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The Effects of Firm Size and Production Cost Levels on dynamically Optimal After-Tax Cotton Storage and Hedging Decisions

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Journal of Agricultural and Applied Economics 2017年第1期23卷 165-179页

作者： Russell Tronstad University of Arizona

Farm size and production costs are varied in a six state variable stochastic dynamic programming model that quantifies monthly hedging, storage, and cash cotton sale decisions for an Alabama cotton producer. State variables considered are: (1) cash cotton price; (2) basis level; (3) before-tax income level; (4) cotton holdings; (5) futures position; and (6) value of futures position. Results indicate that when farm size and production cost level differ, marketing decisions diverge the most for cash cotton sales at the end of the tax year and lower range of cash price (less than $.65/lb.), basis (less than -$.05/lb.), and before-tax income (less than $0.00) states.

关键词： farm size production costs stochastic dynamic programming

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Two-step optimal energy management strategy for single-shaft series-parallel powertrain

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MECHATRONICS 2016年 36卷 147-158页

作者： Li, Liang Yan, Bingjie Song, Jian Zhang, Yuanbo Jiang, Guirong Li, Lei Tsinghua Univ State Key Lab Automot Safety & Energy Beijing 100084 Peoples R China Yanshan Univ Coll Mech Engn Qinhuangdao 066004 Hebei Peoples R China Suzhou Green Control Transmiss Technol Co Ltd Suzhou Jiangsu Peoples R China

The series-parallel architecture of the plug-in hybrid electric powertrain has attracted wide attentions in recent years for its flexible and highly efficient operating modes. However, despite the improvement of the vehicle fuel economy, it has been gradually facing more challenges on the design of the optimal controller due to the complex structure and the fast depletion of the battery. In this paper, a two-step optimal energy management strategy is proposed for a novel single-shaft series-parallel powertrain. In the first step, an equivalent method is adopted, in which two motors are equivalently regarded as one. After detailed analysis of the operating modes, various objective functions are established to pre-optimize the power split between engine and motor or two motors. In the second step, a stochastic dynamic programming (SDP) is adopted to optimize the power split between the engine and the equivalent motor, and the optimal combination of the operating modes. Then coupled with the pre-optimized results of the first step, the optimal power split among the engine and two motors could be obtained and then constructed as simple lookup-tables, which have great potential for practical applications. Finally, the preliminary test about the real-time performance of the optimal results is developed on the hardware-in-the-loop (HIL) system. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Energy management strategy Plug-in hybrid electric powertrain Two step method stochastic dynamic programming HIL

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Optimal hedging through limit orders

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stochastic MODELS 2016年第4期32卷 593-605页

作者： Agliardi, Rossella Univ Bologna Dept Math Viale Filopanti 5 I-40126 Bologna Italy

This article applies the methods of stochastic dynamic programming to a risk management problem, where an agent hedges her derivative position by submitting limit orders. Therefore, this model is the first, in the literature on optimal trading with limit orders, to handle a problem of hedging options or other derivatives. A hedging strategy is developed where both the size and the limit price of each order is optimally set.

关键词： Hedging limit orders martingales stochastic dynamic programming 91G20 91G80 G11 G13 C61

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Stock-level dependent ordering of perishables: A comparison of hybrid base-stock and constant order policies

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2016年第PartA期181卷 215-225页

作者： Haijema, Rene Minner, Stefan TI Food & Nutr Wageningen Netherlands Wageningen Univ Operat Res & Logist Hollandseweg 1 NL-6706 KN Wageningen Netherlands Tech Univ Munich TUM Sch Management Munich Germany

In practice, traditional stock-level dependent policies, like base-stock policies (BSP) and constant order policies (COP), are commonly used for replenishing inventories of perishable products at retailers. These policies are preferred for being easy to implement: they only require information on the total number of products in stock, but not differentiated by their age. In this paper, we analyze a number of new and existing hybrid BSP-COP policies. These policies have different complexities, but, so far, they have not been systematically compared with respect to their performance. By simulation-based optimization, the parameter values of the policies are determined. For this purpose, search ranges for the parameter values are provided. Based on an extensive set of experiments, insights are gained on when to apply which policy. The results show that two newly proposed enhancements of traditional base-stock policies, in particular, perform well and can be recommended for practical implementation. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Perishable Inventory Management Food Waste Base-Stock Policy Constant Order Policy Heuristics Simulation-based Optimization stochastic dynamic programming

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Optimal Storage Scheduling Using Markov Decision Processes

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IEEE TRANSACTIONS ON SUSTAINABLE ENERGY 2016年第2期7卷 755-764页

作者： Grillo, Samuele Pievatolo, Antonio Tironi, Enrico Politecn Milan Dipartimento Elettron Informaz & Bioingn I-20133 Milan Italy CNR IMATI I-20133 Milan Italy

The paper presents a method based on Markov decision processes to optimally schedule energy storage devices in power distribution networks with renewable generation. The time series of renewable generation is modeled as a Markov chain which allows for the implementation of a stochastic dynamic programming algorithm. The output of this algorithm is an optimal scheduling policy for the storage device achieving the minimization of an objective function including cost of energy and network losses. Besides this, other properties, such as energy storage placement and size, can be assessed and compared in optimized systems with different layouts.

关键词： Energy storage Markov processes renewable generation stochastic dynamic programming

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服务水平约束下动态定价与库存管理

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管理科学 2019年第9期

作者：段永瑞徐超霍佳震

本文研究服务水平约束下的动态定价与库存管理问题。企业在有限期内销售某种产品，产品的需求为随机需求，且期望需求依赖于产品价格。在每一期期初，企业需要在满足服务水平约束的条件下同时决定订货量和产品价格。本文首先构建了动态... 详细信息

本文研究服务水平约束下的动态定价与库存管理问题。企业在有限期内销售某种产品，产品的需求为随机需求，且期望需求依赖于产品价格。在每一期期初，企业需要在满足服务水平约束的条件下同时决定订货量和产品价格。本文首先构建了动态定价和订购联合决策的随机动态规划模型，并证明了最优解的存在性。进一步，通过对最优解的结构进行刻画，将原问题的求解转化为若干子问题的求解，降低了问题求解的难度。通过对最优解的分析发现，当期初库存增大时，产品最优价格降低。通过分析目标服务水平对利润的影响，证明了服务水平与利润之间存在权衡，实现高的服务水平需要承受利润损失。数值模拟表明，相对于传统的静态定价策略，采用动态定价策略可以降低追求服务水平所带来的利润损失，验证了动态定价策略的有效性。

关键词：动态定价库存管理服务水平约束随机动态规划　　dynamic pricing inventory management service level constraint stochastic dynamic programming

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dynamic procurement management by reverse auctions with fixed setup costs and sales levers

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APPLIED MATHEMATICAL MODELLING 2016年第4期40卷 3049-3061页

作者： Liu, Shuren Zhu, Yimin Hu, Qiying Xiangtan Univ Sch Business Xiangtan 411105 Peoples R China Quzhou Coll Dept Math & Sci Quzhou 324000 Peoples R China Fudan Univ Sch Management Shanghai 200433 Peoples R China

In this paper, we study a dynamic procurement problem for a retailer with fixed setup costs and sales levers (such as pricing, advertising, etc.). The retailer runs a reverse auction with a procurement contract in each period. A number of potential suppliers bid for this contract, and the winner is the supplier with the highest bid and is given the decision right for the quantity produced and delivered. The demand is either realized by selling via Internet auctions and unmet demand is lost, or is a price-sensitive nonnegative random variable and all shortages are backlogged. We show the existence of the retailer's optimal procurement contract, under which the suppliers' Bayesian Nash equilibrium bidding strategy is (q(.), Q(.)), similar to the classic (s, S) policy for the retailers in dynamic inventory control problems. However, the (q(.), Q(.)) strategy here is for the suppliers and is realized through the suppliers' marginal production costs and so consists of two random variables for the retailer. (C) 2015 Elsevier Inc. All rights reserved.

关键词： dynamic procurement strategy Reverse auction Sales levers stochastic dynamic programming

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A Markov chain model of military personnel dynamics

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2016年第6期54卷 1863-1885页

作者： Zais, Mark Zhang, Dan Off Secretary Def Washington DC USA Univ Colorado Leeds Sch Business Boulder CO 80309 USA

Personnel retention is one of the most significant challenges faced by the US Army. Central to the problem is understanding the incentives of the stay-or-leave decision for military personnel. Using three years of data from the US Department of Defense, we construct and estimate a Markov chain model of military personnel. Unlike traditional classification approaches, such as logistic regression models, the Markov chain model allows us to describe military personnel dynamics over time and answer a number of managerially relevant questions. Building on the Markov chain model, we construct a finite-horizon stochastic dynamic programming model to study the monetary incentives of stay-or-leave decisions. The dynamic programming model computes the expected pay-off of staying versus leaving at different stages of the career of military personnel, depending on employment opportunities in the civilian sector. We show that the stay-or-leave decisions from the dynamic programming model possess surprisingly strong predictive power, without requiring personal characteristics that are typically employed in classification approaches. Furthermore, the results of the dynamic programming model can be used as an input in classification methods and lead to more accurate predictions. Overall, our work presents an interesting alternative to classification methods and paves the way for further investigations on personnel retention incentives.

关键词： Markov chain estimation stochastic dynamic programming reenlistment propensity

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Container relocation problem with time windows for container departure

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2016年第3期252卷 1031-1039页

作者： Ku, Dusan Arthanari, Tiru S. Univ Auckland Sch Business Dept Informat Syst & Operat Management Private Bag 92019 Auckland 1421 New Zealand

The blocks relocation problem is a classic combinatorial optimisation problem that occurs in daily operations for facilities that use block stacking systems. In the block stacking method, blocks can be stored on top of each other in order to utilise the limited surface of a storage area. When there is a predetermined pickup order among the blocks, this stacking method inevitably leads to the reshuffling moves for blocks stored above the target block and the minimisation of such unproductive reshuffling moves is of a primary concern to industry practitioners. A container terminal is a typical place where this problem arises, thus the problem being also referred to as the container relocation problem. In this study, we consider departure time windows for containers, which are usually revealed by the truck appointment system in port container terminals. We propose a stochastic dynamic programming model to calculate the minimum expected number of reshuffles for a stack of containers which all have departure time windows. The model is solved with a search-based algorithm in a tree search space, and an abstraction heuristic is proposed to improve the time performance. To overcome the computational limitation of exact methods, we develop a heuristic called the expected reshuffling index (ERI) and evaluate its performance. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Logistics Container relocation problem Truck appointment system stochastic dynamic programming Abstraction heuristics

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Opportunistic scheduling for a two-way relay network using Markov decision process

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IET COMMUNICATIONS 2016年第14期10卷 1846-1854页

作者： Meshgi, Hadi Zhao, Dongmei McMaster Univ Dept Elect & Comp Engn Hamilton ON Canada

In this study, the authors study transmission scheduling for a two-way relay network in time-varying fading channels, where the relay node can opportunistically use traditional one-way relay technique or network coding to forward traffic to the end nodes. They formulate a stochastic dynamic programme with the objective of minimising the long-run cost, defined as a function of both the transmission power and data transmission delay. An unconstrained Markov decision process model is developed and solved for the average and discounted cost problems. The optimal solution requires high computational and modelling complexity when the state space is large. For this reason, they develop heuristic solutions with lower complexity. For the discounted cost problem, a simulation-based dynamic programming algorithm is proposed that not only simplifies the modelling process and reduces the computational complexity, but also achieves close-to-optimum cost. For the average cost problem, a heuristic scheduling scheme is proposed, which makes transmission decisions based on estimated costs in the current and next time slots. The heuristic scheme achieves close-to-optimum cost performance while greatly reducing the computational complexity.

关键词： Markov processes decision theory telecommunication scheduling relay networks (telecommunication) time-varying channels fading channels minimisation stochastic programming dynamic programming computational complexity network coding telecommunication traffic opportunistic scheduling two-way relay network transmission scheduling time-varying fading channels relay node one-way relay technique network coding stochastic dynamic programming long-run cost minimization data transmission delay transmission power function unconstrained Markov decision process model discounted cost problems computational complexity modelling complexity simulation-based dynamic programming algorithm close-to-optimum cost heuristic scheduling scheme next time slots close-to-optimum cost performance average cost problems

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