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16th IFAC Symposium on Control in Transportation Systems (CTS)

作者： Typaldos, P. Volakakis, V. Papageorgiou, M. Papamichail, I Tech Univ Crete Sch Prod Engn & Management Dynam Syst & Simulat Lab Khania 73100 Greece

Vehicle-based GLOSA (Green Light Optimal Speed Advisory) systems use information about the next switching time of the traffic lights to calculate fuel-efficient position and velocity profiles for connected vehicles, according to their current state (position and speed). A stochastic optimal control problem was recently proposed to address the GLOSA problem in cases where the next switching time is decided in real time and is therefore uncertain in advance. The corresponding numerical solution via SDP (stochastic dynamic programming) calls for substantial computational time (few minutes), which excludes problem solution in the vehicle's computer in real time. This work considers the same stochastic problem of optimal trajectory specification for vehicles approaching a signalized junction with traffic signals operated in real-time (adaptive) mode, due to which the next switching time is stochastic. However, a modified version of dynamic programming, known as Discrete Differential dynamic programming (DDDP), is used for numerical solution of the stochastic optimal control problem. It is demonstrated, based on a realistic example, that the DDDP algorithm achieves results equivalent to those obtained with the ordinary SDP algorithm, albeit with significantly better performance in terms of computational time. Specifically, the solution is typically obtained in around 1 CPUs, which is real-time feasible and would allow for the DDDP calculations to be executed in the vehicles on-board computer. Copyright (C) 2021 The Authors.

关键词： GLOSA stochastic dynamic programming Discrete Differential dynamic programming (DDDP) Traffic Light Advisory Speed Advisory

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Distributed Combined Cooling Heating and Power Optimization in a Microgrid Based on Collocation Method

Distributed Combined Cooling Heating and Power Optimization ...

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2017 International Electrical and Energy Conference (CIEEC 2017)

作者： Feng Gao Jun Hu Qinglai Guo Dongyuan Zhao Yang Wang Gerald Sheble Xuanyuan Wang Tsinghua University Energy Internet Research Institute Tsinghua University Department of Electrical Engineering

ISBN: (纸本)9781509062775;9781509062768

Distributed combined cooling heating and power system develops as a novel energy supply way in recent years,which achieves energy cascading utilization,boosts the energy efficiency and is regarded as environment-friendly,economical,and reliable option for the *** paper first proposes a general methodology called Collocation Algorithm to optimize CCHP performance;second introduces a dynamic model to evaluate CCHP operating cost and combine power network analysis with heating/cooling energy dispatch;and third presents a numerical example to efficiently resolve the resulting stochastic dynamic programming *** paper demonstrates results on a simulated data set.

关键词： Combined Cooling Heating and Power Microgrid Collocation Method stochastic dynamic programming

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Developing an integrated revenue management and customer relationship management approach in the hotel industry

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JOURNAL OF REVENUE AND PRICING MANAGEMENT 2015年第2期14卷 97-119页

作者： Vaeztehrani, Amirhossein Modarres, Mohammad Aref, Samin Sharif Univ Technol Dept Ind Engn Azadi AvePOB 11365-11155 Tehran Iran Univ Auckland Dept Comp Sci Auckland New Zealand

Revenue management (RM) and customer relationship management (CRM) are the standard strategies of many hotels to increase their profitability. Although the objectives and time horizons of RM and CRM are different, they can be considered as complimentary business strategies. However, the integration has received little attention both practically and theoretically. In this study, we develop an approach to jointly make the capacity allocation and overbooking decisions considering CRM strategies over a hotel network. Hotel customers are divided based on their lifetime value into two major groups of occasional and loyal customers. Price discounts and room availability guarantee (RAG) are offered to loyal customers, who are the hotel's essential source of profit. The main problem is tackled by a stochastic dynamic programming model whose expected value of objective function is approximated by two deterministic linear programming-based algorithms. The computational results indicate that the loyalty programs may lead to decrease in short-term net revenue. However, another analysis is required to decide upon cost-effectiveness of loyalty programs in an extended planning horizon. On the basis of an estimated discount-RAG response function, the cost-effectiveness of different loyalty programs is compared, which shows potential increase in hotel expected net revenue up to 3.5 per cent. The analytical long-term evaluation of loyalty programs introduced is capable of determining the most appropriate loyalty program factors. Moreover, it suggests discount-RAG response function and the level of tightness as sensitive parameters.

关键词： network revenue management customer relationship management hotel industry loyalty programs overbooking stochastic dynamic programming

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Optimal Electric Energy Storage Operation

Optimal Electric Energy Storage Operation

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General Meeting of the IEEE-Power-and-Energy-Society

作者： Qin, Junjie Sevlian, Raffi Varodayan, David Rajagopal, Ram Stanford Univ Inst Computat & Math Engn Stanford CA 94305 USA

ISBN: (纸本)9781467327299

Estimating the arbitrage value of storage is an important problem in power systems planning. Various studies have reported different values based numerical solutions of variations of a basic model. In this paper, we instead rely on a closed form solution for storage control. The closed form highlights the right type of forecasting that is required and allows large horizon problems to be solved. We study various scenarios and provide a simple methodology for evaluating the arbitrage value of storage.

关键词： Energy storage operation stochastic dynamic programming warehousing problem

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Explicit approximation of stochastic optimal feedback control for combined therapy of cancer

Explicit approximation of stochastic optimal feedback contro...

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American Control Conference (ACC)

作者： Alamir, Mazen

ISBN: (纸本)9798350382662;9798350382655

In this paper, a tractable methodology is proposed to approximate stochastic optimal feedback treatment in the context of mixed immuno-chemothrapy therapy of cancer. The method uses a fixed-point value iteration that approximately solves a stochastic dynamic programming-like equation. It is in particular shown that the introduction of a variance-related penalty in the latter induces better results that cope with the consequences of softening the health safety constraints in the cost function. The convergence of the value function iteration is revisited in the presence of the variance related term. The implementation involves some Machine Learning tools in order to represent the optimal function and to perform complexity reduction by clustering. Quantitative illustration is given using a commonly used model of combined therapy involving twelve highly uncertain parameters.

关键词： stochastic optimal control stochastic dynamic programming Cancer therapy Machine Learning Clustering

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A simple but powerful simulated certainty equivalent approximation method for dynamic stochastic problems

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QUANTITATIVE ECONOMICS 2023年第2期14卷 651-687页

作者： Cai, Yongyang Judd, Kenneth L. Ohio State Univ Dept Agr Environm & Dev Econ Columbus OH 43210 USA Stanford Univ Hoover Inst Stanford CA USA

We introduce a novel simulated certainty equivalent approximation (SCEQ) method for solving dynamic stochastic problems. Our examples show that SCEQ can quickly solve high-dimensional finite- or infinite-horizon, stationary or nonstationary dynamic stochastic problems with hundreds of state variables, a wide state space, and occasionally binding constraints. With the SCEQ method, a desktop computer will suffice for large problems, but it can also use parallel tools efficiently. The SCEQ method is simple, stable, and can utilize any solver, making it suitable for solving complex economic problems that cannot be solved by other algorithms.

关键词： stochastic dynamic programming competitive equilibrium large-scale model integrated assessment model new Keynesian model zero lower bound occasionally binding constraint nonstationary problem parallelism C61 C63 C68 Q54 Q58

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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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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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Injection Mold Replacement Analysis in Automotive Industry

Injection Mold Replacement Analysis in Automotive Industry

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IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)

作者： Suwannabool, T. Sutivong, D. Chulalongkorn Univ Dept Ind Engn Bangkok 10330 Thailand

ISBN: (纸本)9781467329453

Injection mold replacement decisions in the automotive industry are usually made by managers and engineers, who based primarily on their own experience. This paper presents an injection mold replacement analysis through the use of stochastic dynamic programming and benchmark from the case study. The algorithm determines a optimal production volume and age that give the minimum expected cost under time constraint. The solutions are presented as a decision chart for easy application and interpretation.

关键词： Injection mold replacement analysis stochastic dynamic programming maintenance decision chart

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stochastic Decision Diagrams 1

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19th International Conference on the Integration of Constraint programming, Artificial Intelligence, and Operations Research (CPAIOR)

作者： Hooker, J. N. Carnegie Mellon Univ Pittsburgh PA 15213 USA

ISBN: (数字)9783031080111

ISBN: (纸本)9783031080111;9783031080104

We introduce stochastic decision diagrams (SDDs) as a generalization of deterministic decision diagrams, which in recent years have been used to solve a variety of discrete optimization and constraint satisfaction problems. SDDs allow one to extend the relaxation techniques of deterministic diagrams to stochastic dynamic programming problems in which optimal controls are state-dependent. In particular, we develop sufficient conditions under which node merger operations applied during top-down compilation of the SDD yield a valid relaxed SDD whose size can be limited as desired. The relaxed SDD provides bounds on the optimal value that can be used to evaluate the quality of solutions obtained heuristically or to accelerate the search for an optimal solution. This results in a general and completely novel method for obtaining optimization bounds for stochastic dynamic programming, and the only method that can be applied to the original state space. We report computational experience on stochastic maximum clique (equivalently, maximum independent set) problem instances.

关键词： stochastic decision diagrams stochastic dynamic programming relaxed decision diagrams maximum clique problem

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stochastic Optimization Based on Principal-agent Problem

Stochastic Optimization Based on Principal-agent Problem

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2nd ISECS International Colloquium on Computing, Communication, Control and Management (CCCM 2009)

作者： Ren, Xiaoyu Shao, Xinping Li, Shenghong Zhejiang Univ Dept Math Hangzhou 310027 Zhejiang Peoples R China

ISBN: (纸本)9781424442461

By the theory of stochastic dynamic programming, we provide the methods for deriving the optimal rules. In this paper, we make two models in dynamic state process to maximize the expected utility of the agent and then obtain the famous Hamilton-Jacobi-Bellman equation. Furthermore, we derive explicit form solution and closed-form solution of the optimal equations for given utility functions.

关键词： principal-agent problem stochastic dynamic programming stochastic differential equation stochastic optimal control HJB equation

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