检索结果-内蒙古大学图书馆

Benchmarking a Scalable Approximate Dynamic programming Algorithm for stochastic Control of Grid-Level Energy Storage

引用

INFORMS JOURNAL ON COMPUTING 2018年第1期30卷 106-123页

作者： Salas, Daniel F. Powell, Warren B. Princeton Univ Dept Chem & Biol Engn Princeton NJ 08540 USA Princeton Univ Dept Operat Res & Financial Engn Princeton NJ 08540 USA

We present and benchmark an approximate dynamic programming algorithm that is capable of designing near-optimal control policies for a portfolio of heterogenous storage devices in a time-dependent environment, where wind supply, demand, and electricity prices may evolve stochastically. We found that the algorithm was able to design storage policies that are within 0.08% of optimal on deterministic models, and within 0.86% on stochastic models. We use the algorithm to analyze a dual-storage system with different capacities and losses, and show that the policy properly uses the low-loss device (which is typically much more expensive) for high-frequency variations. We close by demonstrating the algorithm on a five-device system. The algorithm easily scales to handle heterogeneous portfolios of storage devices distributed over the grid and more complex storage networks.

关键词： dynamic programming-optimal control industries: electric programming: stochastic

来源：评论

学校读者我要写书评

暂无评论

USE OF SAMPLE INFORMATION IN stochastic RECOURSE AND CHANCE-CONSTRAINED programming-MODELS

引用

MANAGEMENT SCIENCE 1985年第1期31卷 96-108页

作者： JAGANNATHAN, R UNIV IOWA COLL BUSINESS ADMIOWA CITYIA 52242 USA

In probabilistic linear programming models the decision maker is typically assumed to know the probability distribution of the random parameters. Here it is assumed that the distribution functions of the parameters have a specified functional form F(t, θ), where θ is an unknown (real) vector parameter. We suppose that the decision maker has the opportunity of observing a random sample drawn from F(t, θ). For a two-stage stochastic programming with recourse model the deterministic equivalent model is found using a Bayesian approach. Properties are presented for the deterministic equivalents in general and in the special case of the simple recourse model. Expressions for Expected Value of Sample Information (EVSI) and Expected Net Gain from Sampling (ENGS) are also derived. In the final section similar results are obtained for chance constrained programming models.

关键词： programming: stochastic chance constrained

来源：评论

学校读者我要写书评

暂无评论

stochastic dual dynamic programming applied to nonconvex hydrothermal models

引用

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2012年第3期218卷 687-697页

作者： Cerisola, Santiago Latorre, Jesus M. Ramos, Andres Univ Pontificia Comillas ICAI Inst Invest Tecnol Madrid 28015 Spain

In this paper we apply stochastic dual dynamic programming decomposition to a nonconvex multistage stochastic hydrothermal model where the nonlinear water head effects on production and the nonlinear dependence between the reservoir head and the reservoir volume are modeled. The nonconvex constraints that represent the production function of a hydro plant are approximated by McCormick envelopes. These constraints are split into smaller regions and the McCormick envelopes are used for each region. We use binary variables for this disjunctive programming approach and solve the problem with a decomposition method. We resort to a variant of the L-shaped method for solving the MIP subproblem with binary variables at any stage inside the stochastic dual dynamic programming algorithm. A realistic large-scale case study is presented. (C) 2011 Elsevier B.V. All rights reserved.

关键词： programming: stochastic Integer Benders decomposition Lagrangean relaxation stochastic dual dynamic programming Production/scheduling: planning

来源：评论

学校读者我要写书评

暂无评论

The Value of Multistage stochastic programming in Capacity Planning Under Uncertainty

引用

OPERATIONS RESEARCH 2009年第4期57卷 893-904页

作者： Huang, Kai Ahmed, Shabbir SUNY Binghamton Sch Management Binghamton NY 13902 USA Georgia Inst Technol Sch Ind & Syst Engn Atlanta GA 30332 USA

This paper addresses a general class of capacity planning problems under uncertainty, which arises, for example, in semiconductor tool purchase planning. Using a scenario tree to model the evolution of the uncertainties, we develop a multistage stochastic integer programming formulation for the problem. In contrast to earlier two-stage approaches, the multistage model allows for revision of the capacity expansion plan as more information regarding the uncertainties is revealed. We provide analytical bounds for the value of multistage stochastic programming (VMS) afforded over the two-stage approach. By exploiting a special substructure inherent in the problem, we develop an efficient approximation scheme for the difficult multistage stochastic integer program and prove that the proposed scheme is asymptotically optimal. Computational experiments with realistic-scale problem instances suggest that the VMS for this class of problems is quite high;moreover, the quality and performance of the approximation scheme is very satisfactory. Fortunately, this is more so for instances for which the VMS is high.

关键词： facilities/equipment planning: capacity expansion production/scheduling: planning programming: stochastic

来源：评论

学校读者我要写书评

暂无评论

stochastic programming and the option of doing it differently

引用

ANNALS OF OPERATIONS RESEARCH 2010年第1期177卷 3-8页

作者： Wallace, Stein W. Univ Lancaster Sch Management Dept Management Sci Lancaster LA1 4YX England

Option theory and stochastic programming are tightly linked. Most options can be analyzed in both frameworks, and the two approaches support each other in many slightly more complex situations. But this similarity hides some central differences in perspective. This short note tries to focus on one of these, namely the fact that option theory can be applied only to options already identified, while stochastic programming is able to help us find options in contexts where it is not at all clear what they are, and where finding might be more important than valuing.

关键词： programming: stochastic Relations to option theory

来源：评论

学校读者我要写书评

暂无评论

Uncertain Linear Programs: Extended Affinely Adjustable Robust Counterparts

引用

OPERATIONS RESEARCH 2009年第6期57卷 1469-1482页

作者： Chen, Xin Zhang, Yuhan Univ Illinois Dept Ind & Enterprise Syst Engn Urbana IL 61801 USA

In this paper, we introduce the extended affinely adjustable robust counterpart to modeling and solving multistage uncertain linear programs with fixed recourse. Our approach first reparameterizes the primitive uncertainties and then applies the affinely adjustable robust counterpart proposed in the literature, in which recourse decisions are restricted to be linear in terms of the primitive uncertainties. We propose a special case of the extended affinely adjustable robust counterpart-the splitting-based extended affinely adjustable robust counterpart-and illustrate both theoretically and computationally that the potential of the affinely adjustable robust counterpart method is well beyond the one presented in the literature. Similar to the affinely adjustable robust counterpart, our approach ends up with deterministic optimization formulations that are tractable and scalable to multistage problems.

关键词： programming: stochastic

来源：评论

学校读者我要写书评

暂无评论

Goal-Driven Optimization

引用

OPERATIONS RESEARCH 2009年第2期57卷 342-357页

作者： Chen, Wenqing Sim, Melvyn Natl Univ Singapore NUS Business Sch NUS Risk Management Inst Singapore 117548 Singapore Singapore MIT Alliance SMA Singapore Singapore

We develop a goal-driven stochastic optimization model that considers a random objective function in achieving an aspiration level, target, or goal. Our model maximizes the shortfall-aware aspiration-level criterion, which encompasses the probability of success in achieving the aspiration level and an expected level of underperformance or shortfall. The key advantage of the proposed model is its tractability. We can obtain its solution by solving a small collection of stochastic linear optimization problems with objectives evaluated under the popular conditional-value-at-risk (CVaR) measure. Using techniques in robust optimization, we propose a decision-rule-based deterministic approximation of the goal-driven optimization problem by solving subproblems whose number is a polynomial with respect to the accuracy, with each subproblem being a second-order cone optimization problem (SOCP). We compare the numerical performance of the deterministic approximation with sampling-based approximation and report the computational insights on a multiproduct newsvendor problem.

关键词： programming: stochastic

来源：评论

学校读者我要写书评

暂无评论

Global stochastic optimization with low-dispersion point sets

引用

OPERATIONS RESEARCH 2000年第6期48卷 939-950页

作者： Yakowitz, S L'Ecuyer, P Vázquez-Abad, F Univ Arizona Dept Syst & Ind Engn Tucson AZ USA Univ Montreal Dept Informat & Rech Operat Montreal PQ H3C 3J7 Canada

This study concerns a generic model-free stochastic optimization problem requiring the minimization of a risk function defined on a given bounded domain in a Euclidean space. Smoothness assumptions regarding the risk function are hypothesized, and members of the underlying space of probabilities are presumed subject to a large deviation principle;however, the risk function may well be nonconvex and multimodal. A general approach to finding the risk minimizer on the basis of decision/observation pairs is proposed. It consists of repeatedly observing pairs over a collection of design points. Principles are derived for choosing the number of these design points on the basis of an observation budget, and for allocating the observations between these points in both prescheduled and adaptive settings. On the basis of these principles, large-deviation type bounds of the minimizer in terms of sample size are established.

关键词： Simulation: stochastic optimization design of experiments programming: stochastic adaptive

来源：评论

学校读者我要写书评

暂无评论

An approximation scheme for stochastic integer programs arising in capacity expansion

引用

OPERATIONS RESEARCH 2003年第3期51卷 461-471页

作者： Ahmed, S Sahinidis, NV Georgia Inst Technol Sch Ind & Syst Engn Atlanta GA 30332 USA Univ Illinois Dept Chem & Biomol Engn Urbana IL 61801 USA

Planning for capacity expansion forms a crucial part of the strategic-level decision making in many applications. Consequently, quantitative models for economic capacity expansion planning have been the subject of intense research. However, much of the work in this area has been restricted to linear cost models and/or limited degree of uncertainty to make the problems analytically tractable. This paper addresses a stochastic capacity expansion problem where the economies-of-scale in expansion costs are handled via fixed-charge cost functions, and forecast uncertainties in the problem parameters are explicitly considered by specifying a set of scenarios. The resulting formulation is a multistage stochastic integer program. We develop a fast, linear-programming-based, approximation scheme that exploits the decomposable structure and is guaranteed to produce feasible solutions for this problem. Through a probabilistic analysis, we prove that the optimality gap of the heuristic solution almost surely vanishes asymptotically as the problem size increases.

关键词： Analysis of algorithms: asymptotically optimal heuristics Facilities/equipment planning: capacity expansion programming: stochastic integer

来源：评论

学校读者我要写书评

暂无评论

Assisting Defined-Benefit Pension Plans

引用

OPERATIONS RESEARCH 2008年第5期56卷 1066-1078页

作者： Mulvey, John M. Simsek, Koray D. Zhang, Zhuojuan Fabozzi, Frank J. Pauling, William R. Princeton Univ Bendheim Ctr Finance Dept Operat Res & Financial Engn Princeton NJ 08544 USA Sabanci Univ Fac Management TR-34956 Istanbul Turkey BlackRock Financial Management Inc New York NY 10055 USA Yale Univ Sch Management New Haven CT 06511 USA Hartford Investment Management Co Hartford CT 06105 USA

The defined-benefit pension system poses substantial, long-term risks for the U.S. economy. We describe a flexible asset-liability management (ALM) system for pension planning. The primary goals are to improve the performance and survivability of the pension trust. We first employ a stochastic program for enhancing investment strategies in light of company and other goals and pension risk constraints. The results are linked with a policy simulator for further analysis. We illustrate the concepts via two disparate real-world companies. The first is a slowly growing auto company, and the second a pro. table pharmaceutical enterprise. We show that a stochastic program can help in the process of discovering sound policy rules. The ALM system has been employed extensively throughout the world by a large global actuarial firm.

关键词： decision analysis: multiple criteria risk finance: corporate portfolio programming: stochastic simulation: applications

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：