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dynamic order acceptance and capacity planning on a single bottleneck resource

NAVAL RESEARCH LOGISTICS 2007年第8期54卷 874-889页

作者： Herbots, Jade Herroelen, Willy Leus, Roel Katholieke Univ Leuven Dept Decis Sci & Informat Management Louvain Belgium

We present a tactical decision model for order acceptance and capacity planning that maximizes the expected profits from accepted orders, allowing for aggregate regular as well as nonregular capacity. The stream of incoming order arrivals is the main source of uncertainty in dynamic order acceptance and the company only has forecasts of the main properties of the future incoming projects. Project proposals arrive sequentially with deterministic interarrival times and a decision on order acceptance and capacity planning needs to be made each time a proposal arrives and its project characteristics are revealed. We apply stochastic dynamic programming to determine a profit threshold for the accept/reject decision as well as to deterministically allocate a single bottleneck resource to the accepted projects, both with an eye on maximizing the expected revenues within the problem horizon. We derive a number of managerial insights based on an analysis of the influence of project and environmental characteristics on optimal project selection and aggregate capacity usage. (c) 2007 Wiley Periodicals, Inc.

关键词： order acceptance capacity planning multiproject stochastic dynamic programming

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A multi-objective re-assembling policy model and its implementation in the case of a network of personal computers

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COMPUTERS & MATHEMATICS WITH APPLICATIONS 2010年第1期59卷 391-398页

作者： Rachaniotis, N. P. Pappis, C. P. Tsoulfas, G. T. Dasaklis, T. Univ Piraeus Dept Ind Management Piraeus 18534 Greece

Re-assembling identical or similar deteriorating systems which are elements of a network (for example, a network of personal computers) from used and new parts represents a special case of closed loop supply chains management. Environmental gains may incur, since the life cycle of used components may be extended by re-using them instead of putting them into the waste stream. These benefits are assessed using a case study referring to personal computers. The problem examined is to find proper re-assembly policies in a time period, under a limited budget as well as re-assembly and compatibility constraints, so as to obtain the Pareto optimal solutions for the overall performance and the total environmental savings. (C) 2009 Elsevier Ltd. All rights reserved.

关键词： Re-assembly Deteriorating systems stochastic dynamic programming Environmental performance

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Scheduling of design projects with uncertain number of iterations

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 1999年第3期113卷 575-592页

作者： Luh, PB Liu, F Moser, B Univ Connecticut Dept Elect & Syst Engn Storrs CT 06269 USA Univ Tokyo United Technol Res Ctr Tokyo Japan

A short product design cycle is critical to the success of companies in the era of time-based competition. The underlying design activities, however, are often interlinked and quite uncertain. For example, some activities may have to be iterated several times to meet the design criteria. Furthermore, time-critical projects suffer the risk of failure if they cannot meet established target dates. Generating good and robust schedules is thus critical, especially under the concurrent engineering paradigm where the delay of a single task may have a domino effect on subsequent tasks and on other projects sharing designers and/or resources. This paper studies the scheduling of design projects with uncertain number of iterations while managing design risks. A "separable" problem formulation that balances modeling accuracy and computation complexity is created with the goal to minimize project tardiness and risk penalties. An optimization-based methodology that combines Lagrangian relaxation, stochastic dynamic programming, and "ordinal optimization" is developed. Numerical results supported by simulation demonstrate that near optimal solutions are obtained, and uncertainties are effectively managed for problems of practical sizes. (C) 1999 Elsevier Science B.V. All rights reserved.

关键词： scheduling theory design project management integer programming stochastic dynamic programming risk management

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An approximate dynamic programming based approach to dual adaptive control

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JOURNAL OF PROCESS CONTROL 2009年第5期19卷 859-864页

作者： Lee, Jong Min Lee, Jay H. Georgia Inst Technol Sch Chem & Biomol Engn Atlanta GA 30332 USA Univ Alberta Edmonton AB T6G 2G6 Canada

In this paper, an approximate dynamic programming (ADP) based strategy is applied to the dual adaptive control problem. The ADP strategy provides a computationally amenable way to build a significantly improved policy by solving dynamic programming on only those points of the hyper-state space sampled during closed-loop Monte Carlo simulations performed under known suboptimal control policies. The potentials of the ADP approach for generating a significantly improved policy are illustrated on an ARX process with unknown/varying parameters. (C) 2009 Elsevier Ltd. All rights reserved.

关键词： Dual control stochastic optimal control Adaptive control stochastic dynamic programming Approximate dynamic programming

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Peak-Load Energy Management by Direct Load Control Contracts

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MANAGEMENT SCIENCE 2023年第5期69卷 2788-2813页

作者： Fattahi, Ali Dasu, Sriram Ahmadi, Reza Johns Hopkins Univ Carey Business Sch Baltimore MD 21202 USA Univ Southern Calif Marshall Sch Business Los Angeles CA 90089 USA Univ Calif Los Angeles Anderson Sch Management Los Angeles CA 90089 USA

We study direct load control contracts that utilities use to curtail customers' electricity consumption during peak-load periods. These contracts place limits on the number of calls and total number of hours of power reduction per customer per year as well as the duration of each call. The stochastic dynamic program that determines how many customers to call and the timing and duration of each call for each day is an extremely difficult (NP-hard) optimization problem. We design a scenario-based approximation method to generate probabilistic allocation polices in a reasonable amount of time. Our approach consists of three approximations: deterministic approximation of demand, discretization of the expected demand, and aggregation/disaggregation of the resources. We show the relative information error resulting from the deterministic approximation is O(1/root ==), the discretizan tion error is O(1/n), and the aggregation/disaggregation error is O(1/n), where n represents the length of the horizon. Finally, we show the total relative error is O(1/== root ). Our n error analysis establishes that our approximation method is near optimal. In addition, our extensive numerical experiments verify the high quality of our approximation approach. The error, conservatively measured, is quite small and has an average and standard deviation of 8.6% and 1.4%, respectively. We apply our solution approach to the data provided by three major utility companies in California. Overall, our study shows our procedure improves the savings in energy-generation cost by 37.7% relative to current practices.

关键词： optimization electricity industries stochastic dynamic programming error analysis scheduling

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Optimal timing of airline promotions under dilution

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2019年第3期277卷 981-995页

作者： Otero, Daniel F. Escallon, Mariana Lopez, Cristina Akhavan-Tabatabaei, Raha Univ Los Andes Dept Ind Engn Bogota Colombia Sabanci Sch Management Istanbul Turkey Univ Michigan Dept Ind & Operat Engn Ann Arbor MI 48109 USA Northwestern Univ Dept Ind Engn & Management Sci Evanston IL 60208 USA

Offering promotions has become common practice in the airline industry as a strategy to boost the total revenue. An effective promotion campaign should be adequately priced and timed to attract sufficient extra demand and compensate for the markdown price. Diversion of demand from the regular fare to the markdown price is also a side-effect of offering promotions, which needs to be considered in designing successful campaigns. Demand dilution occurs when customers are attracted to the promotional fare from higher fare families, or from future purchases to the promotional time window. We propose a stochastic dynamic model for the optimal timing of promotions, considering both types of dilution and given fixed prices for the regular and promotional fares. We prove the existence of an optimal policy, and derive structural properties to find the minimum number of unsold seats that justifies the promotion under dilution. We examine the performance of this model on two cases from a Latin American airline and demonstrate considerable savings by applying our proposed optimal policy versus the airline's current policy. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Revenue management stochastic dynamic programming Dilution Airline promotion

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Multi-stand forest management under a climatic risk: Do time and risk preferences matter?

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ENVIRONMENTAL MODELING & ASSESSMENT 2008年第2期13卷 181-193页

作者： Couture, Stephane Reynaud, Arnaud Univ Toulouse 1 LERNA INRA F-31042 Toulouse France LEF INRA ENGREF F-54042 Nancy France

We propose a stochastic dynamic programming framework to model the management of a multi-stand forest under climate risk (strong wind occurrence). The preferences of the forest-owner are specified by a non-expected utility in order to separately analyze intertemporal substitution and risk aversion effects. A numerical method is developed to characterize the optimal forest management policies and the optimal consumption-saving strategy. The stochastic dynamic programming framework is applied to a non-industrial private forest-owner located in North-East of France. We show that the optimal decisions both depend upon risk and time preferences.

关键词： forest economics stochastic dynamic programming non-expected utility climate risk

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Recycled content claims under demand benefit and supply uncertainty: Multi-period model and application to glasswool insulation

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2023年第2期309卷 745-761页

作者： Iyer, Ananth V. Vedantam, Aditya Lacourbe, Paul SUNY Buffalo Jacobs Management Ctr 160 Sch Management Buffalo NY USA SUNY Buffalo Jacobs Management Ctr 326G Dept Operat Management & Strategy Buffalo NY 14260 USA Alba Grad Business Sch 6-8 Xenias St Athens Greece

Manufacturers often declare recycled content claims that are specific (e.g., to each production period) or average (e.g., across many production periods). Such claims are manifested through the choice of certification and generate demand for the manufacturer's recycled content product. However, since the amount of usable recycled input available from local sources is often limited and uncertain, and external (non-local) sources are expensive, a manufacturer needs to balance the demand-side benefits of a recycled content claim with the associated sourcing and inventory costs. In this paper, we develop a multi-period model over a planning horizon, where a manufacturer makes a product's source mix decision (recycled input vs. virgin content) and recycled input carryover decision each period in the presence of a stochastic supply and external sourcing cost. We solve for the manufacturer's optimal recycled content claim decision over a planning horizon and calculate the manufacturer's profit, recycled input, and virgin raw material usage at the optimal claim. Our key contributions are as follows. We show that (i) a shorter (longer) planning horizon may sometimes increase (decrease) the recycled content claim, (ii) demand stimulation for recycled products may sometimes decrease the optimal recycled content claim, and (iii) supply stabilization (i.e., lowering variability in the municipal stream) may decrease the recycled content claim. We provide numerical results for parameters driven by European data from the fiberglass insulation industry and use our analysis to quantify the impact of several European policies relevant to the glasswool insulation industry on a manufacturer's incentive to incorporate recycled content. (c) 2023 Elsevier B.V. All rights reserved.

关键词： Supply chain management Manufacturing Recycled content Supply uncertainty stochastic dynamic programming

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A reinforcement learning approach to distribution-free capacity allocation for sea cargo revenue management

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INFORMATION SCIENCES 2021年 571卷 623-648页

作者： Seo, Dong-Wook Chang, Kyuchang Cheong, Taesu Baek, Jun-Geol Korea Univ Sch Ind & Management Engn Seoul 02841 South Korea

In this paper, we propose learning-based adaptive control based on reinforcement learning for the booking policy in sea cargo revenue management. The problem setting is that the demand distribution is unknown while the historical data is available, and the problem is formulated as a stochastic dynamic programming model. We demonstrate the existence of an optimal control limit policy and investigate the important properties and optimal policy structures of the model. We then propose a reinforcement learning approach for the data-driven approximation of the optimal booking policy to maximize shipping line revenue. The performance of the proposed approach is very close to that of the optimal policy and superior to that of the EMSR-b algorithm. (c) 2021 Elsevier Inc. All rights reserved.

关键词： Revenue management stochastic dynamic programming Reinforcement learning Liner shipping

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Inventory management for dual sales channels with inventory-level-dependent demand

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JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 2015年第3期66卷 488-499页

作者： Li, Tingting Zhao, Xiaobo Xie, Jinxing Tsinghua Univ Dept Math Sci Beijing 100084 Peoples R China Tsinghua Univ Dept Ind Engn Beijing 100084 Peoples R China

This paper studies the inventory management problem of dual channels operated by one vendor. Demands of dual channels are inventory-level-dependent. We propose a multi-period stochastic dynamic programming model which shows that under mild conditions, the myopic inventory policy is optimal for the infinite horizon problem. To investigate the importance of capturing demand dependency on inventory levels, we consider a heuristic where the vendor ignores demand dependency on inventory levels, and compare the optimal inventory levels with those recommended by the heuristic. Through numerical examples, we show that the vendor may order less for dual channels than those recommended by the heuristic, and the difference between the inventory levels in the two cases can be so large that the demand dependency on inventory levels cannot be neglected. In the end, we numerically examine the impact of different ways to treat unmet demand and obtain some managerial insights.

关键词： inventory-level-dependent demand stochastic dynamic programming dual sales channels

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