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Coordination of manufacturing, remanufacturing and returns acceptance in hybrid manufacturing/remanufacturing systems

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2014年 148卷 62-70页

作者： Vercraene, Samuel Gayon, Jean-Philippe Flapper, Simme Douwe Inst Natl Sci Appl DISP F-69621 Villeurbanne France Grenoble INP UJF Grenoble 1 CNRS G SCOP UMR5272 F-38031 Grenoble France Tech Univ Eindhoven NL-5600 MB Eindhoven Netherlands

This paper deals with the coordination of manufacturing, remanufacturing and returns acceptance control in a hybrid production-inventory system. We use a queuing control framework, where manufacturing and remanufacturing are modelled by single servers with exponentially distributed processing times. Customer demand and returned products arrive in the system according to independent Poisson processes. A returned product can be either accepted or rejected. When accepted, a return is placed in a remanufacturable product inventory. Customer demand can be satisfied as well by new and remanufactured products. The following costs are included: stock keeping, backorder, manufacturing, remanufacturing, acceptance and rejection costs. We show that the optimal policy is characterized by two state-dependent base-stock thresholds for manufacturing and remanufacturing and one state-dependent return acceptance threshold. We also derive monotonicity results for these thresholds. Based on these theoretical results, we introduce several relevant heuristic control rules for manufacturing, remanufacturing and returns acceptance. In an extensive numerical study we compare these policies with the optimal policy and provide several insights. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Remanufacturing Manufacturing Returns acceptance control Inventory control stochastic dynamic programming Optimal policy Heuristic policies

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Active Classification for POMDPs: A Kalman-Like State Estimator

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2014年第23期62卷 6209-6224页

作者： Zois, Daphney-Stavroula Levorato, Marco Mitra, Urbashi Univ So Calif Dept Elect Engn Los Angeles CA 90089 USA Univ Calif Irvine Donald Bren Sch Informat & Comp Sci Dept Comp Sci Irvine CA 92697 USA

The problem of state tracking with active observation control is considered for a system modeled by a discrete-time, finite-state Markov chain observed through conditionally Gaussian measurement vectors. The measurement model statistics are shaped by the underlying state and an exogenous control input, which influence the observations' quality. Exploiting an innovations approach, an approximate minimum mean-squared error (MMSE) filter is derived to estimate the Markov chain system state. To optimize the control strategy, the associated mean-squared error is used as an optimization criterion in a partially observable Markov decision process formulation. A stochastic dynamic programming algorithm is proposed to solve for the optimal solution. To enhance the quality of system state estimates, approximate MMSE smoothing estimators are also derived. Finally, the performance of the proposed framework is illustrated on the problem of physical activity detection in wireless body sensing networks. The power of the proposed framework lies within its ability to accommodate a broad spectrum of active classification applications, including sensor management for object classification and tracking, estimation of sparse signals, and radar scheduling.

关键词： Active classification controlled sensing active state tracking partially observable Markov decision processes (POMDP) nonlinear POMDPs Kalman-like filter Kalman-like smoothers innovations approach approximate MMSE estimation stochastic dynamic programming discrete state Markov chains Martingale difference sequence body sensing network application

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An optimal statistical testing policy for software reliability demonstration of safety-critical systems

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2002年第3期137卷 544-557页

作者： Tal, O McCollin, C Bendell, A Nottingham Trent Univ Dept Math Stat & Operat Res Nottingham NG1 4BU England RAFAEL IL-31021 Haifa Israel Univ Leicester Ctr Management Leicester LE1 7RH Leics England

When software reliability demonstration of safety-critical systems by statistical testing is treated as a Test, Analyse and Fix (TAAF) process, an optimal testing policy can be found, which maximises the probability of p success of the whole process, over a pre-determined period of time. The optimisation problem is formulated, solved by stochastic dynamic programming, and demonstrated by two numerical examples. (C) 2002 Elsevier Science B.V. All rights reserved.

关键词： reliability software reliability demonstration statistical testing safety-critical systems stochastic dynamic programming

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A dual sourcing inventory model for modal split transport: Structural properties and optimal solution

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2020年第3期283卷 883-900页

作者： Dong, Chuanwen Transchel, Sandra ESCP Europe Berlin Campus Berlin Germany Kuehne Logist Univ Hamburg Germany

Shifting freight volumes from road to rail transport increases the economic performances of freight logistics. However, compared to road transport, rail transport generally lacks the flexibility in delivery quantity and frequency, and exhibits economies of scale in its shipment volume. This often leads to high inventory levels in the destination after deliveries. We generalize the tailored base-surge dual sourcing inventory model by introducing a fixed cost in rail transport, adding an extra decision in its delivery frequency, and relaxing the assumption of the base stock control of road transport, to support firms' modal split transport optimization. The objective is to optimize the controls of the two transport modes and the corresponding inventory management at the destination, which minimize the combined average transport and inventory costs per period in the steady state. Using stochastic dynamic programming, we find that when the delivery quantity and frequency of rail transport is fixed, the optimal shipment volume via the road transport indeed follows a base stock control. This allows to solve the relevant Bellman equation via an efficient policy iteration approach. We also find that the total cost is convex in the delivery quantity of rail transport, and a bi-section search can be applied. Finally, we analyze the sensitivity and robustness of our model using values suggested by a consumer goods firm. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Inventory Modal split transport Dual sourcing stochastic dynamic programming Optimization

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Finding the K best policies in a finite-horizon Markov decision process

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2006年第2期175卷 1164-1179页

作者： Nielsen, Lars Relund Kristensen, Anders Ringgaard Royal Vet & Agr Univ Dept Large Anim Sci DK-1870 Frederiksberg C Denmark

Directed hypergraphs represent a general modelling and algorithmic tool, which have been successfully used in many different research areas such as artificial intelligence, database systems, fuzzy systems, propositional logic and transportation networks. However, modelling Markov decision processes using directed hypergraphs has not yet been considered. In this paper we consider finite-horizon Markov decision processes (MDPs) with finite state and action space and present an algorithm for finding the K best deterministic Markov policies. That is, we are interested in ranking the first K deterministic Markov policies in non-decreasing order using an additive criterion of optimality. The algorithm uses a directed hypergraph to model the finite-horizon MDP. It is shown that the problem of finding the optimal policy can be formulated as a minimum weight hyperpath problem and be solved in linear time, with respect to the input data representing the MDP, using different additive optimality criteria. (c) 2005 Elsevier B.V. All rights reserved.

关键词： finite-horizon Markov decision processes stochastic dynamic programming directed hypergraphs hyperpaths K best policies

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An approximate dynamic programming approach for sequential pig marketing decisions at herd level

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2019年第3期276卷 1056-1070页

作者： Pourmoayed, Reza Nielsen, Lars Relund Aarhus Univ Dept Econ & Business Econ Fuglesangs Alle 4 DK-8210 Aarhus V Denmark

One of the most important operations in the production of growing/finishing pigs is the marketing of pigs for slaughter. While pork production can be managed at different levels (animal, pen, section, or herd), it is beneficial to consider the herd level when determining the optimal marketing policy due to inter-dependencies, such as those created by fixed transportation costs and cross-level constraints. In this paper, we consider sequential marketing decisions at herd level. A high-dimensional infinite horizon Markov decision process (MDP) is formulated which, due to the curse of dimensionality, cannot be solved using standard MDP optimization techniques. Instead, approximate dynamic programming (ADP) is applied to solve the model and find the best marketing policy at herd level. Under the total expected discounted reward criterion, the proposed ADP approach is first compared with a standard solution algorithm for solving an MDP at pen level to show the accuracy of the solution procedure. Next, numerical experiments at herd level are given to confirm how the marketing policy adapts itself to varying costs (e.g., transportation cost) and cross-level constraints. Finally, a sensitivity analysis for some parameters in the model is conducted and the marketing policy found by ADP is compared with other well-known marketing polices, often applied at herd level. (C) 2019 Elsevier B.V. All rights reserved.

关键词： OR in agriculture Approximate dynamic programming Markov decision process Herd management stochastic dynamic programming

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Shared Steering Torque Control for Lane Change Assistance: A stochastic Game-Theoretic Approach

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2019年第4期66卷 3093-3105页

作者： Ji, Xuewu Yang, Kaiming Na, Xiaoxiang Lv, Chen Liu, Yahui Tsinghua Univ State Key Lab Automot Safety & Energy Beijing 100084 Peoples R China Univ Cambridge Dept Engn Cambridge CB2 1PZ England Nanyang Technol Univ Sch Mech & Aerosp Engn Singapore 639798 Singapore Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore

The challenging issue of "human-machine copilot" opens up a new frontier to enhancing driving safety. However, driver-machine conflicts and uncertain driver/external disturbances are significant problems in cooperative steering systems, which degrade the system's path-tracking ability and reduce driving safety. This paper proposes a novel stochastic game-based shared control framework to model the steering torque interaction between the driver and the intelligent electric power steering (IEPS) system. A six-order driver-vehicle dynamic system, including driver/external uncertainty, is established for path-tracking. Then, the affine linear-quadratic-based path-tracking problem is proposed to model the maneuvers of the driver and IEPS. Particularly, the feedback Nash and Stackelberg frameworks to the affine-quadratic problem are derived by stochastic dynamic programming. Two cases of copilot lane change driving scenarios are studied via computer simulation. The intrinsic relation between the stochastic Nash and Stackelberg strategies is investigated based on the results. And the steering-in-the-loop experiment reveals the potential of the proposed shared control framework in handling driver-IEPS conflicts and uncertain driver/external turbulence. Finally, the copiloting experiments with a human driver further demonstrate the rationality of the game-based pattern between both the agents.

关键词： Affine-quadratic game driver-machine conflicting shared steering control stochastic dynamic programming

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A scenario simulation approach for market power analysis in hydrothermal systems

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IEEE TRANSACTIONS ON POWER SYSTEMS 2003年第3期18卷 1046-1053页

作者： Vargas, LS Rodrigo, PB Oscar, MA Rigoberto, TA Univ Chile Dept Ingn Elect Santiago 2007 Chile

This paper focuses on markets based on physical bilateral contracts combined with a power exchange (PX). The main feature to be analyzed is the behavior of the hydrothermal system where one or more companies have a big reservoir with capacity for inter annual regulation. In this work, inter annual regulation means the ability of a reservoir to allocate water from consecutive years. The use of the reservoirs in a context of a power exchange market with competition is the main objective of this study. Results on the Chilean Central Interconnected System using stochastic dynamic programming are presented and discussed.

关键词： bilateral contracts hydrothermal systems market power power exchange stochastic dynamic programming

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Optimal dynamic pricing of mobile data plans in wireless communications

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OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE 2017年 66卷 91-105页

作者： Ma, Xiaoyu Deng, Tianhu Xue, Mengying Shen, Zuo-Jun Max Lan, Boxiong Beijing Foreign Studies Univ Int Business Sch Beijing 100089 Peoples R China Tsinghua Univ Dept Ind Engn Beijing 100084 Peoples R China Univ Calif Berkeley Dept Ind Engn & Operat Res Berkeley CA 94720 USA Tsinghua Univ Sch Econ & Management Beijing 100084 Peoples R China Univ Calif Berkeley Dept Civil & Environm Engn Berkeley CA 94720 USA

With smartphones sweeping the world, customers use much more data service than voice service nowadays. Because mobile data service occupies much more network capacity than voice, wireless network is frequently congested. We build a dynamic cell phone plan control model where the service provider can decide a subset of plans to open at the beginning of each period. New customers can only subscribe open plans. The dynamic plan control problem is a stochastic programming problem where the system state dimension is exponential in the number of plans and periods. In this paper, we analyze the case when the number of customers approaches positive infinity. In this limiting case, we transform the stochastic dynamic programming problem to an equivalent integer linear programming problem. In a case study, we analyze a large mobile service provider in Asia using 10,000 real individual-level data. Sensitivity analysis implies that a mobile service provider whose initial market share is low can benefit more from the dynamic data plan control. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： dynamic plan control Mobile data plans Congestion effect stochastic dynamic programming

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Action-timing problem with sequential Bayesian belief revision process

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 1998年第1期105卷 118-129页

作者： Ahn, JH Kim, JJ AT&T Bell Labs Murray Hill NJ 07974 USA CUNY Hunter Coll New York NY 10021 USA

We consider the problem of deciding the beat action time when observations are made sequentially. Specifically we address a special type of optimal stopping problem where observations are made from state-contingent distributions and there exists uncertainty on the state. In this paper, the decision-maker's belief on state is revised sequentially based on the previous observations. By using the independence property of the observations from a given distribution, the sequential Bayesian belief revision process is represented as a simple recursive form. The methodology developed in this paper provides a new theoretical framework for addressing the uncertainty on state in the action-timing problem context. By conducting a simulation analysis, we demonstrate the value of applying Bayesian strategy which uses sequential belief revision process. In addition, we evaluate the value of perfect information to gain more insight on the effects of using Bayesian strategy in the problem. (C) 1998 Elsevier Science B.V.

关键词： decision theory stochastic dynamic programming Bayesian analysis action-timing problem simulation

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