composite system, e.g., by reducing the variance of the reliability distribution. This methodology involves calculating the 'Bayes risk of a decision rule' for each available sampling strategy, where risk quantifies the relative effect that each sampling strategy could have on the reliability estimate. A general numerical algorithm is developed and tested using an example multicomponent system. The results show that the procedure scales linearly with the number of components available for testing.
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.
Trade-off between carbon dioxide emissions and logistics costs based on multiobjective optimization
Kim, N.S.; Janic, M.; Van Wee, G.P.
2009-01-01
This paper examines the relationship between the freight transport costs and the carbon dioxide (CO2) emissions in given intermodal and truckonly freight networks. When the trade-off, which is represented as the relationship, is changed, the freight mode share and route choice are also modified. To
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...
Surkov, I.; Ondersteijn, C.J.M.; Oude Lansink, A.G.J.M.
2005-01-01
Quarantine pests and diseases represent a significant threat to agricultural and horticultural production worldwide. Currently, it is recognised that international trade in agricultural products, and especially in plants and plant materials, is a major vector facilitating the spread of quarantine or
Heuristic Portfolio Trading Rules with Capital Gain Taxes
DEFF Research Database (Denmark)
Fischer, Marcel; Gallmeyer, Michael
strategy is not dominated out-of-sample by a variety of optimizing trading strategies, except the parametric portfolios of Brandt, Santa-Clara, and Valkanov (2009). With dividend and realization-based capital gain taxes, the welfare costs of the taxes are large with the cost being as large as 30% of wealth......We study the out-of-sample performance of portfolio trading strategies when an investor faces capital gain taxation and proportional transaction costs. Under no capital gain taxation and no transaction costs, we show that, consistent with DeMiguel, Garlappi, and Uppal (2009), a simple 1/N trading...... 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...
El Hanandeh, Ali; El-Zein, Abbas
2009-07-01
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.
DEFF Research Database (Denmark)
Wang, Qi
and DR resources, and upwardly trading in the TL real-time market, resulting in a proactive manner. The DL aggregator (DA) is dened to manage these small-scale and dispersed DGs and DRs. A methodology is proposed in this thesis for a proactive DISCO (PDISCO) to strategically trade with DAs......-level model is proposed to elaborate the interactions between the PDISCO's bids/offers and the TL market's outcomes. The PDISCO's trading performance features in a bidirectional transaction. In this thesis, replacing the lower-level problems with the primal-dual approach, each proposed bi-level model......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...
Infomax Strategies for an Optimal Balance Between Exploration and Exploitation
Reddy, Gautam; Celani, Antonio; Vergassola, Massimo
2016-06-01
Proper balance between exploitation and exploration is what makes good decisions that achieve high reward, like payoff or evolutionary fitness. The Infomax principle postulates that maximization of information directs the function of diverse systems, from living systems to artificial neural networks. While specific applications turn out to be successful, the validity of information as a proxy for reward remains unclear. Here, we consider the multi-armed bandit decision problem, which features arms (slot-machines) of unknown probabilities of success and a player trying to maximize cumulative payoff by choosing the sequence of arms to play. We show that an Infomax strategy (Info-p) which optimally gathers information on the highest probability of success among the arms, saturates known optimal bounds and compares favorably to existing policies. Conversely, gathering information on the identity of the best arm in the bandit leads to a strategy that is vastly suboptimal in terms of payoff. The nature of the quantity selected for Infomax acquisition is then crucial for effective tradeoffs between exploration and exploitation.
Optimal measurement strategies for effective suppression of drift errors
Energy Technology Data Exchange (ETDEWEB)
Yashchuk, Valeriy V.
2009-04-16
Drifting of experimental set-ups with change of temperature or other environmental conditions is the limiting factor of many, if not all, precision measurements. The measurement error due to a drift is, in some sense, in-between random noise and systematic error. In the general case, the error contribution of a drift cannot be averaged out using a number of measurements identically carried out over a reasonable time. In contrast to systematic errors, drifts are usually not stable enough for a precise calibration. Here a rather general method for effective suppression of the spurious effects caused by slow drifts in a large variety of instruments and experimental set-ups is described. An analytical derivation of an identity, describing the optimal measurement strategies suitable for suppressing the contribution of a slow drift described with a certain order polynomial function, is presented. A recursion rule as well as a general mathematical proof of the identity is given. The effectiveness of the discussed method is illustrated with an application of the derived optimal scanning strategies to precise surface slope measurements with a surface profiler.
Web malware spread modelling and optimal control strategies
Liu, Wanping; Zhong, Shouming
2017-02-01
The popularity of the Web improves the growth of web threats. Formulating mathematical models for accurate prediction of malicious propagation over networks is of great importance. The aim of this paper is to understand the propagation mechanisms of web malware and the impact of human intervention on the spread of malicious hyperlinks. Considering the characteristics of web malware, a new differential epidemic model which extends the traditional SIR model by adding another delitescent compartment is proposed to address the spreading behavior of malicious links over networks. The spreading threshold of the model system is calculated, and the dynamics of the model is theoretically analyzed. Moreover, the optimal control theory is employed to study malware immunization strategies, aiming to keep the total economic loss of security investment and infection loss as low as possible. The existence and uniqueness of the results concerning the optimality system are confirmed. Finally, numerical simulations show that the spread of malware links can be controlled effectively with proper control strategy of specific parameter choice.
Directory of Open Access Journals (Sweden)
Mohsen Khalilpour
2013-02-01
Full Text Available Power companies world-wide have been restructuring their electric power systems from a vertically integrated entity to a deregulated, open-market environment. Previously, electric utilities usually sought to maximize the social welfare of the system with distributional equity as its main operational criterion. The operating paradigm was based on achieving the least-cost system solution while meeting reliability and security margins. This often resulted in investments in generating capacity operating at very low capacity factors. Decommissioning of this type of generating capacity was a natural outcome when the vertically integrated utilities moved over to deregulated market operations. This study proposes an optimizing base and load demand relative binding strategy for generating power apprises of different units in the investigated system. Afterwards, congestion effect in this biding strategy is investigated. The described systems analysis is implemented on 5 and 9 bus systems and optimizing technique in this issue is the Invasive Weed Optimization algorithm; the results are then compared by GA. Finally, examined systems is simulated by using the Power World software; experimental results show that the proposed technique (Invasive Weed Optimization is a high performance by compared GA for the congestion management purposes.
Directory of Open Access Journals (Sweden)
Fábio Neves de Carvalho da Silva Maia
2010-01-01
Full Text Available Este trabalho avalia os retornos e os riscos de estratégias de hedge para as dez principais regiões produtoras de soja do Brasil em relação aos contratos futuros de soja da Chicago Board of Trade (CBOT. Verificou-se que as bases apresentaram padrão bem definido: fortalecimento entre maio e novembro, seguido por enfraquecimento nos seis meses subsequentes. Os hedgers de compra possuem oportunidades de obter retornos brutos maiores, mas os riscos envolvidos nas estratégias de hedge de compra também são maiores. Conclui-se que os contratos de soja em grão da CBOT apresentam diferentes possibilidades de retornos brutos em função do tipo de hedge, do período hedgeado e do contrato utilizado. Logo, as informações disponibilizadas neste trabalho se apresentam como importante subsídio ao processo de tomada de decisão por parte dos agentes da cadeia agroindustrial da soja.This paper analyzes the return and risks of hedging strategies of the major ten soybean producing regions in Brazil concerning Chicago Board of Trade (CBOT future contracts. It was verified that the bases presented a well defined pattern characterized by strengthening from May to November and weakening in the remaining months. Long hedging had larger returns and larger risks comparing with short hedging. The conclusion of this study is that the CBOT soybean contracts present different returns depending on the type of hedging, on the period of hedging, and on the contract used. Therefore, the information presented in this paper is very important to support the decision making process in the Brazilian soybean agricultural system.
Strategy Developed for Selecting Optimal Sensors for Monitoring Engine Health
2004-01-01
Sensor indications during rocket engine operation are the primary means of assessing engine performance and health. Effective selection and location of sensors in the operating engine environment enables accurate real-time condition monitoring and rapid engine controller response to mitigate critical fault conditions. These capabilities are crucial to ensure crew safety and mission success. Effective sensor selection also facilitates postflight condition assessment, which contributes to efficient engine maintenance and reduced operating costs. Under the Next Generation Launch Technology program, the NASA Glenn Research Center, in partnership with Rocketdyne Propulsion and Power, has developed a model-based procedure for systematically selecting an optimal sensor suite for assessing rocket engine system health. This optimization process is termed the systematic sensor selection strategy. Engine health management (EHM) systems generally employ multiple diagnostic procedures including data validation, anomaly detection, fault-isolation, and information fusion. The effectiveness of each diagnostic component is affected by the quality, availability, and compatibility of sensor data. Therefore systematic sensor selection is an enabling technology for EHM. Information in three categories is required by the systematic sensor selection strategy. The first category consists of targeted engine fault information; including the description and estimated risk-reduction factor for each identified fault. Risk-reduction factors are used to define and rank the potential merit of timely fault diagnoses. The second category is composed of candidate sensor information; including type, location, and estimated variance in normal operation. The final category includes the definition of fault scenarios characteristic of each targeted engine fault. These scenarios are defined in terms of engine model hardware parameters. Values of these parameters define engine simulations that generate
Survey strategy optimization for the Atacama Cosmology Telescope
De Bernardis, F.; Stevens, J. R.; Hasselfield, M.; Alonso, D.; Bond, J. R.; Calabrese, E.; Choi, S. K.; Crowley, K. T.; Devlin, M.; Dunkley, J.; Gallardo, P. A.; Henderson, S. W.; Hilton, M.; Hlozek, R.; Ho, S. P.; Huffenberger, K.; Koopman, B. J.; Kosowsky, A.; Louis, T.; Madhavacheril, M. S.; McMahon, J.; Næss, S.; Nati, F.; Newburgh, L.; Niemack, M. D.; Page, L. A.; Salatino, M.; Schillaci, A.; Schmitt, B. L.; Sehgal, N.; Sievers, J. L.; Simon, S. M.; Spergel, D. N.; Staggs, S. T.; van Engelen, A.; Vavagiakis, E. M.; Wollack, E. J.
2016-07-01
In recent years there have been significant improvements in the sensitivity and the angular resolution of the instruments dedicated to the observation of the Cosmic Microwave Background (CMB). ACTPol is the first polarization receiver for the Atacama Cosmology Telescope (ACT) and is observing the CMB sky with arcmin resolution over 2000 sq. deg. Its upgrade, Advanced ACTPol (AdvACT), will observe the CMB in five frequency bands and over a larger area of the sky. We describe the optimization and implementation of the ACTPol and AdvACT surveys. The selection of the observed fields is driven mainly by the science goals, that is, small angular scale CMB measurements, B-mode measurements and cross-correlation studies. For the ACTPol survey we have observed patches of the southern galactic sky with low galactic foreground emissions which were also chosen to maximize the overlap with several galaxy surveys to allow unique cross-correlation studies. A wider field in the northern galactic cap ensured significant additional overlap with the BOSS spectroscopic survey. The exact shapes and footprints of the fields were optimized to achieve uniform coverage and to obtain cross-linked maps by observing the fields with different scan directions. We have maximized the efficiency of the survey by implementing a close to 24 hour observing strategy, switching between daytime and nighttime observing plans and minimizing the telescope idle time. We describe the challenges represented by the survey optimization for the significantly wider area observed by AdvACT, which will observe roughly half of the low-foreground sky. The survey strategies described here may prove useful for planning future ground-based CMB surveys, such as the Simons Observatory and CMB Stage IV surveys.
Using Chemical Reaction Kinetics to Predict Optimal Antibiotic Treatment Strategies
Abel zur Wiesch, Pia; Cohen, Ted
2017-01-01
Identifying optimal dosing of antibiotics has proven challenging—some antibiotics are most effective when they are administered periodically at high doses, while others work best when minimizing concentration fluctuations. Mechanistic explanations for why antibiotics differ in their optimal dosing are lacking, limiting our ability to predict optimal therapy and leading to long and costly experiments. We use mathematical models that describe both bacterial growth and intracellular antibiotic-target binding to investigate the effects of fluctuating antibiotic concentrations on individual bacterial cells and bacterial populations. We show that physicochemical parameters, e.g. the rate of drug transmembrane diffusion and the antibiotic-target complex half-life are sufficient to explain which treatment strategy is most effective. If the drug-target complex dissociates rapidly, the antibiotic must be kept constantly at a concentration that prevents bacterial replication. If antibiotics cross bacterial cell envelopes slowly to reach their target, there is a delay in the onset of action that may be reduced by increasing initial antibiotic concentration. Finally, slow drug-target dissociation and slow diffusion out of cells act to prolong antibiotic effects, thereby allowing for less frequent dosing. Our model can be used as a tool in the rational design of treatment for bacterial infections. It is easily adaptable to other biological systems, e.g. HIV, malaria and cancer, where the effects of physiological fluctuations of drug concentration are also poorly understood. PMID:28060813
Using Chemical Reaction Kinetics to Predict Optimal Antibiotic Treatment Strategies.
Abel Zur Wiesch, Pia; Clarelli, Fabrizio; Cohen, Ted
2017-01-01
Identifying optimal dosing of antibiotics has proven challenging-some antibiotics are most effective when they are administered periodically at high doses, while others work best when minimizing concentration fluctuations. Mechanistic explanations for why antibiotics differ in their optimal dosing are lacking, limiting our ability to predict optimal therapy and leading to long and costly experiments. We use mathematical models that describe both bacterial growth and intracellular antibiotic-target binding to investigate the effects of fluctuating antibiotic concentrations on individual bacterial cells and bacterial populations. We show that physicochemical parameters, e.g. the rate of drug transmembrane diffusion and the antibiotic-target complex half-life are sufficient to explain which treatment strategy is most effective. If the drug-target complex dissociates rapidly, the antibiotic must be kept constantly at a concentration that prevents bacterial replication. If antibiotics cross bacterial cell envelopes slowly to reach their target, there is a delay in the onset of action that may be reduced by increasing initial antibiotic concentration. Finally, slow drug-target dissociation and slow diffusion out of cells act to prolong antibiotic effects, thereby allowing for less frequent dosing. Our model can be used as a tool in the rational design of treatment for bacterial infections. It is easily adaptable to other biological systems, e.g. HIV, malaria and cancer, where the effects of physiological fluctuations of drug concentration are also poorly understood.
Optimal Power Management Strategy for Energy Storage with Stochastic Loads
Directory of Open Access Journals (Sweden)
Stefano Pietrosanti
2016-03-01
Full Text Available In this paper, a power management strategy (PMS has been developed for the control of energy storage in a system subjected to loads of random duration. The PMS minimises the costs associated with the energy consumption of specific systems powered by a primary energy source and equipped with energy storage, under the assumption that the statistical distribution of load durations is known. By including the variability of the load in the cost function, it was possible to define the optimality criteria for the power flow of the storage. Numerical calculations have been performed obtaining the control strategies associated with the global minimum in energy costs, for a wide range of initial conditions of the system. The results of the calculations have been tested on a MATLAB/Simulink model of a rubber tyre gantry (RTG crane equipped with a flywheel energy storage system (FESS and subjected to a test cycle, which corresponds to the real operation of a crane in the Port of Felixstowe. The results of the model show increased energy savings and reduced peak power demand with respect to existing control strategies, indicating considerable potential savings for port operators in terms of energy and maintenance costs.
OPTIMIZATION OF BIOCIDE STRATEGIES ON FINE PAPER MACHINES
Directory of Open Access Journals (Sweden)
Jani Kiuru
2010-05-01
Full Text Available In this study a rapid at-line ATP (adenosine triphosphate analysis is applied in papermaking. This ATP analysis takes less than a minute, and the information can be utilized instantly to adapt the biocide program. The study shows the effect of different biocide strategies at paper mills. Comparison is made between oxidative and reductive biocides on the one hand, and on the other hand between continuous vs. batch additions of biocide. Continuous biocide addition keeps the microbial activity at a constant level. However, a long production period without a boil-out might result in accumulation of resistant bacteria, which cannot be eliminated without changing the biocide strategy. Batch addition of biocide creates a high temporary concentration of biocide in the process. This causes lower temporary microbial activity in the process, but between the doses the microbial activity may rise to an intolerable level. Batch addition causes chemical variation to the wet end of a paper machine more easily than continuous addition. This can affect the performance of papermaking chemicals and cause problems with retention, fixing, etc. Both biocide addition strategies can be used if they are monitored and optimized properly. Rapid ATP analysis is a suitable tool for both purposes.
Energy Technology Data Exchange (ETDEWEB)
Hope, E.
1994-06-01
The report discusses the organization and behaviour of grid monopolies in the Norwegian power trade and relations to the socio-economic effectiveness. The main attention is laid on analyzing regulation mechanisms and measures leading to an efficient short-term operation and to the investment of optimum production capacity in a long run. Regarding the management, measures are discussed for increasing the efficiency of total power trade by evaluating the existing marketing function of Statnett. Some basic conditions are accounted concerning the regulation problem of grid monopolies with a particular attention to asymmetric information between the authority and the monopoly. In addition, forms of regulation and regulation mechanisms together with the incentive characteristics of these, are discussed. The existing profit regulation principles in relation to an alternative system design such as maximum price regulation combined with standard regulation, are evaluated. 16 refs., 7 figs.
Dewandaru, Ginanjar; Masih, Rumi; Bacha, Obiyathulla Ismath; Masih, A. Mansur. M.
2015-11-01
We provide a new contribution to trading strategies by using multi-fractal de-trended fluctuation analysis (MF-DFA), imported from econophysics, to complement various momentum strategies. The method provides a single measure that can capture both persistency and anti-persistency in stock prices, accounting for multifractality. This study uses a sample of Islamic stocks listed in the U.S. Dow Jones Islamic market for a sample period covering 16 years starting in 1996. The findings show that the MF-DFA strategy produces monthly excess returns of 6.12%, outperforming other various momentum strategies. Even though the risk of the MF-DFA strategy may be relatively higher, it can still produce a Sharpe ratio of 0.164, which is substantially higher than that of the other strategies. When we control for the MF-DFA factor with the other factors, its pure factor return is still able to yield a monthly excess return of 1.35%. Finally, we combine the momentum and MF-DFA strategies, with the proportions of 90/10, 80/20, and 70/30 and by doing so we demonstrate that the MF-DFA measure can boost the total monthly excess returns as well as Sharpe ratio. The value added is non-linear which implies that the additional returns are associated with lower incremental risk.
Skinner, Brian
2011-01-01
When facing a heavily-favored opponent, an underdog must be willing to assume greater-than-average risk. In statistical language, one would say that an underdog must be willing to adopt a strategy whose outcome has a larger-than-average variance. The difficult question is how much risk a team should be willing to accept. This is equivalent to asking how much the team should be willing to sacrifice from its mean score in order to increase the score's variance. In this paper a general, analytical method is developed for addressing this question quantitatively. Under the assumption that every play in a game is statistically independent, both the mean and the variance of a team's offensive output can be described using the binomial distribution. This description allows for direct calculations of the winning probability when a particular strategy is employed, and therefore allows one to calculate optimal offensive strategies. This paper develops this method for calculating optimal strategies exactly and then prese...
Publish or patent: bibliometric evidence for empirical trade-offs in national funding strategies
R.D. Shelton; L. Leydesdorff
2012-01-01
Multivariate linear regression models suggest a trade-off in allocations of national research and development (R&D). Government funding and spending in the higher education sector encourage publications as a long-term research benefit. Conversely, other components such as industrial funding and spen
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
Strategies for optimizing algal biology for enhanced biomass production
Directory of Open Access Journals (Sweden)
Amanda N. Barry
2015-02-01
Full Text Available One of the more environmentally sustainable ways to produce high energy density (oils feed stocks for the production of liquid transportation fuels is from biomass. Photosynthetic carbon capture combined with biomass combustion (point source and subsequent carbon capture and sequestration (BECCS has also been proposed in the Intergovernmental Panel on Climate Change Report as one of the most effective and economical strategies to remediate atmospheric greenhouse gases. To maximize photosynthetic carbon capture efficiency and energy-return-on-investment, we must develop biomass production systems that achieve the greatest yields with the lowest inputs. Numerous studies have demonstrated that microalgae have among the greatest potentials for biomass production. This is in part due to the fact that all alga cells are photoautotrophic, they have active carbon concentrating mechanisms to increase photosynthetic productivity, and all the biomass is harvestable unlike plants. All photosynthetic organisms, however, convert only a fraction of the solar energy they capture into chemical energy (reduced carbon or biomass. To increase aerial carbon capture rates and biomass productivity it will be necessary to identify the most robust algal strains and increase their biomass production efficiency often by genetic manipulation. We review recent large-scale efforts to identify the best biomass producing strains and metabolic engineering strategies to improve aerial productivity. These strategies include optimization of photosynthetic light-harvesting antenna size to increase energy capture and conversion efficiency and the potential development of advanced molecular breeding techniques. To date, these strategies have resulted in up to two-fold increases in biomass productivity.
Optimal Privacy-Cost Trade-off in Demand-Side Management with Storage
Tan, Onur; Gündüz, Deniz; Gómez-Vilardebó, Jesús
2015-01-01
Demand-side energy storage management is studied from a joint privacy-energy cost optimization perspective. Assuming that the user's power demand profile as well as the electricity prices are known non-causally, the optimal energy management (EM) policy that jointly increases the privacy of the user and reduces his energy cost is characterized. The backward water-filling interpretation is provided for the optimal EM policy. While the energy cost is reduced by requesting more energy when the p...
Optimizing urology group partnerships: collaboration strategies and compensation best practices.
Jacoby, Dana L; Maller, Bruce S; Peltier, Lisa R
2014-10-01
Market forces in health care have created substantial regulatory, legislative, and reimbursement changes that have had a significant impact on urology group practices. To maintain viability, many urology groups have merged into larger integrated entities. Although group operations vary considerably, the majority of groups have struggled with the development of a strong culture, effective decision-making, and consensus-building around shared resources, income, and expense. Creating a sustainable business model requires urology group leaders to allocate appropriate time and resources to address these issues in a proactive manner. This article outlines collaboration strategies for creating an effective culture, governance, and leadership, and provides practical suggestions for optimizing the performance of the urology group practice.
An Overview of Optimizing Strategies for Flotation Banks
Directory of Open Access Journals (Sweden)
Miguel Maldonado
2012-10-01
Full Text Available A flotation bank is a serial arrangement of cells. How to optimally operate a bank remains a challenge. This article reviews three reported strategies: air profiling, mass-pull (froth velocity profiling and Peak Air Recovery (PAR profiling. These are all ways of manipulating the recovery profile down a bank, which may be the property being exploited. Mathematical analysis has shown that a flat cell-by-cell recovery profile maximizes the separation of two floatable minerals for a given target bank recovery when the relative floatability is constant down the bank. Available bank survey data are analyzed with respect to recovery profiling. Possible variations on recovery profile to minimize entrainment are discussed.
Can bilateral trade agreements help induce free trade?
Riezman, Raymond Glenn
1999-01-01
There has been growing debate about whether bilateral trade agreements are damaging multilateral efforts to eliminate barriers to international trade. This paper develops a model in which trading blocks always charge optimal tariffs and make trade agreements based on strategic considerations. We ask a very simple question. Does the fact that trading blocks can form bilateral trade agreements make Free trade less likely to occur? The answer is that it depends on the size distribution of the tr...
Optimizing clinical environments for knowledge translation: strategies for nursing leaders.
Scott, Shannon D; VandenBeld, Brenda; Cummings, Greta G
2011-10-01
Using findings from our recent study that found that a context of uncertainty in the work environment hindered nurses' research utilization, we suggest strategies for nurse managers and leaders to optimize clinical environments and support efforts to put research into clinical practice (knowledge translation). Two important sources of uncertainty were the complexity of teamwork and inconsistency in management and leadership styles. To reduce the uncertainty arising from teamwork, we propose (a) clarifying nurses' scopes of practice, (b) increasing knowledge sharing through supporting journal clubs and enhanced computer access and (c) creating safe venues for multidisciplinary dialogue. To reduce uncertainty arising from variations in management and leadership, we propose (a) developing policies that enhance the consistency of leadership and clarify the strategic direction of the management team, (b) clearly communicating those policies to nurses and (c) providing explicit rationales for treatment changes. Small, incremental steps can be taken to realize substantive changes in clinical environments in order to optimize nursing work environments for knowledge translation.
[Optimal allocation of irrigation water resources based on systematical strategy].
Cheng, Shuai; Zhang, Shu-qing
2015-01-01
With the development of the society and economy, as well as the rapid increase of population, more and more water is needed by human, which intensified the shortage of water resources. The scarcity of water resources and growing competition of water in different water use sectors reduce water availability for irrigation, so it is significant to plan and manage irrigation water resources scientifically and reasonably for improving water use efficiency (WUE) and ensuring food security. Many investigations indicate that WUE can be increased by optimization of water use. However, present studies focused primarily on a particular aspect or scale, which lack systematic analysis on the problem of irrigation water allocation. By summarizing previous related studies, especially those based on intelligent algorithms, this article proposed a multi-level, multi-scale framework for allocating irrigation water, and illustrated the basic theory of each component of the framework. Systematical strategy of optimal irrigation water allocation can not only control the total volume of irrigation water on the time scale, but also reduce water loss on the spatial scale. It could provide scientific basis and technical support for improving the irrigation water management level and ensuring the food security.
Optimal Order Strategy in Uncertain Demands with Free Shipping Option
Directory of Open Access Journals (Sweden)
Qing-Chun Meng
2014-01-01
Full Text Available Free shipping with conditions has become one of the most effective marketing tools; more and more companies especially e-business companies prefer to offer free shipping to buyers whenever their orders exceed the minimum quantity specified by them. But in practice, the demands of buyers are uncertain, which are affected by weather, season, and many other factors. Firstly, we model the centralization ordering problem of retailers who face stochastic demands when suppliers offer free shipping, in which limited distributional information such as known mean, support, and some deviation measures of the random data is needed only. Then, based on the linear decision rule mainly for stochastic programming, we analyze the optimal order strategies of retailers and discuss the approximate solution. Further, we present the core allocation between all retailers via dual and cooperative game theory. The existence of core shows that each retailer is pleased to cooperate with others in the centralization problem. Finally, a numerical example is implemented to discuss how uncertain data and parameters affect the optimal solution.
Evolving strategies for optimal care management and plan benefit designs.
Cruickshank, John M
2012-11-01
As a prevalent, complex disease, diabetes presents a challenge to managed care. Strategies to optimize type 2 diabetes care management and treatment outcomes have been evolving over the past several years. Novel economic incentive programs (eg, those outlined in the Patient Protection and Affordable Care Act of 2010 that tie revenue from Medicare Advantage plans to the quality of healthcare delivered) are being implemented, as are evidence-based interventions designed to optimize treatment, reduce clinical complications, and lower the total financial burden of the disease. Another step that can improve outcomes is to align managed care diabetes treatment algorithms with national treatment guidelines. In addition, designing the pharmacy benefit to emphasize the overall value of treatment and minimize out-of-pocket expenses for patients can be an effective approach to reducing prescription abandonment. The implementation of emerging models of care that encourage collaboration between providers, support lifestyle changes, and engage patients to become partners in their own treatment also appears to be effective.
B2B Strategy Making and Planning : case: Datnam Techonologies and Trading Company, Ltd.
Hoang, Hong Tu
2013-01-01
There is an increasing demand for safety and security equipment market in Vietnam thanks to the encouragement of the government and the growing concentration on working condition improvement. Therefore the Case Company Datnam Technology and Trading Company, Ltd., a successful SME in Vietnam, realized the rising demand in business to business (B2B) market and assigned the author to do research about this topic. The purpose of the study is to assist the company to launch the Breath Alcohol T...
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
Cities are becoming the locus of climate change policy and planning, both for mitigating greenhouse gas emissions and adapting to the impacts of climate change. These actions involve a number of trade-offs, including densification of the urban structure, concerns over social equity and the proper...... 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....
An Entropic Approach for Pair Trading
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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.
An Entropic Approach for Pair Trading
Daisuke Yoshikawa
2017-01-01
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.
Optimizing the HLT Buffer Strategy with Monte Carlo Simulations
AUTHOR|(CDS)2266763
2017-01-01
This project aims to optimize the strategy of utilizing the disk buffer for the High Level Trigger (HLT) of the LHCb experiment with the help of Monte-Carlo simulations. A method is developed, which simulates the Event Filter Farm (EFF) -- a computing cluster for the High Level Trigger -- as a compound of nodes with different performance properties. In this way, the behavior of the computing farm can be analyzed at a deeper level than before. It is demonstrated that the current operating strategy might be improved when data taking is reaching a mid-year scheduled stop or the year-end technical stop. The processing time of the buffered data can be lowered by distributing the detector data according to the processing power of the nodes instead of the relative disk size as long as the occupancy level of the buffer is low enough. Moreover, this ensures that data taken and stored on the buffer at the same time is processed by different nodes nearly simultaneously, which reduces load on the infrastructure.
Optimizing Reinjection Strategy at Palinpinon, Philippines Based on Chloride Data
Energy Technology Data Exchange (ETDEWEB)
Urbino, Ma. Elena G.; Horne, Roland N.
1992-03-24
One of the guidelines established for the safe and efficient management of the Palinpinon Geothermal Field is to adopt a production and well utilization strategy such that the rapid rate and magnitude of reinjection fluid returns leading to premature thermal breakthrough would be minimized. To help achieve this goal, sodium fluorescein and radioactive tracer tests have been conducted to determine the rate and extent of communication between the reinjection and producing sectors of the field. The first objective of this paper is to show how the results of these tests, together with information on field geometry and operating conditions were used in algorithms developed in Operations Research to allocate production and reinjection rates among the different Palinpinon wells. Due to operational and economic constraints, such tracer tests were very limited in number and scope. This prevents obtaining information on the explicit interaction between each reinjection well and the producing wells. Hence, the chloride value of the producing well, was tested to determine if use of this parameter would enable identifying fast reinjection paths among different production/reinjection well pairs. The second aim, therefore, of this paper is to show the different methods of using the chloride data of the producing wells and the injection flow rates of the reinjection wells to provide a ranking of the pair of wells and, thereby, optimize the reinjection strategy of the field.
Optimal Pharmacologic Treatment Strategies in Obesity and Type 2 Diabetes
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Gayotri Goswami
2014-06-01
Full Text Available The prevalence of obesity has increased to pandemic levels worldwide and is related to increased risk of morbidity and mortality. Metabolic comorbidities are commonly associated with obesity and include metabolic syndrome, pre-diabetes, and type 2 diabetes. Even if the prevalence of obesity remains stable until 2030, the anticipated numbers of people with diabetes will more than double as a consequence of population aging and urbanization. Weight reduction is integral in the prevention of diabetes among obese adults with pre-diabetes. Lifestyle intervention and weight reduction are also key in the management of type 2 diabetes. Weight loss is challenging for most obese patients, but for those with diabetes, it can pose an even greater challenge due to the weight gain associated with many treatment regimens. This article will review optimal treatment strategies for patients with comorbid obesity and type 2 diabetes. The role of anti-obesity agents in diabetes will also be reviewed. This literature review will provide readers with current strategies for the pharmacologic treatment of obesity and diabetes with a focus on the weight outcomes related to diabetes treatments.
The complete proof on the optimal ordering policy under cash discount and trade credit
Chung, Kun-Jen
2010-04-01
Huang ((2005), 'Buyer's Optimal Ordering Policy and Payment Policy under Supplier Credit', International Journal of Systems Science, 36, 801-807) investigates the buyer's optimal ordering policy and payment policy under supplier credit. His inventory model is correct and interesting. Basically, he uses an algebraic method to locate the optimal solution of the annual total relevant cost TRC(T) and ignores the role of the functional behaviour of TRC(T) in locating the optimal solution of it. However, as argued in this article, Huang needs to explore the functional behaviour of TRC(T) to justify his solution. So, from the viewpoint of logic, the proof about Theorem 1 in Huang has some shortcomings such that the validity of Theorem 1 in Huang is questionable. The main purpose of this article is to remove and correct those shortcomings in Huang and present the complete proofs for Huang.
Altomare, Cristina; Guglielmann, Raffaella; Riboldi, Marco; Bellazzi, Riccardo; Baroni, Guido
2015-02-01
In high precision photon radiotherapy and in hadrontherapy, it is crucial to minimize the occurrence of geometrical deviations with respect to the treatment plan in each treatment session. To this end, point-based infrared (IR) optical tracking for patient set-up quality assessment is performed. Such tracking depends on external fiducial points placement. The main purpose of our work is to propose a new algorithm based on simulated annealing and augmented Lagrangian pattern search (SAPS), which is able to take into account prior knowledge, such as spatial constraints, during the optimization process. The SAPS algorithm was tested on data related to head and neck and pelvic cancer patients, and that were fitted with external surface markers for IR optical tracking applied for patient set-up preliminary correction. The integrated algorithm was tested considering optimality measures obtained with Computed Tomography (CT) images (i.e. the ratio between the so-called target registration error and fiducial registration error, TRE/FRE) and assessing the marker spatial distribution. Comparison has been performed with randomly selected marker configuration and with the GETS algorithm (Genetic Evolutionary Taboo Search), also taking into account the presence of organs at risk. The results obtained with SAPS highlight improvements with respect to the other approaches: (i) TRE/FRE ratio decreases; (ii) marker distribution satisfies both marker visibility and spatial constraints. We have also investigated how the TRE/FRE ratio is influenced by the number of markers, obtaining significant TRE/FRE reduction with respect to the random configurations, when a high number of markers is used. The SAPS algorithm is a valuable strategy for fiducial configuration optimization in IR optical tracking applied for patient set-up error detection and correction in radiation therapy, showing that taking into account prior knowledge is valuable in this optimization process. Further work will be
Optimization of a virtual EUV photoresist for the trade-off between throughput and CDU
Smith, Mark D.; Biafore, John; Fang, Chao
2013-03-01
EUV source power and resist photospeed will dictate the throughput of EUV lithography, and throughput is a key factor in the cost of ownership of EUVL as a technology. However, low exposure doses typically lead to poor CD uniformity (CDU) and line-width roughness (LWR). In this paper, we simulate the CDU versus dose-to-size trade-off for a large number of virtual photoresists using PROLITH for 28nm, 26nm, and 22nm HP contacts. The resulting CDU versus dose curve is very similar to the experimental investigations by Naulleau et al. (Proc. SPIE, v7972, 2011) and by Goethals et al. (EUVL Symposium 2012). With the simulated results, we can investigate trends with physical properties such as diffusivity of acid and quencher, and overall exposure yield, as well as formulation properties such as PAG and quencher loadings, and conventional versus photodecomposable quencher.
Adaptive hybrid optimization strategy for calibration and parameter estimation of physical models
Vesselinov, Velimir V
2011-01-01
A new adaptive hybrid optimization strategy, entitled squads, is proposed for complex inverse analysis of computationally intensive physical models. The new strategy is designed to be computationally efficient and robust in identification of the global optimum (e.g. maximum or minimum value of an objective function). It integrates a global Adaptive Particle Swarm Optimization (APSO) strategy with a local Levenberg-Marquardt (LM) optimization strategy using adaptive rules based on runtime performance. The global strategy optimizes the location of a set of solutions (particles) in the parameter space. The LM strategy is applied only to a subset of the particles at different stages of the optimization based on the adaptive rules. After the LM adjustment of the subset of particle positions, the updated particles are returned to the APSO strategy. The advantages of coupling APSO and LM in the manner implemented in squads is demonstrated by comparisons of squads performance against Levenberg-Marquardt (LM), Particl...
Li, Zejing
2012-01-01
This dissertation is mainly devoted to the research of two problems - the continuous-time portfolio optimization in different Wishart models and the effects of discrete rebalancing on portfolio wealth distribution and optimal portfolio strategy.
Optimal control strategies for tuberculosis treatment: a case study in Angola
Silva, Cristiana J
2012-01-01
We apply optimal control theory to a tuberculosis model given by a system of ordinary differential equations. Optimal control strategies are proposed to minimize the cost of interventions. Numerical simulations are given using data from Angola.
Selection, optimization, and compensation strategies : Interactive effects on daily work engagement
Zacher, Hannes; Chan, Felicia; Bakker, Arnold B.; Demerouti, Evangelia
2015-01-01
The theory of selective optimization with compensation (SOC) proposes that the "orchestrated" use of three distinct action regulation strategies (selection, optimization, and compensation) leads to positive employee outcomes. Previous research examined overall scores and additive models (i.e., main
Computing Optimal Stochastic Portfolio Execution Strategies: A Parametric Approach Using Simulations
Moazeni, Somayeh; Coleman, Thomas F.; Li, Yuying
2010-09-01
Computing optimal stochastic portfolio execution strategies under appropriate risk consideration presents great computational challenge. We investigate a parametric approach for computing optimal stochastic strategies using Monte Carlo simulations. This approach allows reduction in computational complexity by computing coefficients for a parametric representation of a stochastic dynamic strategy based on static optimization. Using this technique, constraints can be similarly handled using appropriate penalty functions. We illustrate the proposed approach to minimize the expected execution cost and Conditional Value-at-Risk (CVaR).
Yen, Ghi-Feng; Chung, Kun-Jen; Chen, Tzung-Ching
2012-11-01
The traditional economic order quantity model assumes that the retailer's storage capacity is unlimited. However, as we all know, the capacity of any warehouse is limited. In practice, there usually exist various factors that induce the decision-maker of the inventory system to order more items than can be held in his/her own warehouse. Therefore, for the decision-maker, it is very practical to determine whether or not to rent other warehouses. In this article, we try to incorporate two levels of trade credit and two separate warehouses (own warehouse and rented warehouse) to establish a new inventory model to help the decision-maker to make the decision. Four theorems are provided to determine the optimal cycle time to generalise some existing articles. Finally, the sensitivity analysis is executed to investigate the effects of the various parameters on ordering policies and annual costs of the inventory system.
Optimizing strategies to improve interprofessional practice for veterans, part 1
Directory of Open Access Journals (Sweden)
Bhattacharya SB
2014-04-01
Full Text Available Shelley B Bhattacharya,1–3 Michelle I Rossi,1,2 Jennifer M Mentz11Geriatric Research Education and Clinical Center (GRECC, Veteran's Affairs Pittsburgh Healthcare System, 2University of Pittsburgh Medical Center, Pittsburgh, PA, USA; 3Albert Schweitzer Fellowship Program, Pittsburgh, PA, USAIntroduction: Interprofessional patient care is a well-recognized path that health care systems are striving toward. The Veteran's Affairs (VA system initiated interprofessional practice (IPP models with their Geriatric Evaluation and Management (GEM programs. GEM programs incorporate a range of specialties, including but not limited to, medicine, nursing, social work, physical therapy and pharmacy, to collaboratively evaluate veterans. Despite being a valuable resource, they are now faced with significant cut-backs, including closures. The primary goal of this project was to assess how the GEM model could be optimized at the Pittsburgh, Pennsylvania VA to allow for the sustainability of this important IPP assessment. Part 1 of the study evaluated the IPP process using program, patient, and family surveys. Part 2 examined how well the geriatrician matched patients to specialists in the GEM model. This paper describes Part 1 of our study.Methods: Three strategies were used: 1 a national GEM program survey; 2 a veteran/family satisfaction survey; and 3 an absentee assessment.Results: Twenty-six of 92 programs responded to the GEM IPP survey. Six strategies were shared to optimize IPP models throughout the country. Of the 34 satisfaction surveys, 80% stated the GEM clinic was beneficial, 79% stated their concerns were addressed, and 100% would recommend GEM to their friends. Of the 24 absentee assessments, the top three reasons for missing the appointments were transportation, medical illnesses, and not knowing/remembering about the appointment. Absentee rate diminished from 41% to 19% after instituting a reminder phone call policy.Discussion: Maintaining the
Optimal pandemic influenza vaccine allocation strategies for the Canadian population.
Directory of Open Access Journals (Sweden)
Ashleigh R Tuite
Full Text Available BACKGROUND: The world is currently confronting the first influenza pandemic of the 21(st century. Influenza vaccination is an effective preventive measure, but the unique epidemiological features of swine-origin influenza A (H1N1 (pH1N1 introduce uncertainty as to the best strategy for prioritization of vaccine allocation. We sought to determine optimal prioritization of vaccine distribution among different age and risk groups within the Canadian population, to minimize influenza-attributable morbidity and mortality. METHODOLOGY/PRINCIPAL FINDINGS: We developed a deterministic, age-structured compartmental model of influenza transmission, with key parameter values estimated from data collected during the initial phase of the epidemic in Ontario, Canada. We examined the effect of different vaccination strategies on attack rates, hospitalizations, intensive care unit admissions, and mortality. In all scenarios, prioritization of high-risk individuals (those with underlying chronic conditions and pregnant women, regardless of age, markedly decreased the frequency of severe outcomes. When individuals with underlying medical conditions were not prioritized and an age group-based approach was used, preferential vaccination of age groups at increased risk of severe outcomes following infection generally resulted in decreased mortality compared to targeting vaccine to age groups with higher transmission, at a cost of higher population-level attack rates. All simulations were sensitive to the timing of the epidemic peak in relation to vaccine availability, with vaccination having the greatest impact when it was implemented well in advance of the epidemic peak. CONCLUSIONS/SIGNIFICANCE: Our model simulations suggest that vaccine should be allocated to high-risk groups, regardless of age, followed by age groups at increased risk of severe outcomes. Vaccination may significantly reduce influenza-attributable morbidity and mortality, but the benefits are
隐性技术、贸易溢出和模仿策略%Tacit Technology, Trade Spillover and Imitating Strategy
Institute of Scientific and Technical Information of China (English)
宋艳丽; 王九云
2011-01-01
本文构建了一个扩展的南北贸易模型,将北方创新、南方模仿和进口产品隐性技术作为内生变量,分析进口国如何选择模仿策略以最大程度地获得进口产品的内生技术溢出效应.结果表明,进口产品中隐性技术含量会影响南方厂商的模仿策略:进口产品隐性技术含量低时,原始模仿是南方厂商的理性选择;进口产品隐性技术产量较高时,南方厂商的模仿策略取决于模仿的预期边际收益与单位模仿成本的对比关系:模仿的预期边际收益大于单位模仿成本时,内生模仿是南方厂商的最优选择,反之原始模仿.%The paper builds an expanded the trade model between the south and the north of Chins, involving the northern innovation, the southern imitation and tacit technology in the model as endogenous variables.Then the paper analyses how importers imitate the imported products to get optimal technology spillover effect.The theoretical analysis shows that the southern manufacturers' imitating strategy may be affected by tacit technology hidden within the imported products.If the content of tacit technology is low within the imported products, simple imitation is the southern manufacturers' optimal imitating strategy.And when the content of tacit technology is high, southern manufacturers' optimal imitating strategy depends on the relative relationship of imitation' s marginal revenue and unit imitating cost.When the imitation' s marginal revenue is higher than unit imitating cost, endogenous imitation is optimal for southern manufacturers, otherwise simple imitation.
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.
Greig, Bradley; Koopmans, Léon V E
2015-01-01
With the first phase of the Square Kilometre Array (SKA1) entering into its final pre-construction phase, we investigate how best to maximise its scientific return. Specifically, we focus on the statistical measurement of the 21 cm power spectrum (PS) from the epoch of reionization (EoR) using the low frequency array, SKA1-low. To facilitate this investigation we use the recently developed MCMC based EoR analysis tool 21CMMC (Greig & Mesinger). In light of the recent 50 per cent cost reduction, we consider several different SKA core baseline designs, changing: (i) the number of antenna stations; (ii) the number of dipoles per station; and also (iii) the distribution of baseline lengths. We find that a design with a reduced number of dipoles per core station (increased field of view and total number of core stations), together with shortened baselines, maximises the recovered EoR signal. With this optimal baseline design, we investigate three observing strategies, analysing the trade-off between lowering t...
Leaf Area Adjustment As an Optimal Drought-Adaptation Strategy
Manzoni, S.; Beyer, F.; Thompson, S. E.; Vico, G.; Weih, M.
2014-12-01
Leaf phenology plays a major role in land-atmosphere mass and energy exchanges. Much work has focused on phenological responses to light and temperature, but less to leaf area changes during dry periods. Because the duration of droughts is expected to increase under future climates in seasonally-dry as well as mesic environments, it is crucial to (i) predict drought-related phenological changes and (ii) to develop physiologically-sound models of leaf area dynamics during dry periods. Several optimization criteria have been proposed to model leaf area adjustment as soil moisture decreases. Some theories are based on the plant carbon (C) balance, hypothesizing that leaf area will decline when instantaneous net photosynthetic rates become negative (equivalent to maximization of cumulative C gain). Other theories draw on hydraulic principles, suggesting that leaf area should adjust to either maintain a constant leaf water potential (isohydric behavior) or to avoid leaf water potentials with negative impacts on photosynthesis (i.e., minimization of water stress). Evergreen leaf phenology is considered as a control case. Merging these theories into a unified framework, we quantify the effect of phenological strategy and climate forcing on the net C gain over the entire growing season. By accounting for the C costs of leaf flushing and the gains stemming from leaf photosynthesis, this metric assesses the effectiveness of different phenological strategies, under different climatic scenarios. Evergreen species are favored only when the dry period is relatively short, as they can exploit most of the growing season, and only incur leaf maintenance costs during the short dry period. In contrast, deciduous species that lower maintenance costs by losing leaves are advantaged under drier climates. Moreover, among drought-deciduous species, isohydric behavior leads to lowest C gains. Losing leaves gradually so as to maintain a net C uptake equal to zero during the driest period in
A Swarm Optimization Based Power Aware Clustering Strategy for WSNs
Directory of Open Access Journals (Sweden)
Harendra S. Jangwan
2017-02-01
Full Text Available The technique of division of a wireless sensor network (WSN into clusters has proved to most suitable for the reliable data communication inside the network. This approach also improves the throughput of the system along with other attributes such as rate of delivering data packet to the base station (BS and overall energy dissipation of the sensor nodes in the network. This in turn results in the increased network lifetime. As the sensor nodes are operated by battery or some other source, this introduces a constraint in energy resource. Therefore, there is a strong need to develop a novel approach to overcome this constraint, since this phenomenon leads to the degradation of the network. The swarm intelligence approach is able to cope with all such pitfalls of WSNs. In this paper, we have presented a cluster-head (CH selection technique which is based on swarm optimization with the main aim to increase the overall network lifetime. The proposed approach gives higher effects with regards to power utilization of nodes, data packets received at BS and stability period, and for this reason serves to be a higher performer as compared to Stable Election Protocol (SEP and Enhance Threshold Sensitive Stable Election Protocol(ETSSEP. MATLAB simulation outcomes exhibit that the proposed clustering strategy outperforms the SEP and ETSSEP with regards to the above noted attributes.
Solving Optimal Broadcasting Strategy in Metropolitan MANETs Using MOCELL Algorithm
Directory of Open Access Journals (Sweden)
M. Ghonamy
2010-09-01
Full Text Available Mobile ad-hoc networks (MANETs are a set of communicating devices that are able to spontaneously interconnect without any pre-existing infrastructure. In such a scenario, broadcasting becomes very important to the existence and the operation of this network. The process of optimizing the broadcast strategy of MANETs is a multi-objective problem with three objectives: (1 reaching as many stations as possible, (2 minimizing the network utilization and (3 reducing the broadcasting duration. The main contribution of this paper is that it tackles this problem by using multi-objective cellular genetic algorithm that is called MOCELL. MOCELL computes a Pareto front of solutions to empower a human designer with the ability to choose the preferred configuration for the network. Our results are compared with those obtained from the previous proposals used for solving the problem, a cellular multi-objective genetic algorithm which called cMOGA (the old version of MOCELL. We conclude that MOCELL outperforms cMOGA with respect to set coverage metric.
Phenology as a strategy for carbon optimality: a global model
Directory of Open Access Journals (Sweden)
S. Caldararu
2013-09-01
Full Text Available Phenology is essential to our understanding of biogeochemical cycles and the climate system. We develop a global mechanistic model of leaf phenology based on the hypothesis that phenology is a strategy for optimal carbon gain at the canopy level so that trees adjust leaf gains and losses in response to environmental factors such as light, temperature and soil moisture, to achieve maximum carbon assimilation. We fit this model to five years of satellite observations of leaf area index (LAI using a Bayesian fitting algorithm. We show that our model is able to reproduce phenological patterns for all vegetation types and use it to explore variations in growing season length and the climate factors that limit leaf growth for different biomes. Phenology in wet tropical areas is limited by leaf age physiological constraints while at higher latitude leaf seasonality is limited by low temperature and light availability. Leaf growth in grassland regions is limited by water availability but often in combination with other factors. This model will advance the current understanding of phenology for ecosystem carbon models and our ability to predict future phenological behaviour.
Strategy optimization for mask rule check in wafer fab
Yang, Chuen Huei; Lin, Shaina; Lin, Roger; Wang, Alice; Lee, Rachel; Deng, Erwin
2015-07-01
Photolithography process is getting more and more sophisticated for wafer production following Moore's law. Therefore, for wafer fab, consolidated and close cooperation with mask house is a key to achieve silicon wafer success. However, generally speaking, it is not easy to preserve such partnership because many engineering efforts and frequent communication are indispensable. The inattentive connection is obvious in mask rule check (MRC). Mask houses will do their own MRC at job deck stage, but the checking is only for identification of mask process limitation including writing, etching, inspection, metrology, etc. No further checking in terms of wafer process concerned mask data errors will be implemented after data files of whole mask are composed in mask house. There are still many potential data errors even post-OPC verification has been done for main circuits. What mentioned here are the kinds of errors which will only occur as main circuits combined with frame and dummy patterns to form whole reticle. Therefore, strategy optimization is on-going in UMC to evaluate MRC especially for wafer fab concerned errors. The prerequisite is that no impact on mask delivery cycle time even adding this extra checking. A full-mask checking based on job deck in gds or oasis format is necessary in order to secure acceptable run time. Form of the summarized error report generated by this checking is also crucial because user friendly interface will shorten engineers' judgment time to release mask for writing. This paper will survey the key factors of MRC in wafer fab.
Optimal recruitment strategies for groups of interacting walkers with leaders
Martínez-García, Ricardo; López, Cristóbal; Vazquez, Federico
2015-02-01
We introduce a model of interacting random walkers on a finite one-dimensional chain with absorbing boundaries or targets at the ends. Walkers are of two types: informed particles that move ballistically towards a given target and diffusing uninformed particles that are biased towards close informed individuals. This model mimics the dynamics of hierarchical groups of animals, where an informed individual tries to persuade and lead the movement of its conspecifics. We characterize the success of this persuasion by the first-passage probability of the uninformed particle to the target, and we interpret the speed of the informed particle as a strategic parameter that the particle can tune to maximize its success. We find that the success probability is nonmonotonic, reaching its maximum at an intermediate speed whose value increases with the diffusing rate of the uninformed particle. When two different groups of informed leaders traveling in opposite directions compete, usually the largest group is the most successful. However, the minority can reverse this situation and become the most probable winner by following two different strategies: increasing its attraction strength or adjusting its speed to an optimal value relative to the majority's speed.
Glycosylation of therapeutic proteins: an effective strategy to optimize efficacy.
Solá, Ricardo J; Griebenow, Kai
2010-02-01
During their development and administration, protein-based drugs routinely display suboptimal therapeutic efficacies due to their poor physicochemical and pharmacological properties. These innate liabilities have driven the development of molecular strategies to improve the therapeutic behavior of protein drugs. Among the currently developed approaches, glycoengineering is one of the most promising, because it has been shown to simultaneously afford improvements in most of the parameters necessary for optimization of in vivo efficacy while allowing for targeting to the desired site of action. These include increased in vitro and in vivo molecular stability (due to reduced oxidation, cross-linking, pH-, chemical-, heating-, and freezing-induced unfolding/denaturation, precipitation, kinetic inactivation, and aggregation), as well as modulated pharmacodynamic responses (due to altered potencies from diminished in vitro enzymatic activities and altered receptor binding affinities) and improved pharmacokinetic profiles (due to altered absorption and distribution behaviors, longer circulation lifetimes, and decreased clearance rates). This article provides an account of the effects that glycosylation has on the therapeutic efficacy of protein drugs and describes the current understanding of the mechanisms by which glycosylation leads to such effects.
Noninfectious uveitis: strategies to optimize treatment compliance and adherence
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Dolz-Marco R
2015-08-01
Full Text Available Rosa Dolz-Marco,1 Roberto Gallego-Pinazo,1 Manuel Díaz-Llopis,2 Emmett T Cunningham Jr,3–6 J Fernando Arévalo7,8 1Unit of Macula, Department of Ophthalmology, University and Polytechnic Hospital La Fe, 2Faculty of Medicine, University of Valencia, Spain; 3Department of Ophthalmology, California Pacific Medical Center, San Francisco, 4Department of Ophthalmology, Stanford University School of Medicine, Stanford, 5The Francis I Proctor Foundation, University of California San Francisco Medical Center, 6West Coast Retina Medical Group, San Francisco, CA, USA; 7Vitreoretina Division, King Khaled Eye Specialist Hospital, Riyadh, Saudi Arabia; 8Retina Division, Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA Abstract: Noninfectious uveitis includes a heterogenous group of sight-threatening ocular and systemic disorders. Significant progress has been made in the treatment of noninfectious uveitis in recent years, particularly with regard to the effective use of corticosteroids and non-corticosteroid immunosuppressive drugs, including biologic agents. All of these therapeutic approaches are limited, however, by any given patient’s ability to comply with and adhere to their prescribed treatment. In fact, compliance and adherence are among the most important patient-related determinants of treatment success. We discuss strategies to optimize compliance and adherence. Keywords: noninfectious uveitis, intraocular inflammation, immunosuppressive treatment, adherence, compliance, therapeutic failure
Trading Regret for Efficiency: Online Convex Optimization with Long Term Constraints
Mahdavi, Mehrdad; Yang, Tianbao
2011-01-01
In this paper we propose a framework for solving constrained online convex optimization problem. Our motivation stems from the observation that most algorithms proposed for online convex optimization require a projection onto the convex set $\\mathcal{K}$ from which the decisions are made. While for simple shapes (e.g. Euclidean ball) the projection is straightforward, for arbitrary complex sets this is the main computational challenge and may be inefficient in practice. In this paper, we consider an alternative online convex optimization problem. Instead of requiring decisions belong to $\\mathcal{K}$ for all rounds, we only require that the constraints which define the set $\\mathcal{K}$ be satisfied in the long run. We show that our framework can be utilized to solve a relaxed version of online learning with side constraints addressed in \\cite{DBLP:conf/colt/MannorT06} and \\cite{DBLP:conf/aaai/KvetonYTM08}. By turning the problem into an online convex-concave optimization problem, we propose an efficient algo...
Scheiner, Samuel M
2016-05-01
Confronted with variable environments, species adapt in several ways, including genetic differentiation, a jack-of-all-trades strategy, or phenotypic plasticity. Adaptive habitat choice favors genetic differentiation and local adaptation over a generalist, jack-of-all-trades strategy. Models predict that, absent plasticity costs, variable environments generally favor phenotypic plasticity over genetic differentiation and being a jack-of-all-trades generalist. It is unknown how habitat choice might affect the evolution of plasticity. Using an individual-based simulation model, I explored the interaction of choice and plasticity. With only spatial variation, habitat choice promotes genetic differentiation over a jack-of-all-trades strategy or phenotypic plasticity. In the absence of plasticity, temporal variation favors a jack-of-all-trades strategy over choice-mediated genetic differentiation; when plasticity is an option, it is favored. This occurs because habitat choice creates a feedback between genetic differentiation and dispersal rates. As demes become better adapted to their local environments, the effective dispersal rate decreases, because more individuals have very high fitness and so choose not to disperse, reinforcing local stabilizing selection and negating selection for plasticity. Temporal variation breaks that feedback. These results point to a potential data paradox: systems with habitat choice may have the lowest actual movement rates. The potential for adaptive habitat choice may be very common, but its existence may reduce observed dispersal rates enough that we do not recognize systems where it may be present, warranting further exploration of likely systems.
DEVELOPMENT OF MARKETING STRATEGY AND ORGANIZATION OF THE TRADE-MARKETING EVENTS FOR CORPORATION
Directory of Open Access Journals (Sweden)
Miroshnichenko M. A.
2015-06-01
Full Text Available The article defines the feature of marketing activity focused on the future, in which the two sides are interested: producers and consumers. Five concepts of a resolution of conflict of interests of the company and clients are established. The essence and the content of marketing in corporation are considered, the plan of organization of the trade - marketing events in corporation is offered. On the basis of market research it is recommended to conduct local events with mechanisms aimed at final customer in the point of sale, on increasing the presence of the products of key customers in the point of sale in various formats: additional space sales, bandling or a gift for a purchase, discount or flyer
Congestion management rules and trading strategies in the Spanish electricity market
Energy Technology Data Exchange (ETDEWEB)
Furio, Dolores; Lucia, Julio J. [Departamento de Economia Financiera y Actuarial, Universidad de Valencia, Avda. Los Naranjos, s/n, 46022 - Valencia (Spain)
2009-01-15
This paper analyses the economic incentives embodied in the rules governing the resolution of transmission constraints in the Spanish wholesale electricity market and the way these incentives may have influenced on the trading behaviour of both the generators and the demand side. The evidence obtained is consistent with them responding to these incentives. In particular, buyers would respond to the way congestion costs are billed to them by abandoning the daily market in favour of the intraday market as far as possible. Additionally, some strategic generators may have been prompted the system operator to require them to inject electricity into the system to solve network congestions. Finally, these results may contribute to shed light on what should be expected of the reform in the aforementioned rules. (author)
Clicking and trading: Strategies of on-line banking in Spain
Directory of Open Access Journals (Sweden)
BEATRIZ SALVADOR
2006-06-01
Full Text Available The strategy of Spanish banks regarding online banking has moved cautiously between the sector modernization and the fear of third parties’ entry. In this paper we show how from the bubbling beginnings, institutions have moved towards a sound business part of a multichannel strategy. Still, Spanish institutions haven’t been able to rip all the advantages that Internet may have in the distribution of financial products.
Designing a Forex Trading and Equity Investment Strategy for the New-State Capital Hedge Fund
Malik, Rizvan
2008-01-01
Construct the investment strategy for the New-State Capital Hedge Fund. Identify profit making opportunities in Foreign Exchange (Forex) & Equities using both conventional and non-conventional indicators. The author is to articulate and document his current knowledge in the chosen area in order to stimuate ideas in creating potential investment strategies. Justify knowledge with actual results in a genuine live investment. Critique and evluate the effectiveness of the proposed investment ...
Zhang, Zili; Gao, Chao; Liu, Yuxin; Qian, Tao
2014-09-01
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.
Mahata, Puspita; Mahata, Gour Chandra; Kumar De, Sujit
2017-06-01
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.
Mathematical models and numerical algorithms for option pricing and optimal trading
Song, Na; 宋娜.
2013-01-01
Research conducted in mathematical finance focuses on the quantitative modeling of financial markets. It allows one to solve financial problems by using mathematical methods and provides understanding and prediction of the complicated financial behaviors. In this thesis, efforts are devoted to derive and extend stochastic optimization models in financial economics and establish practical algorithms for representing and solving problems in mathematical finance. An option gives the holder ...
Polymerase chain reaction: basic protocol plus troubleshooting and optimization strategies.
Lorenz, Todd C
2012-05-22
In the biological sciences there have been technological advances that catapult the discipline into golden ages of discovery. For example, the field of microbiology was transformed with the advent of Anton van Leeuwenhoek's microscope, which allowed scientists to visualize prokaryotes for the first time. The development of the polymerase chain reaction (PCR) is one of those innovations that changed the course of molecular science with its impact spanning countless subdisciplines in biology. The theoretical process was outlined by Keppe and coworkers in 1971; however, it was another 14 years until the complete PCR procedure was described and experimentally applied by Kary Mullis while at Cetus Corporation in 1985. Automation and refinement of this technique progressed with the introduction of a thermal stable DNA polymerase from the bacterium Thermus aquaticus, consequently the name Taq DNA polymerase. PCR is a powerful amplification technique that can generate an ample supply of a specific segment of DNA (i.e., an amplicon) from only a small amount of starting material (i.e., DNA template or target sequence). While straightforward and generally trouble-free, there are pitfalls that complicate the reaction producing spurious results. When PCR fails it can lead to many non-specific DNA products of varying sizes that appear as a ladder or smear of bands on agarose gels. Sometimes no products form at all. Another potential problem occurs when mutations are unintentionally introduced in the amplicons, resulting in a heterogeneous population of PCR products. PCR failures can become frustrating unless patience and careful troubleshooting are employed to sort out and solve the problem(s). This protocol outlines the basic principles of PCR, provides a methodology that will result in amplification of most target sequences, and presents strategies for optimizing a reaction. By following this PCR guide, students should be able to: • Set up reactions and thermal cycling
Aprison, Erin Z; Ruvinsky, Ilya
2014-01-01
To ensure long-term reproductive success organisms have to cope with harsh environmental extremes. A reproductive strategy that simply maximizes offspring production is likely to be disadvantageous because it could lead to a catastrophic loss of fecundity under unfavorable conditions. To understand how an appropriate balance is achieved, we investigated reproductive performance of C. elegans under conditions of chronic heat stress. We found that following even prolonged exposure to temperatures at which none of the offspring survive, worms could recover and resume reproduction. The likelihood of producing viable offspring falls precipitously after exposure to temperatures greater than 28°C primarily due to sperm damage. Surprisingly, we found that worms that experienced higher temperatures can recover considerably better, provided they did not initiate ovulation. Therefore mechanisms controlling this process must play a crucial role in determining the probability of recovery. We show, however, that suppressing ovulation is only beneficial under relatively long stresses, whereas it is a disadvantageous strategy under shorter stresses of the same intensity. This is because the benefit of shutting down egg laying, and thus protecting the reproductive system, is negated by the cost associated with implementing this strategy--it takes considerable time to recover and produce offspring. We interpret these balanced trade-offs as a dynamic response of the C. elegans reproductive system to stress and an adaptation to life in variable and unpredictable conditions.
Directory of Open Access Journals (Sweden)
Erin Z Aprison
Full Text Available To ensure long-term reproductive success organisms have to cope with harsh environmental extremes. A reproductive strategy that simply maximizes offspring production is likely to be disadvantageous because it could lead to a catastrophic loss of fecundity under unfavorable conditions. To understand how an appropriate balance is achieved, we investigated reproductive performance of C. elegans under conditions of chronic heat stress. We found that following even prolonged exposure to temperatures at which none of the offspring survive, worms could recover and resume reproduction. The likelihood of producing viable offspring falls precipitously after exposure to temperatures greater than 28°C primarily due to sperm damage. Surprisingly, we found that worms that experienced higher temperatures can recover considerably better, provided they did not initiate ovulation. Therefore mechanisms controlling this process must play a crucial role in determining the probability of recovery. We show, however, that suppressing ovulation is only beneficial under relatively long stresses, whereas it is a disadvantageous strategy under shorter stresses of the same intensity. This is because the benefit of shutting down egg laying, and thus protecting the reproductive system, is negated by the cost associated with implementing this strategy--it takes considerable time to recover and produce offspring. We interpret these balanced trade-offs as a dynamic response of the C. elegans reproductive system to stress and an adaptation to life in variable and unpredictable conditions.
Economic trade-offs amongst production diversification strategies in Brazilian coffee cooperatives
Directory of Open Access Journals (Sweden)
Fellipe Silva Martins
2014-01-01
Full Text Available Brazilian agricultural cooperatives have seen an unprecedented growth in production in the last decade which has led to several different product diversification strategies. Almost all studies in Brazil focus on the financial outcome of these strategies but few empirical studies have addressed them properly. Even fewer researches have dealt with the causes and possible strategies for the diversification of such cooperatives and their impact on their strategic planning. Hence, this paper aims at comprehending the different strategies in operations management for production diversification in coffee-producing cooperatives in south-eastern Brazil. This was done through a multi-case analysis comprising 6 coffee-producing cooperatives. The research analysed both verbal (through interviews and non-verbal (multi-criteria decision analysis responses to the causes of their diversification behaviours. It was possible to find out that most of the cooperatives’ rationale for diversifying is their pre-emptive response to financial crisis followed by increasing the number of associates as a strategy to overcome this economic struggle.
基于在线理论的股票算法交易策略研究%Study on the Stock Algorithmic Trading Strategy Based on Online Theory
Institute of Scientific and Technical Information of China (English)
朱莹; 茹少峰; 张文明
2015-01-01
运用在线理论研究多支股票算法交易策略。在El－Yaniv等人研究基础上，构造了单支股票买入问题的在线策略，证明该策略为最优在线策略；将构造的单支股票交易策略应用到多支股票交易策略问题中，设计了多支股票交易策略算法，并以每支股票收益加权进行投资组合；最后选择上证A股二十支股票从2009年到2012年的交易时间价格数据验证本文所提策略有效性。将20支股票随机抽取10支组成一组，选4组分别进行验证，结果表明本文所给策略对于任意选择的多支股票有较好收益。对交易周期分别选取10个偶数长度进行验证，发现交易周期为18天时平均收益最大，平均收益率为5．2％。%The online theory is used to study multi-stock algorithmic trading strategy .On the basis of El-Yaniv’s research , online buying strategy is established and proved to be the optimal online strategy;multi-stock algorith-mic trading strategy is designed and the investment portfolio is determined by weighting every stock yield with applying single stock trading strategy into multi-stock trading strategy .Transaction time data of twenty stocks , which are picked out of the A Stock of Shanghai Stock Exchange , is selected to test and verify the validity of the strategy mentioned in this paper .Ten stocks are randomly picked out of these twenty stocks to compose a group , and four groups are selected to be tested respectively , and the result indicates that the strategy proposed in this paper has better yield to any multi-stock.As for transaction cycle, ten even length is selected for test and the result implies the average yield will reach its maximum when the transaction cycle is eighteen and the average yield is 5.2%.
FOREIGN TRADE AT REGIONAL LEVEL IN ROMANIA AS A TOOL IN BUILDING SMART SPECIALISATION STRATEGIES
Directory of Open Access Journals (Sweden)
Constantin POSTOIU
2015-08-01
Full Text Available In the context of the new EU Cohesion Policy and Europe 2020 strategy, regions are encouraged to build their own development strategies based on specialisation and innovation. Smart specialisation strategies aim to identify and focus on those activities in which the region has comparative advantages and at the same time, are characterized by a high added value. These activities have the power to bring the greatest benefits to the local and regional economy and, thus, reduce disparities between regions and enhance overall competitiveness of European regions. This paper analyzes data on exports and imports at the county level, on sections and chapters of the Combined Nomenclature in order to identify trends of specialisation of economic activity. Moreover, this approach provides information on the competitiveness of these counties, high export rates indicating a better adaptation to international markets. Results show that the majority of counties import and, at the same time, export machinery and electrical equipment, and textiles and textile articles.
Zhu, Jun; Yan, Xuefeng; Zhao, Weixiang
2013-10-01
To solve chemical process dynamic optimization problems, a differential evolution algorithm integrated with adaptive scheduling mutation strategy (ASDE) is proposed. According to the evolution feedback information, ASDE, with adaptive control parameters, adopts the round-robin scheduling algorithm to adaptively schedule different mutation strategies. By employing an adaptive mutation strategy and control parameters, the real-time optimal control parameters and mutation strategy are obtained to improve the optimization performance. The performance of ASDE is evaluated using a suite of 14 benchmark functions. The results demonstrate that ASDE performs better than four conventional differential evolution (DE) algorithm variants with different mutation strategies, and that the whole performance of ASDE is equivalent to a self-adaptive DE algorithm variant and better than five conventional DE algorithm variants. Furthermore, ASDE was applied to solve a typical dynamic optimization problem of a chemical process. The obtained results indicate that ASDE is a feasible and competitive optimizer for this kind of problem.
Publish or Patent: Bibliometric evidence for empirical trade-offs in national funding strategies
Shelton, Robert D
2011-01-01
Multivariate linear regression models suggest a trade-off in allocations of national R&D investments. Government funding, and spending in the higher education sector, seem to encourage publications, whereas other components such as industrial funding, and spending in the business sector, encourage patenting. Our results help explain why the US trails the EU in publications, because of its focus on industrial funding - some 70% of its total R&D investment. Conversely, it also helps explain why the EU trails the US in patenting. Government funding is indicated as a negative incentive to high-quality patenting. The models here can also be used to predict an output indicator for a country, once the appropriate input indicator is known. This usually is done within a dataset for a single year, but the process can be extended to predict outputs a few years into the future, if reasonable forecasts can be made of the input indicators. We provide new forecasts about the further relationships of the US, the EU-2...
Self-service in Retail Trade of Consumer Cooperation: Assessment and Strategy of Development
Directory of Open Access Journals (Sweden)
Isaenko EV
2015-11-01
Full Text Available The article studies the necessity to convert consumer cooperatives’ stores into the self-service system, directions of self-service development strategy implementation in retailing. The authors analyze assessment methods of the sale process, a single store and a consumer cooperative organization in the whole.
Boundedly rational learning and heterogeneous trading strategies with hybrid neuro-fuzzy models
Bekiros, S.D.
2009-01-01
The present study deals with heterogeneous learning rules in speculative markets where heuristic strategies reflect the rules-of-thumb of boundedly rational investors. The major challenge for "chartists" is the development of new models that would enhance forecasting ability particularly for time
Boundedly rational learning and heterogeneous trading strategies with hybrid neuro-fuzzy models
S.D. Bekiros
2009-01-01
The present study deals with heterogeneous learning rules in speculative markets where heuristic strategies reflect the rules-of-thumb of boundedly rational investors. The major challenge for "chartists" is the development of new models that would enhance forecasting ability particularly for time se
The trade effects of endogenous preferential trade agreements
Egger, Peter; Larch, Mario; Staub, Kevin E; Winkelmann, Rainer
2010-01-01
Recent work by Anderson and van Wincoop (2003) establishes an empirical modelling strategy which takes full account of the structural, non-(log-)linear impact of trade barriers on trade in new trade theory models. Structural new trade theory models have never been used to evaluate and quantify the role of endogenous preferential trade agreement (PTA) membership for trade in a way which is consistent with general equilibrium. Apart from this gap, the present paper aims at delivering an empiric...
Institute of Scientific and Technical Information of China (English)
林存文
2012-01-01
By using the input-output table and indicators of foreign trade product structure rationality,this empirical study showed that the optimization of foreign trade structure has a positive promotion effect on foreign trade growth mode transformation,and put forward suggestions for implementing of strategy of innovation-oriented import structure optimization.%本文基于投入产出表,借助外贸产品结构合理度指标,通过实证检验,不仅分析了当前我国进出口商品结构的优化情况,而且验证了进口结构优化对外贸增长方式转变具有正向促进作用,并提出了实行创新导向型进口结构优化战略的政策建议。
Gas Chromatograph Method Optimization Trade Study for RESOLVE: 20-meter Column v. 8-meter Column
Huz, Kateryna
2014-01-01
RESOLVE is the payload on a Class D mission, Resource Prospector, which will prospect for water and other volatile resources at a lunar pole. The RESOLVE payload's primary scientific purpose includes determining the presence of water on the moon in the lunar regolith. In order to detect the water, a gas chromatograph (GC) will be used in conjunction with a mass spectrometer (MS). The goal of the experiment was to compare two GC column lengths and recommend which would be best for RESOLVE's purposes. Throughout the experiment, an Inficon Fusion GC and an Inficon Micro GC 3000 were used. The Fusion had a 20m long column with 0.25mm internal diameter (Id). The Micro GC 3000 had an 8m long column with a 0.32mm Id. By varying the column temperature and column pressure while holding all other parameters constant, the ideal conditions for testing with each column length in their individual instrument configurations were determined. The criteria used for determining the optimal method parameters included (in no particular order) (1) quickest run time, (2) peak sharpness, and (3) peak separation. After testing numerous combinations of temperature and pressure, the parameters for each column length that resulted in the most optimal data given my three criteria were selected. The ideal temperature and pressure for the 20m column were 95 C and 50psig. At this temperature and pressure, the peaks were separated and the retention times were shorter compared to other combinations. The Inficon Micro GC 3000 operated better at lower temperature mainly due to the shorter 8m column. The optimal column temperature and pressure were 70 C and 30psig. The Inficon Micro GC 3000 8m column had worse separation than the Inficon Fusion 20m column, but was able to separate water within a shorter run time. Therefore, the most significant tradeoff between the two column lengths was peak separation of the sample versus run time. After performing several tests, it was concluded that better
Supply Chain Optimized Strategies in the Mode of External Financing
Institute of Scientific and Technical Information of China (English)
Wenyi; DU; Xingzheng; AI; Xiaowo; TANG
2015-01-01
In the circumstance that market demand is uncertain,it studies the decision-making problem of supply chain financial system consisting of the single supplier,a capital constraint retailer and a bank. Considering the mode of external financing,we obtain the optimal order decision of the capital constraint retailer,the optimal financing rate and the optimal wholesale price of the supplier and analyze the effects of owned capitals of retailer on the optimized decision-making of supply chain financial system. At last,it demonstrates the effectiveness of conclusion by numerical examples.
Synergies, Conflicts, and Trade-offs of C40 Cities Adaptation Strategies
DEFF Research Database (Denmark)
Driscoll, Patrick Arthur; De Rosa, Michele; Lehmann, Martin
2013-01-01
There is a growing body of literature in the field of urban climate change adaptation planning that indicate a need to address climate change planning measures from a more holistic sustainable development perspective. This paper presents the findings from a recently completed study that indicates...... there remain significant unresolved tensions between the development pathways and the climate change adaptation strategies of the 58 cities within the C40 Cities Climate Leadership Group....
Directory of Open Access Journals (Sweden)
Rizky Luxianto
2014-08-01
Full Text Available This paper wants to explore the effectiveness of momentum or contrarian strategy in Indonesian Stock Exchange using different methods in measuring the performance. The point of momentum or contrarian strategy is selecting winner (stocks with highest gain or loser stocks (stocks with highest loss and then buy or sell it based on the research result. This research employed three methods in measuring performance to select winner and loser stocks. The irst method used cross section relative return, while the second method used cross section relative return plus risk component (return divided by standard deviation, and the third method employed historical relative return instead of cross section. The result is that, all of those three methods prove that momentum strategy is effectively applicable for winner stock, so in the next period winner stock will continue to make profit, while for loser stock, it is more effective to use contrarian strategy because in the next period, loser stock will rebound and make proit after suffering from high loss. ";} // -->activate javascript
Intention-Disguised Algorithmic Trading
Yuen, William; Syverson, Paul; Liu, Zhenming; Thorpe, Christopher
Large market participants (LMPs) must often execute trades while keeping their intentions secret. Sometimes secrecy is required before trades are completed to prevent other traders from anticipating (and exploiting) the price impact of their trades. This is known as "front-running". In other cases, LMPs with proprietary trading strategies wish to keep their positions secret even after trading because their strategies and positions contain valuable information. LMPs include hedge funds, mutual funds, and other specialized market players.
Optimal approximation method to characterize the resource trade-off functions for media servers
Chang, Ray-I.
1999-08-01
We have proposed an algorithm to smooth the transmission of the pre-recorded VBR media stream. It takes O(n) time complexity, where n is large, this algorithm is not suitable for online resource management and admission control in media servers. To resolve this drawback, we have explored the optimal tradeoff among resources by an O(nlogn) algorithm. Based on the pre-computed resource tradeoff function, the resource management and admission control procedure is as simple as table hashing. However, this approach requires O(n) space to store and maintain the resource tradeoff function. In this paper, while giving some extra resources, a linear-time algorithm is proposed to approximate the resource tradeoff function by piecewise line segments. We can prove that the number of line segments in the obtained approximation function is minimized for the given extra resources. The proposed algorithm has been applied to approximate the bandwidth-buffer-tradeoff function of the real-world Star War movie. While an extra 0.1 Mbps bandwidth is given, the storage space required for the approximation function is over 2000 times smaller than that required for the original function. While an extra 10 KB buffer is given, the storage space for the approximation function is over 2200 over times smaller than that required for the original function. The proposed algorithm is really useful for resource management and admission control in real-world media servers.
Offshore Wind Farm Layout Design Considering Optimized Power Dispatch Strategy
DEFF Research Database (Denmark)
Hou, Peng; Hu, Weihao; N. Soltani, Mohsen
2017-01-01
leading to energy losses. It is expected that the optimized placement of wind turbines (WT) over a large sea area can lead to the best tradeoff between energy yields and capital investment. This paper proposes a novel way to position offshore WTs for a regular shaped wind farm. In addition to optimizing...
Educational Tool for Optimal Controller Tuning Using Evolutionary Strategies
Carmona Morales, D.; Jimenez-Hornero, J. E.; Vazquez, F.; Morilla, F.
2012-01-01
In this paper, an optimal tuning tool is presented for control structures based on multivariable proportional-integral-derivative (PID) control, using genetic algorithms as an alternative to traditional optimization algorithms. From an educational point of view, this tool provides students with the necessary means to consolidate their knowledge on…
A trust-region strategy for manifold-mapping optimization
Hemker, P.W.; Echeverria, D.
2007-01-01
Studying the space-mapping technique by Bandler et al. [J. Bandler, R. Biernacki, S. Chen, P. Grobelny, R.H. Hemmers, Space mapping technique for electromagnetic optimization, IEEE Trans. Microwave Theory Tech. 42 (1994) 2536–2544] for the solution of optimization problems, we observe the possible d
A trust-region strategy for manifold mapping optimization.
Hemker, P.W.; Echeverria, D.
2006-01-01
As a starting point we take the space-mapping iteration technique by Bandler et al. for the efficient solution of optimization problems. This technique achieves acceleration of accurate design processes with the help of simpler, easier to optimize models. We observe the difference between the soluti
Model-based Optimization of Oil Recovery: Robust Operational Strategies
Van Essen, G.M.
2015-01-01
The process of depleting an oil reservoir can be poured into an optimal control problem with the objective to maximize economic performance over the life of the ﬁeld. Despite its large potential, life-cycle optimization has not yet found its way into operational environments. The objective of this t
Global Optimization strategies for two-mode clustering
J.M. van Rosmalen (Joost); P.J.F. Groenen (Patrick); J. Trejos (Javier); W. Castilli
2005-01-01
textabstractTwo-mode clustering is a relatively new form of clustering that clusters both rows and columns of a data matrix. To do so, a criterion similar to k-means is optimized. However, it is still unclear which optimization method should be used to perform two-mode clustering, as various meth
Directory of Open Access Journals (Sweden)
Kui-Ting CHEN
2015-12-01
Full Text Available Capacitated vehicle routing problem with pickups and deliveries (CVRPPD is one of the most challenging combinatorial optimization problems which include goods delivery/pickup optimization, vehicle number optimization, routing path optimization and transportation cost minimization. The conventional particle swarm optimization (PSO is difficult to find an optimal solution of the CVRPPD due to its simple search strategy. A PSO with adaptive multi-swarm strategy (AMSPSO is proposed to solve the CVRPPD in this paper. The proposed AMSPSO employs multiple PSO algorithms and an adaptive algorithm with punishment mechanism to search the optimal solution, which can deal with large-scale optimization problems. The simulation results prove that the proposed AMSPSO can solve the CVRPPD with the least number of vehicles and less transportation cost, simultaneously.
Optimal Strategy for Inspection and Repair of Structural Systems
DEFF Research Database (Denmark)
Thoft-Christensen, Palle; Sørensen, John Dalsgaard
1987-01-01
A new strategy for inspection and repair of structural elements and systems is presented. The total cost of inspection and repair is minimized with the constraints that the reliability of elements and/or of the structural system are acceptable. The design variables are the time intervals between...... inspections and the quality of the inspections. Numerical examples are presented to illustrate the performance of the strategy. The strategy can be used for any engineering system where inspection and repair are required....
NAFTA and member country strategies for maritime trade and marine invasive species.
Fernandez, Linda
2008-12-01
Maritime shipping has two vectors of spreading marine invasive species: ballast water inside the ship and biofouling on the hulls outside the ship. While some attention has focused on ballast water, virtually none is focused on biofouling. This paper offers a quantitative analysis of economic incentives for shippers and regulating ports to address both pollution vectors. The strategies to address the vectors are induced by incentive mechanisms involving liability, subsidies and taxes. Results show these offer ample incentives in order to truly foster abatement of both vectors. Data from North America's Pacific coast is included in the analysis.
Open- and closed-loop multiobjective optimal strategies for HIV therapy using NSGA-II.
Heris, S Mostapha Kalami; Khaloozadeh, Hamid
2011-06-01
In this paper, multiobjective open- and closed-loop optimal treatment strategies for HIV/AIDS are presented. It is assumed that highly active antiretroviral therapy is available for treatment of HIV infection. Amount of drug usage and the quality of treatment are defined as two objectives of a biobjective optimization problem, and Nondominated Sorting Genetic Algorithm II is used to solve this problem. Open- and closed-loop control strategies are used to produce optimal control inputs, and the Pareto frontiers obtained from these two strategies are compared. Pareto frontier, resulted from the optimization process, suggests a set of treatment strategies, which all are optimal from a perspective, and can be used in different medical and economic conditions. Robustness of closed-loop system in the presence of measurement noises is analyzed, assuming various levels of noise.
Directory of Open Access Journals (Sweden)
Yin Aiwei
2016-01-01
Full Text Available To reduce the influence of wind power random on system operation, energy storage systems (ESSs and demand response (DR are introduced to the traditional scheduling model of wind power and thermal power with carbon emission trading (CET. Firstly, a joint optimization scheduling model for wind power, thermal power, and ESSs is constructed. Secondly, DR and CET are integrated into the joint scheduling model. Finally, 10 thermal power units, a wind farm with 2800 MW of installed capacity, and 3×80 MW ESSs are taken as the simulation system for verifying the proposed models. The results show backup service for integrating wind power into the grid is provided by ESSs based on their charge-discharge characteristics. However, system profit reduces due to ESSs’ high cost. Demand responses smooth the load curve, increase profit from power generation, and expand the wind power integration space. After introducing CET, the generation cost of thermal power units and the generation of wind power are both increased; however, the positive effect of DR on the system profit is also weakened. The simulation results reach the optimum when both DR and CET are introduced.
Wakano, Joe Yuichiro; Miura, Chiaki
2014-02-01
Inheritance of culture is achieved by social learning and improvement is achieved by individual learning. To realize cumulative cultural evolution, social and individual learning should be performed in this order in one's life. However, it is not clear whether such a learning schedule can evolve by the maximization of individual fitness. Here we study optimal allocation of lifetime to learning and exploitation in a two-stage life history model under a constant environment. We show that the learning schedule by which high cultural level is achieved through cumulative cultural evolution is unlikely to evolve as a result of the maximization of individual fitness, if there exists a trade-off between the time spent in learning and the time spent in exploiting the knowledge that has been learned in earlier stages of one's life. Collapse of a fully developed culture is predicted by a game-theoretical analysis where individuals behave selfishly, e.g., less learning and more exploiting. The present study suggests that such factors as group selection, the ability of learning-while-working ("on the job training"), or environmental fluctuation might be important in the realization of rapid and cumulative cultural evolution that is observed in humans.
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...
Optimizing the stirring strategy for the vibrating intrinsic reverberation chamber
Serra, Ramiro; Leferink, Frank
2010-01-01
This work describes the definition, application and assessment of a factorial plan with the aim of gaining insight on what kind of stirring strategy could work the best in a vibrating intrinsic reverberation chamber. Three different stirring strategies were defined as factors of a factorial analysis
A Cascade Optimization Strategy for Solution of Difficult Multidisciplinary Design Problems
Patnaik, Surya N.; Coroneos, Rula M.; Hopkins, Dale A.; Berke, Laszlo
1996-01-01
A research project to comparatively evaluate 10 nonlinear optimization algorithms was recently completed. A conclusion was that no single optimizer could successfully solve all 40 problems in the test bed, even though most optimizers successfully solved at least one-third of the problems. We realized that improved search directions and step lengths, available in the 10 optimizers compared, were not likely to alleviate the convergence difficulties. For the solution of those difficult problems we have devised an alternative approach called cascade optimization strategy. The cascade strategy uses several optimizers, one followed by another in a specified sequence, to solve a problem. A pseudorandom scheme perturbs design variables between the optimizers. The cascade strategy has been tested successfully in the design of supersonic and subsonic aircraft configurations and air-breathing engines for high-speed civil transport applications. These problems could not be successfully solved by an individual optimizer. The cascade optimization strategy, however, generated feasible optimum solutions for both aircraft and engine problems. This paper presents the cascade strategy and solutions to a number of these problems.
Asset price dynamics in a financial market with heterogeneous trading strategies and time delays
Sansone, Alessandro; Garofalo, Giuseppe
2007-08-01
In this paper we present a continuous time dynamical model of heterogeneous agents interacting in a financial market where transactions are cleared by a market maker. The market is composed of fundamentalist, trend following and contrarian agents who process market information with different time delays. Each class of investors is characterized by path dependent risk aversion. We also allow for the possibility of evolutionary switching between trend following and contrarian strategies. We find that the system shows periodic, quasi-periodic and chaotic dynamics as well as synchronization between technical traders. Furthermore, the model is able to generate time series of returns that exhibit statistical properties similar to those of the S&P 500 index, which is characterized by excess kurtosis, volatility clustering and long memory.
Optimal strategy for controlling the spread of Plasmodium Knowlesi malaria: Treatment and culling
Abdullahi, Mohammed Baba; Hasan, Yahya Abu; Abdullah, Farah Aini
2015-05-01
Plasmodium Knowlesi malaria is a parasitic mosquito-borne disease caused by a eukaryotic protist of genus Plasmodium Knowlesi transmitted by mosquito, Anopheles leucosphyrus to human and macaques. We developed and analyzed a deterministic Mathematical model for the transmission of Plasmodium Knowlesi malaria in human and macaques. The optimal control theory is applied to investigate optimal strategies for controlling the spread of Plasmodium Knowlesi malaria using treatment and culling as control strategies. The conditions for optimal control of the Plasmodium Knowlesi malaria are derived using Pontryagin's Maximum Principle. Finally, numerical simulations suggested that the combination of the control strategies is the best way to control the disease in any community.
On Optimality of the Barrier Strategy for the Classical Risk Model with Interest
Institute of Scientific and Technical Information of China (English)
Ying Fang; Rong Wu
2011-01-01
In this paper, we consider the optimal dividend problem for a classical risk model with a constant force of interest. For such a risk model, a sufficient condition under which a barrier strategy is the optimal strategy is presented for general claim distributions. When claim sizes are exponentially distributed, it is shown that the optimal dividend policy is a barrier strategy and the maximal dividend-value function is a concave function. Finally, some known results relating to the distribution of aggregate dividends before ruin are extended.
Immune clonal selection optimization method with combining mutation strategies
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
In artificial immune optimization algorithm, the mutation of immune cells has been considered as the key operator that determines the algorithm performance. Traditional immune optimization algorithms have used a single mutation operator, typically a Gaussian. Using a variety of mutation operators that can be combined during evolution to generate different probability density function could hold the potential for producing better solutions with less computational effort. In view of this, a linear combination...
Optimizing the 3R Study Strategy to Learn from Text
Reijners, Pauline; Kester, Liesbeth; Wetzels, Sandra; Kirschner, Paul A.
2014-01-01
Learning from text is often very difficult for students. In this presentation the results of a study with the 3R study strategy are presented in which possible mechanisms for stimulating successful text learning are discussed.
Optimal scan strategies for future CMB satellite experiments
Wallis, Christopher G R; Battye, Richard A; Delabrouille, Jacques
2016-01-01
The B-mode polarisation power spectrum in the Cosmic Microwave Background (CMB) is about four orders of magnitude fainter than the CMB temperature power spectrum. Any instrumental imperfections that couple temperature fluctuations to B-mode polarisation must therefore be carefully controlled and/or removed. We investigate the role that a scan strategy can have in mitigating certain common systematics by averaging systematic errors down with many crossing angles. We present approximate analytic forms for the error on the recovered B-mode power spectrum that would result from differential gain, differential pointing and differential ellipticity for the case where two detector pairs are used in a polarisation experiment. We use these analytic predictions to search the parameter space of common satellite scan strategies in order to identify those features of a scan strategy that have most impact in mitigating systematic effects. As an example we go on to identify a scan strategy suitable for the CMB satellite pro...
Optimal scan strategies for future CMB satellite experiments
Wallis, Christopher G. R.; Brown, Michael L.; Battye, Richard A.; Delabrouille, Jacques
2017-04-01
The B-mode polarization power spectrum in the cosmic microwave background (CMB) is about four orders of magnitude fainter than the CMB temperature power spectrum. Any instrumental imperfections that couple temperature fluctuations to B-mode polarization must therefore be carefully controlled and/or removed. We investigate the role that a scan strategy can have in mitigating certain common systematics by averaging systematic errors down with many crossing angles. We present approximate analytic forms for the error on the recovered B-mode power spectrum that would result from differential gain, differential pointing and differential ellipticity for the case where two detector pairs are used in a polarization experiment. We use these analytic predictions to search the parameter space of common satellite scan strategies in order to identify those features of a scan strategy that have most impact in mitigating systematic effects. As an example, we go on to identify a scan strategy suitable for the CMB satellite proposed for the European Space Agency M5 call, considering the practical considerations of fuel requirement, data rate and the relative orientation of the telescope to the earth. Having chosen a scan strategy we then go on to investigate the suitability of the scan strategy.
Directory of Open Access Journals (Sweden)
Zeyu Chen
2015-04-01
Full Text Available Plug-in hybrid electric vehicles (PHEVs have been recognized as one of the most promising vehicle categories nowadays due to their low fuel consumption and reduced emissions. Energy management is critical for improving the performance of PHEVs. This paper proposes an energy management approach based on a particle swarm optimization (PSO algorithm. The optimization objective is to minimize total energy cost (summation of oil and electricity from vehicle utilization. A main drawback of optimal strategies is that they can hardly be used in real-time control. In order to solve this problem, a rule-based strategy containing three operation modes is proposed first, and then the PSO algorithm is implemented on four threshold values in the presented rule-based strategy. The proposed strategy has been verified by the US06 driving cycle under the MATLAB/Simulink software environment. Two different driving cycles are adopted to evaluate the generalization ability of the proposed strategy. Simulation results indicate that the proposed PSO-based energy management method can achieve better energy efficiency compared with traditional blended strategies. Online control performance of the proposed approach has been demonstrated through a driver-in-the-loop real-time experiment.
Optimization strategy for element sizing in hybrid power systems
del Real, Alejandro J.; Arce, Alicia; Bordons, Carlos
This paper presents a procedure to evaluate the optimal element sizing of hybrid power systems. In order to generalize the problem, this work exploits the "energy hub" formulation previously presented in the literature, defining an energy hub as an interface among energy producers, consumers and the transportation infrastructure. The resulting optimization minimizes an objective function which is based on costs and efficiencies of the system elements, while taking into account the hub model, energy and power constraints and estimated operational conditions, such as energy prices, input power flow availability and output energy demand. The resulting optimal architecture also constitutes a framework for further real-time control designs. Moreover, an example of a hybrid storage system is considered. In particular, the architecture of a hybrid plant incorporating a wind generator, batteries and intermediate hydrogen storage is optimized, based on real wind data and averaged residential demands, also taking into account possible estimation errors. The hydrogen system integrates an electrolyzer, a fuel cell stack and hydrogen tanks. The resulting optimal cost of such hybrid power plant is compared with the equivalent hydrogen-only and battery-only systems, showing improvements in investment costs of almost 30% in the worst case.
Optimization strategy for element sizing in hybrid power systems
Energy Technology Data Exchange (ETDEWEB)
del Real, Alejandro J.; Arce, Alicia; Bordons, Carlos [Departamento de Ingenieria de Sistemas y Automatica, Universidad de Sevilla, 41092 Sevilla (Spain)
2009-08-01
This paper presents a procedure to evaluate the optimal element sizing of hybrid power systems. In order to generalize the problem, this work exploits the ''energy hub'' formulation previously presented in the literature, defining an energy hub as an interface among energy producers, consumers and the transportation infrastructure. The resulting optimization minimizes an objective function which is based on costs and efficiencies of the system elements, while taking into account the hub model, energy and power constraints and estimated operational conditions, such as energy prices, input power flow availability and output energy demand. The resulting optimal architecture also constitutes a framework for further real-time control designs. Moreover, an example of a hybrid storage system is considered. In particular, the architecture of a hybrid plant incorporating a wind generator, batteries and intermediate hydrogen storage is optimized, based on real wind data and averaged residential demands, also taking into account possible estimation errors. The hydrogen system integrates an electrolyzer, a fuel cell stack and hydrogen tanks. The resulting optimal cost of such hybrid power plant is compared with the equivalent hydrogen-only and battery-only systems, showing improvements in investment costs of almost 30% in the worst case. (author)
Directory of Open Access Journals (Sweden)
Sathya Swaroop Debasish
2012-12-01
Full Text Available The primary objective of the study is to investigate the existence of seasonality in stock price behavior in Indian stock market and more specifically in the IT sector. The period of the study is from 3rd November 1994 to 31st December 2010. The study has employed daily price series of selected seven IT companies obtained from the official website of National Stock Exchange (NSE. The study used multiple regression technique to examine the significance of the regression coefficient for investigating day of week effects and week of the month effect, and Kruskal Wallis for analysis of trading strategy. It is found that all the seven selected IT companies evidenced day of the week effect and mostly either on Monday, Tuesday or Wednesday. Only Patni and Wipro evidenced significant Thursday effect. Similarly, evidence on week of month effect mostly either on 1st week, 2nd week or 3rd week. This implies that active portfolio management taking into account the findings will provide superior returns on investment in the IT sector in India.
Directory of Open Access Journals (Sweden)
Frolov A.V.
2016-03-01
Conclusions. Application of the original model of risk stratification will allow to optimize the general management in DCM and the strategy of timely selection of potential candidates for implantation of cardioverter- defibrillator for the primary prevention of SCD.
Real-time optimization power-split strategy for hybrid electric vehicles
Institute of Scientific and Technical Information of China (English)
XIA ChaoYing; ZHANG Cong
2016-01-01
Energy management strategies based on optimal control theory can achieve minimum fuel consumption for hybrid electric vehicles,but the requirement for driving cycles known in prior leads to a real-time problem.A real-time optimization power-split strategy is proposed based on linear quadratic optimal control.The battery state of charge sustainability and fuel economy are ensured by designing a quadratic performance index combined with two rules.The engine power and motor power of this strategy are calculated in real-time based on current system state and command,and not related to future driving conditions.The simulation results in ADVISOR demonstrate that,under the conditions of various driving cycles,road slopes and vehicle parameters,the proposed strategy significantly improves fuel economy,which is very close to that of the optimal control based on Pontryagin's minimum principle,and greatly reduces computation complexity.
Energy Technology Data Exchange (ETDEWEB)
Boedeker, K.; Moebus, H.; Senkbeil, H. [eds.
1998-12-31
A manual for electrical trade with the following topics: New buissiness sectors, installation and building engineering, standards, tasks and responsibility of qualified personnel in electrical engineering, safety of electrical devices installed and an optimal management of electrical companies.(GL) [Deutsch] Ein Handbuch fuer das Elektrohandwerk mit folgenden Schwerpunkten: Neue Geschaeftsfelder, Installations- und Haustechnik, Normen, Aufgaben und Verantwortung der Elektrofachkraefte, Sicherheit beim Einbau von Anlagen sowie die optimale Betriebsfuehrung in der Elektrobranche.(GL)
On-Demand Based Wireless Resources Trading for Green Communications
Cheng, Wenchi; Zhang, Hailin; Wang, Qiang
2011-01-01
The purpose of Green Communications is to reduce the energy consumption of the communication system as much as possible without compromising the quality of service (QoS) for users. An effective approach for Green Wireless Communications is On-Demand strategy, which scales power consumption with the volume and location of user demand. Applying the On-Demand Communications model, we propose a novel scheme -- Wireless Resource Trading, which characterizes the trading relationship among different wireless resources for a given number of performance metrics. According to wireless resource trading relationship, different wireless resources can be consumed for the same set of performance metrics. Therefore, to minimize the energy consumption for given performance metrics, we can trade the other type of wireless resources for the energy resource under the demanded performance metrics. Based on the wireless resource trading relationship, we derive the optimal energy-bandwidth and energy-time wireless resource trading ...
Šatanová, Martina
2013-01-01
The thesis is dealing with trading based on nonpublic information (insider trading). It contains development of insider trading regulation and describes specifics of american, czech, japanese and chinese market consodering insider trading. It is focused on regulation, investigation and evidence.
Institute of Scientific and Technical Information of China (English)
肖黎; 邓旭霞
2012-01-01
湖南是个农业大省,但湖南农产品出口贸易与之很不相称,其年农产品出口总值占全国农产品出口总值的比重极低,只有1%左右,关键原因是湖南农产品出口贸易结构不合理。解决对策就是要调整优化农产品出口贸易结构：实施市场多元化战略,加强农业产业化基地和深加工基地建设,生产具有出口竞争优势的特色产品,支持和引导农产品出口企业发展自有品牌,强化农产品质量安全管理,创新扩大农产品出口贸易结构优化的政策支持体系等。%Hunan is a major agricultural province.But the Hunan export trade of agricultural products is not proportionate to the annual agricultural exports,accounted for very low share of agricultural exports,only around 1%,the key reason is the irrational structure of Hunan agricultural export trade.Solution is to adjust agricultural export trade structure： Implementing the strategy of market diversification,strengthening the construction of agricultural industrialization base and processing bases,production featured product export competitive advantages,support and guide development of own-brand agricultural products export enterprises,strengthening of agricultural product quality safety management,innovation policy to expand agricultural export trade structure optimization support system.
Directory of Open Access Journals (Sweden)
Musa Danjuma SHEHU
2008-06-01
Full Text Available This paper lays emphasis on formulation of two dimensional differential games via optimal control theory and consideration of control systems whose dynamics is described by a system of Ordinary Differential equation in the form of linear equation under the influence of two controls U(. and V(.. Base on this, strategies were constructed. Hence we determine the optimal strategy for a control say U(. under a perturbation generated by the second control V(. within a given manifold M.
The CEV Model and Its Application in a Study of Optimal Investment Strategy
Directory of Open Access Journals (Sweden)
Aiyin Wang
2014-01-01
Full Text Available The constant elasticity of variance (CEV model is used to describe the price of the risky asset. Maximizing the expected utility relating to the Hamilton-Jacobi-Bellman (HJB equation which describes the optimal investment strategies, we obtain a partial differential equation. Applying the Legendre transform, we transform the equation into a dual problem and obtain an approximation solution and an optimal investment strategies for the exponential utility function.
AN ASSESSMENT AND OPTIMIZATION OF QUALITY OF STRATEGY PROCESS
Directory of Open Access Journals (Sweden)
Snezana Nestic
2013-12-01
Full Text Available In order to improve the quality of their processes companies usually rely on quality management systems and the requirements of ISO 9001:2008. The small and medium-sized companies are faced with a series of challenges in objectification, evaluation and assessment of the quality of processes. In this paper, the strategy process is decomposed for one typical medium size of manufacturing company and the indicators of the defined sub processes, based on the requirements of ISO 9001:2008, are developed. The weights of sub processes are calculated using fuzzy set approach. Finally, the developed solution based on the genetic algorithm approach is presented and tested on data from 142 manufacturing companies. The presented solution enables assessment of the quality of a strategy process, ranks the indicators and provides a basis for successful improvement of the quality of the strategy process.
Optimization Strategies to Increase Electrical Distribution Networks Robustness
Directory of Open Access Journals (Sweden)
Dorin Sarchiz
2010-12-01
Full Text Available The paper aims to present a mathematical model to optimize power distribution network graph, in terms of increasing its robustness, ie to reduce the risk of destruction (its removal from service – accidentally or intentionally, with applications to the distribution networks 20 kV and 110 kV, County Mures.
Evolutionary and principled search strategies for sensornet protocol optimization.
Tate, Jonathan; Woolford-Lim, Benjamin; Bate, Iain; Yao, Xin
2012-02-01
Interactions between multiple tunable protocol parameters and multiple performance metrics are generally complex and unknown; finding optimal solutions is generally difficult. However, protocol tuning can yield significant gains in energy efficiency and resource requirements, which is of particular importance for sensornet systems in which resource availability is severely restricted. We address this multi-objective optimization problem for two dissimilar routing protocols and by two distinct approaches. First, we apply factorial design and statistical model fitting methods to reject insignificant factors and locate regions of the problem space containing near-optimal solutions by principled search. Second, we apply the Strength Pareto Evolutionary Algorithm 2 and Two-Archive evolutionary algorithms to explore the problem space, with each iteration potentially yielding solutions of higher quality and diversity than the preceding iteration. Whereas a principled search methodology yields a generally applicable survey of the problem space and enables performance prediction, the evolutionary approach yields viable solutions of higher quality and at lower experimental cost. This is the first study in which sensornet protocol optimization has been explicitly formulated as a multi-objective problem and solved with state-of-the-art multi-objective evolutionary algorithms.
Optimization of Decommission Strategy for Offshore Wind Farms
DEFF Research Database (Denmark)
Hou, Peng; Hu, Weihao; Soltani, Mohsen
2016-01-01
The life time of offshore wind farm is around 20 years. After that, the whole farm should be decommissioned which is also one of the main factors that contribute to the high investment. In order to make a costeffective wind farm, a novel optimization method for decommission is addressed...
Motion Structural Optimization Strategy for Rhombic Element Based Foldable Structure
Directory of Open Access Journals (Sweden)
Seung Hyun Jeong
2015-02-01
Full Text Available This research presents a new systematical design approach of foldable structure composed of several rhombic elements by applying genetic algorithm. As structural shapes represented by a foldable structure can be easily and dramatically morphed by manipulating rotational directions and angle of joints, the foldable structure has been used for various elementary structural members and engineering mechanisms. However a systematic design approach determining detail rotational angle and directions of unit cells for arbitrary shaped target areas has not been proposed yet. This research contributes to it by developing a new structural optimization method determining optimal angle and rotation directions to cover arbitrary shaped target areas of interest with aggregated rhombic elements. To achieve this purpose, we present an optimization formulation minimizing the sum of distances between each reference joint of an arbitrary shaped target area and its closest outer joints of foldable structure. To find out the outer joint set of a given foldable structure, an efficient geometric analysis method based on Delaunay triangulation is also developed and implemented. To show the validity and limitations of the present approach, several foldable structure design problems for two-dimensional arbitrary shaped target areas are solved with the present optimization procedure.
Taxing Strategies for Carbon Emissions: A Bilevel Optimization Approach
Directory of Open Access Journals (Sweden)
Wei Wei
2014-04-01
Full Text Available This paper presents a quantitative and computational method to determine the optimal tax rate among generating units. To strike a balance between the reduction of carbon emission and the profit of energy sectors, the proposed bilevel optimization model can be regarded as a Stackelberg game between the government agency and the generation companies. The upper-level, which represents the government agency, aims to limit total carbon emissions within a certain level by setting optimal tax rates among generators according to their emission performances. The lower-level, which represents decision behaviors of the grid operator, tries to minimize the total production cost under the tax rates set by the government. The bilevel optimization model is finally reformulated into a mixed integer linear program (MILP which can be solved by off-the-shelf MILP solvers. Case studies on a 10-unit system as well as a provincial power grid in China demonstrate the validity of the proposed method and its capability in practical applications.
Optimal Input Strategy for Plug and Play Process Control Systems
DEFF Research Database (Denmark)
Kragelund, Martin Nygaard; Leth, John-Josef; Wisniewski, Rafal
2010-01-01
This paper considers the problem of optimal operation of a plant, which goal is to maintain production at minimum cost. The system considered in this work consists of a joined plant and redundant input systems. It is assumed that each input system contributes to a flow of goods into the joined part...
React or wait: which optimal culling strategy to control infectious diseases in wildlife.
Bolzoni, Luca; Tessoni, Valentina; Groppi, Maria; De Leo, Giulio A
2014-10-01
We applied optimal control theory to an SI epidemic model to identify optimal culling strategies for diseases management in wildlife. We focused on different forms of the objective function, including linear control, quadratic control, and control with limited amount of resources. Moreover, we identified optimal solutions under different assumptions on disease-free host dynamics, namely: self-regulating logistic growth, Malthusian growth, and the case of negligible demography. We showed that the correct characterization of the disease-free host growth is crucial for defining optimal disease control strategies. By analytical investigations of the model with negligible demography, we demonstrated that the optimal strategy for the linear control can be either to cull at the maximum rate at the very beginning of the epidemic (reactive culling) when the culling cost is low, or never to cull, when culling cost is high. On the other hand, in the cases of quadratic control or limited resources, we demonstrated that the optimal strategy is always reactive. Numerical analyses for hosts with logistic growth showed that, in the case of linear control, the optimal strategy is always reactive when culling cost is low. In contrast, if the culling cost is high, the optimal strategy is to delay control, i.e. not to cull at the onset of the epidemic. Finally, we showed that for diseases with the same basic reproduction number delayed control can be optimal for acute infections, i.e. characterized by high disease-induced mortality and fast dynamics, while reactive control can be optimal for chronic ones.
A study of optimal abstract jamming strategies vs. noncoherent MFSK
Mceliece, R. J.; Rodemich, E. R.
1983-01-01
The present investigation is concerned with the performance of uncoded MFSK modulation in the presence of arbitrary additive jamming, taking into account the objective to devise robust antijamming strategies. An abstract model is considered, giving attention to the signal strength as a nonnegative real number X, the employment of X as a random variable, its distribution function G(x), the transmitter's strategy G, the jamming noise as an M-dimensional random vector Z, and the error probability. A summary of previous work on the considered problem is provided, and the results of the current study are presented.
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
Using Evolution Strategy with Meta-models for Well Placement Optimization
Bouzarkouna, Zyed; Auger, Anne
2010-01-01
Optimum implementation of non-conventional wells allows us to increase considerably hydrocarbon recovery. By considering the high drilling cost and the potential improvement in well productivity, well placement decision is an important issue in field development. Considering complex reservoir geology and high reservoir heterogeneities, stochastic optimization methods are the most suitable approaches for optimum well placement. This paper proposes an optimization methodology to determine optimal well location and trajectory based upon the Covariance Matrix Adaptation - Evolution Strategy (CMA-ES) which is a variant of Evolution Strategies recognized as one of the most powerful derivative-free optimizers for continuous optimization. To improve the optimization procedure, two new techniques are investigated: (1). Adaptive penalization with rejection is developed to handle well placement constraints. (2). A meta-model, based on locally weighted regression, is incorporated into CMA-ES using an approximate ranking ...
Optimized Power Dispatch Strategy for Offshore Wind Farms
DEFF Research Database (Denmark)
Hou, Peng; Hu, Weihao; Zhang, Baohua
2016-01-01
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...
Closing the loop : optimal strategies for hybrid manufacturing /remanufacturing systems
Caner Bulmus, Serra
2013-01-01
Serra Caner Bulmus beschrijft in haar proefschrift optimale strategieën voor inzameling van gebruikte producten en herfabricage van die producten door bedrijven. Bij herfabricage worden niet alleen de materialen hergebruikt, maar wordt ook de toegevoegde productiewaarde behouden. Daarmee is herfabri
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.
Assessment of trading partners for China's rare earth exports using a decision analytic approach.
He, Chunyan; Lei, Yalin; Ge, Jianping
2014-01-01
Chinese rare earth export policies currently result in accelerating its depletion. Thus adopting an optimal export trade selection strategy is crucial to determining and ultimately identifying the ideal trading partners. This paper introduces a multi-attribute decision-making methodology which is then used to select the optimal trading partner. In the method, an evaluation criteria system is established to assess the seven top trading partners based on three dimensions: political relationships, economic benefits and industrial security. Specifically, a simple additive weighing model derived from an additive utility function is utilized to calculate, rank and select alternatives. Results show that Japan would be the optimal trading partner for Chinese rare earths. The criteria evaluation method of trading partners for China's rare earth exports provides the Chinese government with a tool to enhance rare earth industrial policies.
OPTIMAL FEED STRATEGY FOR FED-BATCH GLYCEROL FERMENTATION DETERMINED BY MAXIMUM PRINCIPLE
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
1 IntroductionGlycerol fed-batch fermentation is attractive tocommercial application since it can control theglucose concentration by changing the feed rate andget a high glycerol yield, therefore it is essential todevelop an optimal glucose feed strategy. For mostof fed-batch fermentation, optimization of feed ratewas based on Pontryagin's maximum principle [if.Since the term of feed rate appears linearly in theHamiltonian, the optimal feed rate profile usuallyconsists of ba,lg-bang intervals and singular ...
Alternative adhesive strategies to optimize bonding to radicular dentin.
Bouillaguet, Serge; Bertossa, Bruno; Krejci, Ivo; Wataha, John C; Tay, Franklin R; Pashley, David H
2007-10-01
This study tested the hypothesis that bond strengths of filling materials to radicular dentin might be optimized by using an indirect dentin bonding procedure with an acrylic core material. Roots of human teeth were endodontically prepared and obturated with EndoREZ, Epiphany, or the bonding of an acrylic point with SE Bond by using a direct or an indirect bonding technique. Bond strengths of endodontic sealers to radicular dentin were measured with a thin slice push-out test. Push-out strengths of EndoREZ and Epiphany to radicular dentin were less than 5 megapascals (MPa). The direct bonding technique with acrylic points and the self-etching adhesive had push-out strengths of 10 MPa, increasing to 18 MPa with the indirect technique. The use of the indirect bonding protocol with an acrylic point to compensate for polymerization stresses appears to be a viable means for optimizing bond strengths of endodontic filling materials to radicular dentin.
Numerical Strategies for Stroke Optimization of Axisymmetric Microswimmers
Alouges, François; Heltai, Luca
2009-01-01
We propose a computational method to solve optimal swimming problems, based on the boundary integral formulation of the hydrodynamic interaction between swimmer and surrounding fluid and direct constrained minimization of the energy consumed by the swimmer. We apply our method to axisymmetric model examples. We consider a classical model swimmer (the three-sphere swimmer of Golestanian et al.) as well as a novel axisymmetric swimmer inspired by the observation of biological micro-organisms.
Exploring optimal fertigation strategies for orange production, using soil-crop modelling
Qin, Wei; Heinen, Marius; Assinck, Falentijn B.T.; Oenema, Oene
2016-01-01
Water and nitrogen (N) are two key limiting factors in orange (Citrus sinensis) production. The amount and the timing of water and N application are critical, but optimal strategies have not yet been well established. This study presents an analysis of 47 fertigation strategies examined by a coup
Optimal marker-strategy clinical trial design to detect predictive markers for targeted therapy.
Zang, Yong; Liu, Suyu; Yuan, Ying
2016-07-01
In developing targeted therapy, the marker-strategy design (MSD) provides an important approach to evaluate the predictive marker effect. This design first randomizes patients into non-marker-based or marker-based strategies. Patients allocated to the non-marker-based strategy are then further randomized to receive either the standard or targeted treatments, while patients allocated to the marker-based strategy receive treatments based on their marker statuses. Little research has been done on the statistical properties of the MSD, which has led to some widespread misconceptions and placed clinical researchers at high risk of using inefficient designs. In this article, we show that the commonly used between-strategy comparison has low power to detect the predictive effect and is valid only under a restrictive condition that the randomization ratio within the non-marker-based strategy matches the marker prevalence. We propose a Wald test that is generally valid and also uniformly more powerful than the between-strategy comparison. Based on that, we derive an optimal MSD that maximizes the power to detect the predictive marker effect by choosing the optimal randomization ratios between the two strategies and treatments. Our numerical study shows that using the proposed optimal designs can substantially improve the power of the MSD to detect the predictive marker effect. We use a lung cancer trial to illustrate the proposed optimal designs.
Integrated emission management strategy for cost-optimal engine-aftertreatment operation
Cloudt, R.P.M.; Willems, F.P.T.
2011-01-01
A new cost-based control strategy is presented that optimizes engine-aftertreatment performance under all operating conditions. This Integrated Emission Management strategy minimizes fuel consumption within the set emission limits by on-line adjustment of air management based on the actual state of
Bellingeri, Michele; Agliari, Elena; Cassi, Davide
2015-10-01
The best strategy to immunize a complex network is usually evaluated in terms of the percolation threshold, i.e. the number of vaccine doses which make the largest connected cluster (LCC) vanish. The strategy inducing the minimum percolation threshold represents the optimal way to immunize the network. Here we show that the efficacy of the immunization strategies can change during the immunization process. This means that, if the number of doses is limited, the best strategy is not necessarily the one leading to the smallest percolation threshold. This outcome should warn about the adoption of global measures in order to evaluate the best immunization strategy.
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.
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.
Multiresolution strategies for the numerical solution of optimal control problems
Jain, Sachin
There exist many numerical techniques for solving optimal control problems but less work has been done in the field of making these algorithms run faster and more robustly. The main motivation of this work is to solve optimal control problems accurately in a fast and efficient way. Optimal control problems are often characterized by discontinuities or switchings in the control variables. One way of accurately capturing the irregularities in the solution is to use a high resolution (dense) uniform grid. This requires a large amount of computational resources both in terms of CPU time and memory. Hence, in order to accurately capture any irregularities in the solution using a few computational resources, one can refine the mesh locally in the region close to an irregularity instead of refining the mesh uniformly over the whole domain. Therefore, a novel multiresolution scheme for data compression has been designed which is shown to outperform similar data compression schemes. Specifically, we have shown that the proposed approach results in fewer grid points in the grid compared to a common multiresolution data compression scheme. The validity of the proposed mesh refinement algorithm has been verified by solving several challenging initial-boundary value problems for evolution equations in 1D. The examples have demonstrated the stability and robustness of the proposed algorithm. The algorithm adapted dynamically to any existing or emerging irregularities in the solution by automatically allocating more grid points to the region where the solution exhibited sharp features and fewer points to the region where the solution was smooth. Thereby, the computational time and memory usage has been reduced significantly, while maintaining an accuracy equivalent to the one obtained using a fine uniform mesh. Next, a direct multiresolution-based approach for solving trajectory optimization problems is developed. The original optimal control problem is transcribed into a
Optimal vaccination strategies against vector-borne diseases
DEFF Research Database (Denmark)
Græsbøll, Kaare; Enøe, Claes; Bødker, Rene
2014-01-01
Using a process oriented semi-agent based model, we simulated the spread of Bluetongue virus by Culicoides, biting midges, between cattle in Denmark. We evaluated the minimum vaccination cover and minimum cost for eight different preventive vaccination strategies in Denmark. The simulation model...... replicates both a passive and active flight of midges between cattle distributed on pastures and cattle farms in Denmark. A seasonal abundance of midges and temperature dependence of biological processes were included in the model. The eight vaccination strategies were investigated under four different...... grazing conditions. Furthermore, scenarios were tested with three different index locations stratified for cattle density. The cheapest way to vaccinate cattle with a medium risk profile (less than 1000 total affected cattle) was to vaccinate cattle on pasture. Regional vaccination displayed better...
Optimization of wind farm power production using innovative control strategies
DEFF Research Database (Denmark)
Duc, Thomas
Wind energy has experienced a very significant growth and cost reduction over the past decade, and is now able to compete with conventional power generation sources. New concepts are currently investigated to decrease costs of production of electricity even further. Wind farm coordinated control...... is one of them; it is aimed at increasing the efficiency of a wind farm and decreasing the fatigue loads faced by wind turbines by reducing aerodynamic interactions between them. These objectives are achieved considering two different strategies: curtailing an upwind turbine to reduce the wind speed...... conditions. It is therefore not known to what extent these gains can be reproduced in a real wind farm where wind conditions are very fluctuating. The French national project SMARTEOLE constitutes one of the first attempts of implementing these strategies on a full scale wind farm. A ten month measurement...
Optimal Demand Execution Strategy for the Defense Logistics Agency
2014-12-01
a: ~ 8000 ~ 6000 :I z 4000 2000 0 5 Current PR Generation Demand Avg of March thru June 2014 - current - 5-day moving avg 10 15 20 25...March through June PR Generation The peak demand for daily PR execution per buyer is approximately 23 per day. At nearly 16,000 PRs per day, each of...Current Order Execution Strategy ..................................27 3. Generate Hypothetical Workload Models
Optimization Strategy to Capitalize on the Romanian Tourism Potential
PhD Lecturer Dindire Laura; PhD Reader Dugan Silvia
2010-01-01
An important direction of the improvement of promotional activities achieved both by the decisional governmental and non-governmental organisms within the tourist services sector and by the tourism firms, both on an intern and international level, is the promotional strategy. Consisting in the mastership of obtaining the best results, through organizing, coordination, prediction, communication and control activities, the promotional management means knowing and understanding the intern and in...
A digital processing strategy to optimize hearing aid outputs directly.
Blamey, Peter J; Martin, Lois F A; Fiket, Hayley J
2004-01-01
A new amplification strategy (ADRO), based on 64 independently operating channels, was compared with a nine-channel wide dynamic range compression strategy (WDRC). Open-platform in-the-ear hearing instruments were configured either with ADRO or the manufacturer's WDRC strategy. Twenty-two subjects with mild to moderate hearing loss took home the ADRO or WDRC hearing aids. After three weeks' acclimatization, the aids were evaluated using monosyllables in quiet at 50 to 65 dB SPL and sentences in eight-talker babble. The acclimatization and evaluation were repeated in the second phase of the balanced reverse-block blind experimental design. The ADRO program showed a statistically significant mean advantage of 7.85% word score (95% confidence interval 3.19% to 12.51%; p = 0.002) and 6.41% phoneme score for the monosyllables in quiet (95% confidence interval 2.03% to 10.79%; p = 0.006). A statistically significant advantage of 7.25% was also found for the ADRO program in background noise (95% confidence interval 1.95% to 12.55%; p = 0.010). The results are consistent with earlier data for listeners with moderate to severe hearing loss.
DEFF Research Database (Denmark)
Mohanty, Sankhya; Hattel, Jesper Henri
2015-01-01
to generate optimized cellular scanning strategies and processing parameters, with an objective of reducing thermal asymmetries and mechanical deformations. The optimized scanning strategies are used for selective laser melting of the standard samples, and experimental and numerical results are compared....... gradients that occur during the process. While process monitoring and control of selective laser melting is an active area of research, establishing the reliability and robustness of the process still remains a challenge.In this paper, a methodology for generating reliable, optimized scanning paths...
比较优势发展战略与贸易政策分析%Comparative Advantage Development Strategy and Trade Policy Analysis
Institute of Scientific and Technical Information of China (English)
李剑华
2013-01-01
比较优势理论在国际贸易和经济发展方面有着广泛的影响，林毅夫的比较优势战略对中国改革开放后的经济发展做了很好的解读。本文在分析比较优势战略的基础上，提出一国在贸易政策方面的补充。%Comparative advantage theory has wide influence on international trade and economic development. Lin Yifu's comparative advantage strategy made a good interpretation of China's economic development after reform and opening up. Based on the analysis of comparative advantage strategy, this paper proposes some supplement in terms of a country's trade policy.
Návrh trading strategie pro řízení volného finančního kapitálu jednotlivce
Kinc, Petr
2016-01-01
Tato diplomová práce se zabývá návrhem obchodní strategie pro řízení volného finančního kapitálu jednotlivce. V práci je navržena a otestována obchodní strategie, kterou lze využít při obchodování na forexu. Obchodní strategie využívá pravidla technické analýzy, market profile a order flow. Tato strategie byla testována na historických datech a posléze byla aplikována na obchody na reálném obchodním účtu s cílem maximalizace zisku. This diploma thesis deal with creation of trading strategy...
Dispositional optimism and coping strategies in patients with a kidney transplant.
Costa-Requena, Gemma; Cantarell-Aixendri, M Carmen; Parramon-Puig, Gemma; Serón-Micas, Daniel
2014-01-01
Dispositional optimism is a personal resource that determines the coping style and adaptive response to chronic diseases. The aim of this study was to assess the correlations between dispositional optimism and coping strategies in patients with recent kidney transplantation and evaluate the differences in the use of coping strategies in accordance with the level of dispositional optimism. Patients who were hospitalised in the nephrology department were selected consecutively after kidney transplantation was performed. The evaluation instruments were the Life Orientation Test-Revised, and the Coping Strategies Inventory. The data were analysed with central tendency measures, correlation analyses and means were compared using Student’s t-test. 66 patients with a kidney transplant participated in the study. The coping styles that characterised patients with a recent kidney transplantation were Social withdrawal and Problem avoidance. Correlations between dispositional optimism and coping strategies were significant in a positive direction in Problem-solving (p<.05) and Cognitive restructuring (p<.01), and inversely with Self-criticism (p<.05). Differences in dispositional optimism created significant differences in the Self-Criticism dimension (t=2.58; p<.01). Dispositional optimism scores provide differences in coping responses after kidney transplantation. Moreover, coping strategies may influence the patient’s perception of emotional wellbeing after kidney transplantation.
Optimal dispatch strategy for the agile virtual power plant
DEFF Research Database (Denmark)
Petersen, Mette Højgaard; Bendtsen, Jan Dimon; Stoustrup, Jakob
2012-01-01
of perfect prediction is unrealistic. This paper therefore introduces the Agile Virtual Power Plant. The Agile Virtual Power Plant assumes that the base load production planning based on best available knowledge is already given, so imbalances cannot be predicted. Consequently the Agile Virtual Power Plant...... attempts to preserve maneuverability (stay agile) rather than optimize performance according to predictions. In this paper the imbalance compensation problem for an Agile Virtual Power Plant is formulated. It is proved formally, that when local units are power and energy constrained integrators a dispatch...
OPTIMAL POWER ALLOCATION WITH AF AND SDF STRATEGIES IN DUAL-HOP COOPERATIVE MIMO NETWORKS
Institute of Scientific and Technical Information of China (English)
Xu Xiaorong; Zheng Baoyu; Zhang Jianwu
2010-01-01
Dual-hop cooperative Multiple-Input Multiple-Output (MIMO) network with multi-relay cooperative communication is introduced. Power allocation problem with Amplify-and-Forward (AF) and Selective Decode-and-Forward (SDF) strategies in multi-node scenario are formulated and solved respectively. Optimal power allocation schemes that maximize system capacity with AF strategy are presented. In addition,optimal power allocation methods that minimize asymptotic Symbol Error Rate (SER) with SDF cooperative protocol in multi-node scenario are also proposed. Furthermore,performance comparisons are provided in terms of system capacity and approximate SER. Numerical and simulation results confirm our theoretical analysis. It is revealed that,maximum system capacity could be obtained when powers are allocated optimally with AF protocol,while minimization of system's SER could also be achieved with optimum power allocation in SDF strategy. In multi-node scenario,those optimal power allocation algorithms are superior to conventional equal power allocation schemes.
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.
Lobato, Fran Sérgio; Machado, Vinicius Silvério; Steffen, Valder
2016-07-01
The mathematical modeling of physical and biologic systems represents an interesting alternative to study the behavior of these phenomena. In this context, the development of mathematical models to simulate the dynamic behavior of tumors is configured as an important theme in the current days. Among the advantages resulting from using these models is their application to optimization and inverse problem approaches. Traditionally, the formulated Optimal Control Problem (OCP) has the objective of minimizing the size of tumor cells by the end of the treatment. In this case an important aspect is not considered, namely, the optimal concentrations of drugs may affect the patients' health significantly. In this sense, the present work has the objective of obtaining an optimal protocol for drug administration to patients with cancer, through the minimization of both the cancerous cells concentration and the prescribed drug concentration. The resolution of this multi-objective problem is obtained through the Multi-objective Optimization Differential Evolution (MODE) algorithm. The Pareto's Curve obtained supplies a set of optimal protocols from which an optimal strategy for drug administration can be chosen, according to a given criterion.
Optimal inspection and Repair Strategies for Structural Systems
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard; Faber, Michael Havbro
1992-01-01
A model for reliability-based repair and maintenance strategies of structural systems is described. The total expected costs in the lifetime of the structure are minimized with the number of inspections, the number and positions of the inspected points, the inspection efforts, the repair criteria...... to be inspected and to select the location of the points to be inspected. It is shown how information obtained through inspections and through the periods of normal operating of the structure can be used to update the inspection and maintenance planning. Finally, a small example is given illustrating...
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.
Institute of Scientific and Technical Information of China (English)
2008-01-01
This paper introduces the virtual and real game concepts to investigate multi-criterion optimization for optimum shape design in aerodynamics. The constrained adjoint meth- odology is used as the basic optimizer. Furthermore, the above is combined with the vir- tual and real game strategies to treat single-point/multi-point airfoil optimization. In a symmetric Nash Game, each optimizer attempts to optimize one’s own target with ex- change of symmetric information with others. A Nash equilibrium is just the compromised solution among the multiple criteria. Several kinds of airfoil splitting and design cases are shown for the utility of virtual and real game strategies in aerodynamic design. Successful design results confirm the validity and efficiency of the present design method.
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.
Institute of Scientific and Technical Information of China (English)
TANG ZhiLi; BAI Wen; DONG Jun
2008-01-01
This paper introduces the virtual and real game concepts to investigate multi-criterion optimization for optimum shape design in aerodynamics. The constrained acljoint meth-odology is used as the basic optimizer. Furthermore, the above is combined with the vir-tual and real game strategies to treat single-point/multi-point airfoil optimization. In a symmetric Nash Game, each optimizer attempts to optimize one's own target with ex-change of symmetric information with others. A Nash equilibrium is just the compromised solution among the multiple criteria. Several kinds of airfoil splitting and design cases are shown for the utility of virtual and real game strategies in aerodynamic design. Successful design results confirm the validity and efficiency of the present design method.
Optimization of remediation strategies using vadose zone monitoring systems
Dahan, Ofer
2016-04-01
In-situ bio-remediation of the vadose zone depends mainly on the ability to change the subsurface hydrological, physical and chemical conditions in order to enable development of specific, indigenous, pollutants degrading bacteria. As such the remediation efficiency is much dependent on the ability to implement optimal hydraulic and chemical conditions in deep sections of the vadose zone. These conditions are usually determined in laboratory experiments where parameters such as the chemical composition of the soil water solution, redox potential and water content of the sediment are fully controlled. Usually, implementation of desired optimal degradation conditions in deep vadose zone at full scale field setups is achieved through infiltration of water enriched with chemical additives on the land surface. It is assumed that deep percolation into the vadose zone would create chemical conditions that promote biodegradation of specific compounds. However, application of water with specific chemical conditions near land surface dose not necessarily results in promoting of desired chemical and hydraulic conditions in deep sections of the vadose zone. A vadose-zone monitoring system (VMS) that was recently developed allows continuous monitoring of the hydrological and chemical properties of deep sections of the unsaturated zone. The VMS includes flexible time-domain reflectometry (FTDR) probes which allow continuous monitoring of the temporal variation of the vadose zone water content, and vadose-zone sampling ports (VSPs) which are designed to allow frequent sampling of the sediment pore-water and gas at multiple depths. Implementation of the vadose zone monitoring system in sites that undergoes active remediation provides real time information on the actual chemical and hydrological conditions in the vadose zone as the remediation process progresses. Up-to-date the system has been successfully implemented in several studies on water flow and contaminant transport in
Signal/noise optimization strategies for stochastically estimated correlation functions
Detmold, William
2014-01-01
Numerical studies of quantum field theories usually rely upon an accurate determination of stochastically estimated correlation functions in order to extract information about the spectrum of the theory and matrix elements of operators. The reliable determination of such correlators is often hampered by an exponential degradation of signal/noise at late time separations. We demonstrate that it is sometimes possible to achieve significant enhancements of signal/noise by appropriately optimizing correlators with respect to the source and sink interpolating operators, and highlight the large range of possibilities that are available for this task. The ideas are discussed for both a toy model, and single hadron correlators in the context of quantum chromodynamics.
Optimal control strategy of malaria vector using genetically modified mosquitoes.
Rafikov, M; Bevilacqua, L; Wyse, A P P
2009-06-07
The development of transgenic mosquitoes that are resistant to diseases may provide a new and effective weapon of diseases control. Such an approach relies on transgenic mosquitoes being able to survive and compete with wild-type populations. These transgenic mosquitoes carry a specific code that inhibits the plasmodium evolution in its organism. It is said that this characteristic is hereditary and consequently the disease fades away after some time. Once transgenic mosquitoes are released, interactions between the two populations and inter-specific mating between the two types of mosquitoes take place. We present a mathematical model that considers the generation overlapping and variable environment factors. Based on this continuous model, the malaria vector control is formulated and solved as an optimal control problem, indicating how genetically modified mosquitoes should be introduced in the environment. Numerical simulations show the effectiveness of the proposed control.
A Parameter Communication Optimization Strategy for Distributed Machine Learning in Sensors
Directory of Open Access Journals (Sweden)
Jilin Zhang
2017-09-01
Full Text Available 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.
A Parameter Communication Optimization Strategy for Distributed Machine Learning in Sensors.
Zhang, Jilin; Tu, Hangdi; Ren, Yongjian; Wan, Jian; Zhou, Li; Li, Mingwei; Wang, Jue; Yu, Lifeng; Zhao, Chang; Zhang, Lei
2017-09-21
In order to utilize the distributed characteristic of sensors, distributed machine learning has become the mainstream approach, but the different computing capability of sensors and network delays greatly influence the accuracy and the convergence rate of the machine learning model. Our paper describes a reasonable parameter communication optimization strategy to balance the training overhead and the communication overhead. We extend the fault tolerance of iterative-convergent machine learning algorithms and propose the Dynamic Finite Fault Tolerance (DFFT). Based on the DFFT, we implement a parameter communication optimization strategy for distributed machine learning, named Dynamic Synchronous Parallel Strategy (DSP), which uses the performance monitoring model to dynamically adjust the parameter synchronization strategy between worker nodes and the Parameter Server (PS). This strategy makes full use of the computing power of each sensor, ensures the accuracy of the machine learning model, and avoids the situation that the model training is disturbed by any tasks unrelated to the sensors.
Approximate representation of optimal strategies from influence diagrams
DEFF Research Database (Denmark)
Jensen, Finn V.
2008-01-01
of the advantages of influence diagrams (IDs) is that for small decision problems, the distinction between phases does not confront the decision maker with a problem; when the problem has been properly specified, the solution algorithms are so efficient that the ID can also be used as an on-line representation......, and where the policy functions for the decisions have so large do- mains that they cannot be represented directly in a strategy tree. The approach is to have separate ID representations for each decision variable. In each representation the actual information is fully exploited, however the representation...... of policies for future decisions are approximations. We call the approximation information abstraction. It consists in introducing a dummy structure connecting the past with the decision. We study how to specify, implement and learn information abstraction....
[Plastid genome engineering: novel optimization strategies and applications].
Zhou, Fei; Lu, Shizhan; Gao, Liang; Zhang, Juanjuan; Lin, Yongjun
2015-08-01
The plastid genome engineering system allows site-specific modifications via two homologous recombination events. It is much safer, more precise and efficient compared with the nuclear transformation system. This technology can be applied to the basic research to expand plastid genome function analysis, and it also provides an excellent platform for not only high-level production of recombinant proteins but also plant breeding. In this review, we summarize the state of the art and progresses in this field. We focus on novel breeding strategies in transformation system improvement and new tools to enhance plastid transgene expression levels. In addition, we highlight selected applications in resistance engineering and quality improvement via metabolic engineering. We believe that by overcoming current technological limitations in the plastid transformation system can another green revolution for crop breeding beckon.
Wake Mitigation Strategies for Optimizing Wind Farm Power Production
Dilip, Deepu; Porté-Agel, Fernando
2016-04-01
Although wind turbines are designed individually for optimum power production, they are often arranged into groups of closely spaced turbines in a wind farm rather than in isolation. Consequently, most turbines in a wind farm do not operate in unobstructed wind flows, but are affected by the wakes of turbines in front of them. Such wake interference significantly reduces the overall power generation from wind farms and hence, development of effective wake mitigation strategies is critical for improving wind farm efficiency. One approach towards this end is based on the notion that the operation of each turbine in a wind farm at its optimum efficiency might not lead to optimum power generation from the wind farm as a whole. This entails a down regulation of individual turbines from its optimum operating point, which can be achieved through different methods such as pitching the turbine blades, changing the turbine tip speed ratio or yawing of the turbine, to name a few. In this study, large-eddy simulations of a two-turbine arrangement with the second turbine fully in the wake of the first are performed. Different wake mitigation techniques are applied to the upstream turbine, and the effects of these on its wake characteristics are investigated. Results for the combined power from the two turbines for each of these methods are compared to a baseline scenario where no wake mitigation strategies are employed. Analysis of the results shows the potential for improved power production from such wake control methods. It should be noted, however, that the magnitude of the improvement is strongly affected by the level of turbulence in the incoming atmospheric flow.
An optimizing start-up strategy for a bio-methanator.
Sbarciog, Mihaela; Loccufier, Mia; Vande Wouwer, Alain
2012-05-01
This paper presents an optimizing start-up strategy for a bio-methanator. The goal of the control strategy is to maximize the outflow rate of methane in anaerobic digestion processes, which can be described by a two-population model. The methodology relies on a thorough analysis of the system dynamics and involves the solution of two optimization problems: steady-state optimization for determining the optimal operating point and transient optimization. The latter is a classical optimal control problem, which can be solved using the maximum principle of Pontryagin. The proposed control law is of the bang-bang type. The process is driven from an initial state to a small neighborhood of the optimal steady state by switching the manipulated variable (dilution rate) from the minimum to the maximum value at a certain time instant. Then the dilution rate is set to the optimal value and the system settles down in the optimal steady state. This control law ensures the convergence of the system to the optimal steady state and substantially increases its stability region. The region of attraction of the steady state corresponding to maximum production of methane is considerably enlarged. In some cases, which are related to the possibility of selecting the minimum dilution rate below a certain level, the stability region of the optimal steady state equals the interior of the state space. Aside its efficiency, which is evaluated not only in terms of biogas production but also from the perspective of treatment of the organic load, the strategy is also characterized by simplicity, being thus appropriate for implementation in real-life systems. Another important advantage is its generality: this technique may be applied to any anaerobic digestion process, for which the acidogenesis and methanogenesis are, respectively, characterized by Monod and Haldane kinetics.
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.
Wang, Bo; Tian, Kuo; Zhao, Haixin; Hao, Peng; Zhu, Tianyu; Zhang, Ke; Ma, Yunlong
2016-09-01
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.
Trade Friction of Sino-US Intellectual Property and Coping Strategies%中美贸易中知识产权摩擦及应对策略
Institute of Scientific and Technical Information of China (English)
贾显维
2012-01-01
In recent years, trade friction of Sino-US intellectual property is becoming the focus of Sino-US trade friction, which has become the biggest obstacle for China's enterprises exporting to the U.S. In this paper, the causes and characteristics of trade friction of Sino-US intellectual property were analyzed, and the coping strategies of trade friction of Sino-US intellectual property were put forward from two levels of government and business, combing with China's actual conditions.%近些来,中美知识产权贸易摩擦日渐成为中美贸易摩擦的焦点,已成为中国企业对美出口的最大障碍.本文对中美知识产权贸易摩擦的特点、原因进行了分析,结合我国的实际情况,从政府及企业两个层面提出了应对中美知识产权贸易摩擦的策略.
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.
Survey strategy optimization for the Atacama Cosmology Telescope
De Bernardis, F; Hasselfield, M; Alonso, D; Bond, J R; Calabrese, E; Choi, S K; Crowley, K T; Devlin, M; Dunkley, J; Gallardo, P A; Henderson, S W; Hilton, M; Hlozek, R; Ho, S P; Huffenberger, K; Koopman, B J; Kosowsky, A; Louis, T; Madhavacheril, M S; McMahon, J; Naess, S; Nati, F; Newburgh, L; Niemack, M D; Page, L A; Salatino, M; Schillaci, A; Schmitt, B L; Sehgal, N; Sievers, J L; Simon, S M; Spergel, D N; Staggs, S T; van Engelen, A; Vavagiakis, E M; Wollack, E J
2016-01-01
In recent years there have been significant improvements in the sensitivity and the angular resolution of the instruments dedicated to the observation of the Cosmic Microwave Background (CMB). ACTPol is the first polarization receiver for the Atacama Cosmology Telescope (ACT) and is observing the CMB sky with arcmin resolution over about 2000 sq. deg. Its upgrade, Advanced ACTPol (AdvACT), will observe the CMB in five frequency bands and over a larger area of the sky. We describe the optimization and implementation of the ACTPol and AdvACT surveys. The selection of the observed fields is driven mainly by the science goals, that is, small angular scale CMB measurements, B-mode measurements and cross-correlation studies. For the ACTPol survey we have observed patches of the southern galactic sky with low galactic foreground emissions which were also chosen to maximize the overlap with several galaxy surveys to allow unique cross-correlation studies. A wider field in the northern galactic cap ensured significant...
Optimal Segmentation Strategy for Compact Representation of Hyperspectral Image Cubes
Energy Technology Data Exchange (ETDEWEB)
Paglieroni, D; Roberts, R
2000-02-08
By producing compact representations of hyperspectral image cubes (hypercubes), image storage requirements and the amount of time it takes to extract essential elements of information can both be dramatically reduced. However, these compact representations must preserve the important spectral features within hypercube pixels and the spatial structure associated with background and objects or phenomena of interest. This paper describes a novel approach for automatically and efficiently generating a particular type of compact hypercube representation, referred to as a supercube. The hypercube is segmented into regions that contain pixels with similar spectral shapes that are spatially connected, and the pixel connectivity constraint can be relaxed. Thresholds of similarity in spectral shape between pairs of pixels are derived directly from the hypercube data. One superpixel is generated for each region as some linear combination of pixels belonging to that region. The superpixels are optimal in the sense that the linear combination coefficients are computed so as to minimize the level of noise. Each hypercube pixel is represented in the supercube by applying a gain and bias to the superpixel assigned to the region containing that pixel. Examples are provided.
Directory of Open Access Journals (Sweden)
Guohua Wu
2013-01-01
Full Text Available Discovering and utilizing problem domain knowledge is a promising direction towards improving the efficiency of evolutionary algorithms (EAs when solving optimization problems. We propose a knowledge-based variable reduction strategy (VRS that can be integrated into EAs to solve unconstrained and first-order derivative optimization functions more efficiently. VRS originates from the knowledge that, in an unconstrained and first-order derivative optimization function, the optimal solution locates in a local extreme point at which the partial derivative over each variable equals zero. Through this collective of partial derivative equations, some quantitative relations among different variables can be obtained. These variable relations have to be satisfied in the optimal solution. With the use of such relations, VRS could reduce the number of variables and shrink the solution space when using EAs to deal with the optimization function, thus improving the optimizing speed and quality. When we apply VRS to optimization problems, we just need to modify the calculation approach of the objective function. Therefore, practically, it can be integrated with any EA. In this study, VRS is combined with particle swarm optimization variants and tested on several benchmark optimization functions and a real-world optimization problem. Computational results and comparative study demonstrate the effectiveness of VRS.
Strategies to Optimize Adult Stem Cell Therapy for Tissue Regeneration
Directory of Open Access Journals (Sweden)
Shan Liu
2016-06-01
Full Text Available Stem cell therapy aims to replace damaged or aged cells with healthy functioning cells in congenital defects, tissue injuries, autoimmune disorders, and neurogenic degenerative diseases. Among various types of stem cells, adult stem cells (i.e., tissue-specific stem cells commit to becoming the functional cells from their tissue of origin. These cells are the most commonly used in cell-based therapy since they do not confer risk of teratomas, do not require fetal stem cell maneuvers and thus are free of ethical concerns, and they confer low immunogenicity (even if allogenous. The goal of this review is to summarize the current state of the art and advances in using stem cell therapy for tissue repair in solid organs. Here we address key factors in cell preparation, such as the source of adult stem cells, optimal cell types for implantation (universal mesenchymal stem cells vs. tissue-specific stem cells, or induced vs. non-induced stem cells, early or late passages of stem cells, stem cells with endogenous or exogenous growth factors, preconditioning of stem cells (hypoxia, growth factors, or conditioned medium, using various controlled release systems to deliver growth factors with hydrogels or microspheres to provide apposite interactions of stem cells and their niche. We also review several approaches of cell delivery that affect the outcomes of cell therapy, including the appropriate routes of cell administration (systemic, intravenous, or intraperitoneal vs. local administration, timing for cell therapy (immediate vs. a few days after injury, single injection of a large number of cells vs. multiple smaller injections, a single site for injection vs. multiple sites and use of rodents vs. larger animal models. Future directions of stem cell-based therapies are also discussed to guide potential clinical applications.
Strategies to Optimize Adult Stem Cell Therapy for Tissue Regeneration.
Liu, Shan; Zhou, Jingli; Zhang, Xuan; Liu, Yang; Chen, Jin; Hu, Bo; Song, Jinlin; Zhang, Yuanyuan
2016-06-21
Stem cell therapy aims to replace damaged or aged cells with healthy functioning cells in congenital defects, tissue injuries, autoimmune disorders, and neurogenic degenerative diseases. Among various types of stem cells, adult stem cells (i.e., tissue-specific stem cells) commit to becoming the functional cells from their tissue of origin. These cells are the most commonly used in cell-based therapy since they do not confer risk of teratomas, do not require fetal stem cell maneuvers and thus are free of ethical concerns, and they confer low immunogenicity (even if allogenous). The goal of this review is to summarize the current state of the art and advances in using stem cell therapy for tissue repair in solid organs. Here we address key factors in cell preparation, such as the source of adult stem cells, optimal cell types for implantation (universal mesenchymal stem cells vs. tissue-specific stem cells, or induced vs. non-induced stem cells), early or late passages of stem cells, stem cells with endogenous or exogenous growth factors, preconditioning of stem cells (hypoxia, growth factors, or conditioned medium), using various controlled release systems to deliver growth factors with hydrogels or microspheres to provide apposite interactions of stem cells and their niche. We also review several approaches of cell delivery that affect the outcomes of cell therapy, including the appropriate routes of cell administration (systemic, intravenous, or intraperitoneal vs. local administration), timing for cell therapy (immediate vs. a few days after injury), single injection of a large number of cells vs. multiple smaller injections, a single site for injection vs. multiple sites and use of rodents vs. larger animal models. Future directions of stem cell-based therapies are also discussed to guide potential clinical applications.
Insurance with frequent trading
José Penalva
1997-01-01
This paper looks at the dynamic management of risk in an economy with discrete time consumption and endowments and continuous trading. I study how agents in such an economy deal with all the risk in the economy and attain their Pareto optimal allocations by trading in a few natural securities: private insurance contracts and a common set of derivatives on the aggregate endowment. The parsimonious nature of the implied securities needed for Pareto optimality suggests that in such contexts comp...
A minimax optimal control strategy for uncertain quasi-Hamiltonian systems
Institute of Scientific and Technical Information of China (English)
Yong WANC; Zu-guang YING; Wei-qiu ZHU
2008-01-01
A minimax optimal control strategy for quasi-Hamiltonian systems with bounded parametric and/or external disturbances is proposed based on the stochastic averaging method and stochastic differential game. To conduct the system energy control, the partially averaged It6 stochastic differential equations for the energy processes are first derived by using the stochastic averaging method for quasi-Hamiltonian systems. Combining the above equations with an appropriate performance index, the proposed strategy is searching for an optimal worst-case controller by solving a stochastic differential game problem. The worst-case disturbances and the optimal controls are obtained by solving a Hamilton-Jacobi-Isaacs (HJI) equation. Numerical results for a controlled and stochastically excited Duffing oscillator with uncertain disturbances exhibit the efficacy of the proposed control strategy.
Optimal Strategy of Efficiency Power Plant with Battery Electric Vehicle in Distribution Network
Ma, Tao; Su, Su; Li, Shunxin; Wang, Wei; Yang, Tiantian; Li, Mengjuan; Ota, Yutaka
2017-05-01
With the popularity of electric vehicles (EVs), such as plug-in electric vehicles (PHEVs) and battery electric vehicles (BEVs), an optimal strategy for the coordination of BEVs charging is proposed in this paper. The proposed approach incorporates the random behaviours and regular behaviours of BEV drivers in urban environment. These behaviours lead to the stochastic nature of the charging demand. The optimal strategy is used to guide the coordinated charging at different time to maximize the efficiency of virtual power plant (VPP). An innovative peer-to-peer system is used with BEVs to achieve the goals. The actual behaviours of vehicles in a campus is used to validate the proposed approach, and the simulation results show that the optimal strategy can not only maximize the utilization ratio of efficiency power plant, but also do not need additional energies from distribution grid.
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 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.
Cai, Qiong; Adjiman, Claire S.; Brandon, Nigel P.
2014-12-01
The penetration of intermittent renewable energies requires the development of energy storage technologies. High temperature electrolysis using solid oxide electrolyser cells (SOECs) as a potential energy storage technology, provides the prospect of a cost-effective and energy efficient route to clean hydrogen production. The development of optimal control strategies when SOEC systems are coupled with intermittent renewable energies is discussed. Hydrogen production is examined in relation to energy consumption. Control strategies considered include maximizing hydrogen production, minimizing SOEC energy consumption and minimizing compressor energy consumption. Optimal control trajectories of the operating variables over a given period of time show feasible control for the chosen situations. Temperature control of the SOEC stack is ensured via constraints on the overall temperature difference across the cell and the local temperature gradient within the SOEC stack, to link materials properties with system performance; these constraints are successfully managed. The relative merits of the optimal control strategies are analyzed.
2009-01-01
The work concerns Emission Trading Scheme from perspektive of taxes and accounting. I should show problems with emission trading. The work concerns practical example of trading with emission allowance.
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.
Optimal Attack Strategy in Random Scale-Free Networks Based on Incomplete Information
Institute of Scientific and Technical Information of China (English)
LI Jun; WU Jun; LI Yong; DENG Hong-Zhong; TAN Yue-Jin
2011-01-01
@@ We introduce an attack model based on incomplete information, which means that we can obtain the information from partial nodes.We investigate the optimal attack strategy in random scale-free networks both analytically and numerically.We show that the attack strategy can affect the attack effect remarkably and the OAS can achieve better attack effect than other typical attack strategies.It is found that when the attack intensity is small, the attacker should attack more nodes in the "white area" in which we can obtain attack information; when the attack intensity is greater, the attacker should attack more nodes in the "black area" in which we can not obtain attack information.Moreover, we show that there is an inflection point in the curve of optimal attack proportion.For a given magnitude of attack information, the optimal attack proportion decreases with the attack intensity before the inflection point and then increases after the inflection point.%We introduce an attack model based on incomplete information, which means that we can obtain the information from partial nodes. We investigate the optimal attack strategy in random scale-free networks both analytically and numerically. We show that the attack strategy can affect the attack effect remarkably and the OAS can achieve better attack effect than other typical attack strategies. It is found that when the attack intensity is small, the attacker should attack more nodes in the "white area" in which we can obtain attack information; when the attack intensity is greater, the attacker should attack more nodes in the "black area" in which we can not obtain attack information. Moreover, we show that there is an inflection point in the curve of optimal attack proportion. For a given magnitude of attack information, the optimal attack proportion decreases with the attack intensity before the inflection point and then increases after the inflection point.
Gilijamse, J J; Hoekstra, S; De van Meerakker, S Y T; Meijer, G; Gilijamse, Joop J.; K\\"upper, Jochen; Hoekstra, Steven; Meerakker, Sebastiaan Y. T. van de; Meijer, Gerard
2006-01-01
We demonstrate feedback control optimization for the Stark deceleration and trapping of neutral polar molecules using evolutionary strategies. In a Stark-decelerator beamline pulsed electric fields are used to decelerate OH radicals and subsequently store them in an electrostatic trap. The efficiency of the deceleration and trapping process is determined by the exact timings of the applied electric field pulses. Automated optimization of these timings yields an increase of 40 % of the number of trapped OH radicals.
Novel Modeling Framework To Guide Design of Optimal Dosing Strategies for β-Lactamase Inhibitors
Bhagunde, Pratik; Chang, Kai-Tai; Hirsch, Elizabeth B.; Ledesma, Kimberly R.; Nikolaou, Michael; Tam, Vincent H.
2012-01-01
The scarcity of new antibiotics against drug-resistant bacteria has led to the development of inhibitors targeting specific resistance mechanisms, which aim to restore the effectiveness of existing agents. However, there are few guidelines for the optimal dosing of inhibitors. Extending the utility of mathematical modeling, which has been used as a decision support tool for antibiotic dosing regimen design, we developed a novel mathematical modeling framework to guide optimal dosing strategie...
Implementation of Evolution Strategies (ES) Algorithm to Optimization Lovebird Feed Composition
Agung Mustika Rizki; Wayan Firdaus Mahmudy; Gusti Eka Yuliastuti
2017-01-01
Lovebird current society, especially popular among bird lovers. Some people began to try to develop the cultivation of these birds. In the cultivation process to consider the composition of feed to produce a quality bird. Determining the feed is not easy because it must consider the cost and need for vitamin Lovebird. This problem can be solved by the algorithm Evolution Strategies (ES). Based on test results obtained optimal fitness value of 0.3125 using a population size of 100 and optimal ...
The Development of an Optimal Control Strategy for a Series Hydraulic Hybrid Vehicle
Directory of Open Access Journals (Sweden)
Chih-Wei Hung
2016-03-01
Full Text Available In this work, a Truck Class II series hydraulic hybrid model is established. Dynamic Programming (DP methodology is applied to derive the optimal power-splitting factor for the hybrid system for preselected driving schedules. Implementable rules are derived by extracting the optimal trajectory features from a DP scheme. The system behaviors illustrate that the improved control strategy gives a highly effective operation region for the engine and high power density characteristics for the hydraulic components.
Optimal investment policy and dividend payment strategy in an insurance company
Pablo Azcue; Nora Muler
2010-01-01
We consider in this paper the optimal dividend problem for an insurance company whose uncontrolled reserve process evolves as a classical Cram\\'{e}r--Lundberg process. The firm has the option of investing part of the surplus in a Black--Scholes financial market. The objective is to find a strategy consisting of both investment and dividend payment policies which maximizes the cumulative expected discounted dividend pay-outs until the time of bankruptcy. We show that the optimal value function...