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50th IEEE Conference of Decision and Control (CDC)/European Control Conference (ECC)

作者： Faghih, Ali Roozbehani, Mardavij Dahleh, Munther A. MIT Informat & Decis Syst Lab Dept Elect Engn & Comp Sci Cambridge MA 02139 USA MIT Dept EECS Cambridge MA 02139 USA

ISBN: (纸本)9781612848013

This paper is concerned with optimal utilization of storage, characterization of the economic value of storage in the presence of ramp-rate constraints and stochastically-varying electricity prices, and characterization of the price elasticity of demand induced by optimal utilization of storage. The ramp constraints limit the charging and discharging rate of storage, and can be due to the physical limitations of the storage device or the power lines. Such constraints make analytical characterization of optimal policies particularly difficult. In this paper, the optimal utilization problem is addressed in a finite-horizon stochastic dynamic programming framework, and an analytical characterization of the value function along with recursive formulas for computation of the associated optimal policy are derived. It is shown that the value function associated with the dynamic programming problem is a piecewise linear convex function of the storage state, i.e., the amount of stored energy. Furthermore, while the economic value of storage capacity is a non-decreasing function of price volatility, it is shown that due to finite ramping rates, the value of storage saturates quickly as the capacity increases, regardless of price volatility. Finally, it is shown that optimal utilization of storage by consumers could induce a considerable amount of price elasticity, particularly near the average price.

关键词： Value of Storage Ramp Constraints Price Elasticity of Demand stochastic dynamic programming

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stochastic dynamic demand inventory models with explicit transportation costs and decisions

Stochastic dynamic demand inventory models with explicit tra...

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作者： Zhang, Liqing Texas A&M University

学位级别：Ph.D.

Recent supply chain literature and practice recognize that significant cost savings can be achieved by coordinating inventory and transportation decisions. Although the existing literature on analytical models for these decisions is very broad, there are still some challenging issues. In particular, the uncertainty of demand in a dynamic system and the structure of various practical transportation cost functions remain unexplored in detail. Taking these motivations into account, this dissertation focuses on the analytical investigation of the impact of transportation-related costs and practices on inventory decisions, as well as the integrated inventory and transportation decisions, under stochastic dynamic demand. Considering complicated, yet realistic, transportation-related costs and practices, we develop and solve three classes of models: (1) Pure inbound inventory model impacted by transportation cost; (2) Pure outbound transportation models concerning shipment consolidation strategy; (3) Integrated inbound inventory and outbound transportation models. In broad terms, we investigate the modeling framework of vendor-customer systems for integrated inventory and transportation decisions, and we identify the optimal inbound and outbound policies for stochastic dynamic supply chain systems. This dissertation contributes to the previous literature by exploring the impact of realistic transportation costs and practices on stochastic dynamic supply chain systems while identifying the structural properties of the corresponding optimal inventory and/or transportation policies. Placing an emphasis on the cases of stochastic demand and dynamic planning, this research has roots in applied probability, optimal control, and stochastic dynamic programming.

关键词： stochastic dynamic programming Shipment consolidation Inventory/production Thesis

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On discounted dynamic programming with unbounded returns

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ECONOMIC THEORY 2011年第3期46卷 455-474页

作者： Matkowski, Janusz Nowak, Andrzej S. PWSZ Inst Finance Nysa Poland Univ Zielona Gora Fac Math Comp Sci & Econometr PL-65246 Zielona Gora Poland Silesian Univ Inst Math PL-40007 Katowice Poland

In this paper, we apply the idea of k-local contraction of Rincn-Zapatero and Rodriguez-Palmero (Econometrica 71:1519-1555, 2003;Econ Theory 33:381-391, 2007) to study discounted stochastic dynamic programming models with unbounded returns. Our main results concern the existence of a unique solution to the Bellman equation and are applied to the theory of stochastic optimal growth. Also a discussion of some subtle issues concerning k-local and global contractions is included.

关键词： stochastic dynamic programming Bellman functional equation Contraction mapping stochastic optimal growth

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Optimizing Selection of Technologies in a Multiple Stage, Multiple Objective Wastewater Treatment System

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JOURNAL OF MULTI-CRITERIA DECISION ANALYSIS 2011年第1-2期18卷 115-142页

作者： Tarun, Prashant Chen, Victoria Corley, H. Jiang, F. Missouri Western State Univ Steven L Craig Sch Business St Joseph MO 64507 USA Univ Texas Arlington Ind & Mfg Syst Engn Arlington TX 76019 USA Georgia Dept Nat Resources Atlanta GA USA

In this paper, a multiple stage wastewater treatment system (WTS) is solved for the selection of technological options at each stage to minimize (economic cost, size, odour emissions) and to maximize (nutrient recovery, robustness, global desirability). Stages in the wastewater treatment system are the levels of treatment. There are 17 levels of treatment, where the first 11 levels are for the liquid treatment and the last 6 levels are for the solid treatment. This results in a 20-dimensional, continuous-state, 17-stage, 6-objective, stochastic optimization problem. The resulting multiple stage, multiple objective (MSMO) WTS is solved using the three-phase methodology in conjunction with the multiple objective version of highdimensional, continuous-state, stochastic dynamic programming (SDP). The three-phase methodology comprises the input phase, the matrix generation phase and the weighting phase. The primary goal of three-phase methodology is to obtain weight vectors at each stage of the WTS utilizing expert's opinions in the input phase, computing pairwise comparison matrices at each stage using the geometric mean-based methods in the matrix generation phase, and then calculating weight vectors at each stage using the eigenvector method in the weighting phase. The weight vectors are then used to scalarize the vector optimization problem, which is solved using the high-dimensional, continuous-state SDP augmented for handling multiple objectives at each stage. The results obtained are practical as evidenced by the selection of new technologies in levels 1 and 5 thereby validating expert's decision to include them in the evaluation process. In addition to encouraging reviews from WTS experts, the implementation results satisfy a set of external constraints in the form of interstage dependencies between technological options in the WTS. Furthermore, the solution technique presented here utilizes expert's opinions in the solution development process, and is quite gene

关键词： multiple objective decisions stochastic dynamic programming wastewater treatment model Pareto scalarization analytic hierarchy process

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Capacity Flexibility Premium under Different Demand Uncertainties

Capacity Flexibility Premium under Different Demand Uncertai...

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18th International Conference on Management Science and Engineering

作者： Xue Ming-gao Liu Lin-lin Wang Xiang-yang Huazhong Univ Sci & Technol Sch Management Wuhan 430074 Peoples R China

ISBN: (纸本)9781457718861

In this paper, we study the effect of different demand shocks on flexibility premium in capacity investment. We find that capacity flexibility premium is significantly higher under additive demand uncertainty than that under multiplicative demand shock. The result suggests that real options approach is more appropriate for investment decision in additive model, and when under multiplicative demand shock the simple net present value (NPV) rule is efficient enough for firm to make accurate decision. That may provide additional theoretical support to explain why many firms still prefer NPV approach in reality. Before using real options approach indiscriminately, first to analyze and identify the nature of demand should be necessary. We examine this problem by dynamic programming and extend the application of bi-variable tree approach for jump diffusion stochastic processes.

关键词： capacity investment flexibility premium nature of demand shock real option stochastic dynamic programming

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stochastic dynamic programming for long term hydrothermal scheduling considering different streamflow models

Stochastic dynamic programming for long term hydrothermal sc...

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9th International Conference on Probabilistic Methods Applied to Power Systems

作者： Siqueira, T. G. Zambelli, M. Cicogna, M. Andrade, M. Soares, S. Univ Estadual Campinas Campinas SP Brazil Univ Estadual Campinas Elect & Comp Engn Sch Hydrothermal Power Syst Grp Campinas SP Brazil Univ Estadual Campinas UNICAMP Fac Elect & Comp Engn Campinas SP Brazil Univ Estadual Campinas Elect & Comp Engn Sch Campinas SP Brazil

ISBN: (纸本)9789171785855

This paper is concerned with the performance of stochastic dynamic programming for long term hydrothermal scheduling. Different streamflow models progressively more complex have been considered in order to identify the benefits of increasing sophistication of streamflow modeling on the performance of stochastic dynamic programming. The first and simplest model considers the inflows given by their average values;the second model represents the inflows by independent probability distribution functions;and the third model adopts a Markov chain based on a lag-one periodical auto-regressive model. The effects of using different probability distribution functions have been also addressed. Numerical results for a hydrothermal test system composed by a single hydro plant have been obtained by simulation with Brazilian inflow records.

关键词： streamflow models long term hydrothermal scheduling Markov chain stochastic dynamic programming

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Modeling the operation of multireservoir systems using decomposition and stochastic dynamic programming

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NAVAL RESEARCH LOGISTICS 2006年第3期53卷 217-225页

作者： Archibald, TW McKinnon, KIM Thomas, LC Univ Edinburgh Sch Management Edinburgh EH8 9YL Midlothian Scotland Univ Edinburgh Sch Math Edinburgh EH8 9YL Midlothian Scotland Univ Southampton Sch Management Southampton SO9 5NH Hants England

stochastic dynamic programming models are attractive for multireservoir control problems because they allow nonlinear features to be incorporated and changes in hydrological conditions to be modeled as Markov processes. However, with the exception of the simplest cases, these models are computationally intractable because of the high dimension of the state and action spaces involved. This paper proposes a new method of determining an operating policy for a multireservoir control problem that uses stochastic dynamic programming, but is practical for systems with many reservoirs. Decomposition is first used to reduce the problem to a number of independent subproblems. Each subproblem is formulated as a low-dimensional stochastic dynamic program and solved to determine the operating policy for one of the reservoirs in the system. (c) 2006 Wiley Periodicals, Inc.

关键词： multireservoir systems stochastic dynamic programming decomposition principal components

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An Analysis on Airport-Airline Vertical Relationships with Risk Sharing Contracts under Asymmetric Information Structures

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Procedia - Social and Behavioral Sciences 2011年 20卷 1090-1098页

作者： Katsuya Hihara GraSPP University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo Japan

We analyze the joint venture type airport-airline vertical relationship under double moral hazard, where both make efforts but neither can see the other's efforts. With continuous-time stochastic dynamic programming model, we show, by each party's de-centralized utility maximizations, they can agree on the optimal contract, which is linear function of the final state, slope being the product of their productivity difference and diffusion rate index, when optimal effort costs are negligible and risk averse parameters both asymptotically approach zero. If productivities are same, or diffusion rate is unity, the optimal linear sharing rule do not depend on the final state.

关键词： Airport-Airline Vertical Relationship Load Factor Guarantee Mechanism Double Hidden Action/Moral Hazard Risk Sharing stochastic dynamic programming

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Converging marriage in honey-bees optimization and application to stochastic dynamic programming

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JOURNAL OF GLOBAL OPTIMIZATION 2006年第3期35卷 423-441页

作者： Chang, Hyeong Soo Sogang Univ Dept Comp Sci & Engn Seoul 121742 South Korea Sogang Univ Program Integrated Biotechnol Seoul South Korea

In this paper, we first refine a recently proposed metaheuristic called "Marriage in Honey-Bees Optimization" (MBO) for solving combinatorial optimization problems with some modifications to formally show that MBO converges to the global optimum value. We then adapt MBO into an algorithm called "Honey-Bees Policy Iteration" (HBPI) for solving infinite horizon-discounted cost stochastic dynamic programming problems and show that HBPI also converges to the optimal value.

关键词： honey-bees optimization Markov decision process policy iteration stochastic dynamic programming swarm intelligence

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Optimal Utilization of Storage and the Induced Price Elasticity of Demand in the Presence of Ramp Constraints

Optimal Utilization of Storage and the Induced Price Elastic...

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IEEE Conference on Decision and Control

作者： Ali Faghih Mardavij Roozbehani Munther A. Dahleh Electrical Engineering and Computer Science (EECS) Laboratory for Information and Decision Systems (LIDS) at the Massachusetts Institute of Technology (MIT) Cambridge MA LIDS MIT EECS Department at MIT

ISBN: (纸本)9781612848006

关键词： Value of Storage Ramp Constraints Price Elasticity of Demand stochastic dynamic programming

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