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stochastic wafer fabrication scheduling

IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING 2003年第1期16卷 2-14页

作者： Shen, YX Leachman, RC Agilent Technol Inc Semicond Prod Grp Ft Collins CO 80525 USA Univ Calif Berkeley Dept Ind Engn & Operat Res Berkeley CA 94720 USA

To meet the challenge of integrating uncertainty analysis into wafer fabrication scheduling, this paper proposes a stochastic dynamic programming model for scheduling new releases and bottleneck processing by stage. Based on the paradigm of stochastic linear quadratic control (SLQ), the lab scheduling model incorporates considerable analysis of uncertainties in yields and demands. The SLQ scheduling model explicitly captures the reentrant flow structure characteristic of wafer fabrication. Moreover, the SLQ scheduling model removes a major weakness in applying dynamic programming to production control by accommodating noninteger values for lead times Embedded in the SLQ scheduling model is what the authors term a degree-2 yield distribution that subsumes most popular yield distributions in the literature. As long as the underlying system dynamics behave in a degree-2 fashion, the corresponding optimal scheduling policy turns out to he a linear control rule that is easy to compute and implement. Industrial data are used to test the effectiveness and robustness of the SLQ machinery versus the LP rolling horizon and pull heuristic methodologies. Encouraging results and valuable insights are obtained from extensive numerical experiments that show promise for successfully managing uncertainties surrounding fab scheduling.

关键词： fab scheduling linear quadratic control stochastic dynamic programming uncertainty analysis

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Application of Markov renewal theory andsemi-Markovdecision processes in maintenance modeling and optimization of multi-unit systems

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NAVAL RESEARCH LOGISTICS 2020年第7期67卷 548-558页

作者： Salari, Nooshin Makis, Viliam Univ Toronto Mech & Ind Engn Toronto ON Canada

In this paper, a condition-based maintenance model for a multi-unit production system is proposed and analyzed using Markov renewal theory. The units of the system are subject to gradual deterioration, and the gradual deterioration process of each unit is described by a three-state continuous time homogeneous Markov chain with two working states and a failure state. The production rate of the system is influenced by the deterioration process and the demand is constant. The states of the units are observable through regular inspections and the decision to perform maintenance depends on the number of units in each state. The objective is to obtain the steady-state characteristics and the formula for the long-run average cost for the controlled system. The optimal policy is obtained using a dynamic programming algorithm. The result is validated using a semi-Markov decision process formulation and the policy iteration algorithm. Moreover, an analytical expression is obtained for the calculation of the mean time to initiate maintenance using the first passage time theory.

关键词： maintenance Markov renewal theory multi-unit system stochastic dynamic programming

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Approximate solutions and cost error bounds for quantity flexibility replenishment

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2017年 193卷 306-315页

作者： Zhu, Stuart X. Univ Groningen Fac Econ & Business Dept Operat Nettelbosje 2 NL-9747 AE Groningen Netherlands

Under an environment with quantity flexibility replenishment, we explore the approximate solutions to determine ordering quantities when the demand is correlated with dynamic forecast updating. Moreover, we show the optimality of the myopic policy. We further develop the corresponding cost error bounds to evaluate the performance of the approximate solutions. Extensive numerical experiments demonstrate that our approximate solution can achieve a lower cost performance compared with other bounds.

关键词： Approximation Bounds Quantity flexibility stochastic dynamic programming

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Optimal liquidation of foreign currencies when FX rates follow a generalised Ornstein-Uhlenbeck process

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APPLIED INTELLIGENCE 2023年第2期53卷 1391-1404页

作者： Li, Linwei Matt, Paul-Amaury Heumann, Christian Univ Munich LMU Dept Stat Ludwigstr 33 D-80539 Munich Germany Daimler AG Breitwiesenstr 5 D-70565 Stuttgart Germany

In this article, we consider the case of a multinational company realizing profits in a country other than its base country. The currencies used in the base and foreign countries are referred to as the domestic and foreign currencies respectively. For its quarterly and yearly financial statements, the company transfers its profits from a foreign bank account to a domestic bank account. Thus, the foreign currency liquidation task consists formally in exchanging over a period T a volume V of cash in the foreign currency f for a maximum volume of cash in the domestic currency d. The foreign exchange (FX) rate that prevails at time t is denoted X-d/f(t) and is defined as the worth of one unit of currency d in the currency f. We assume in this article that the natural logarithm of the FX rate x(t) = log X-d/f (t) follows a discrete generalized Ornstein-Uhlenbeck (OU) process, a process which generalizes the Brownian motion and mean-reverting processes. We also assume minimum and maximum volume constraints on each transaction. Foreign currency liquidation exposes the multinational company to financial risks and can have a significant impact on its final revenues, since FX rates are hard to predict and often quite volatile. We introduce a Reinforcement Learning (RL) framework for finding the liquidation strategy that maximizes the expected total revenue in the domestic currency. Despite the huge success of Deep Reinforcement Learning (DRL) in various domains in the recent past, existing DRL algorithms perform sub-optimally in this task and the stochastic dynamic programming (SDP) algorithm - which yields the optimal strategy in the case of discrete state and action spaces - is rather slow. Thus, we propose here a novel algorithm that addresses both issues. Using SDP, we first determine numerically the optimal solution in the case where the state and decision variables are discrete. We analyse the structure of the computed solution and derive an analytical formula for the o

关键词： Liquidation Foreign exchange rates stochastic process Reinforcement learning stochastic dynamic programming

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Fast Path Planning for Unmanned Aerial Vehicles by Self-Correction Based on Q-Learning

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JOURNAL OF AEROSPACE INFORMATION SYSTEMS 2021年第4期18卷 203-211页

作者： Wang, Ziyang Yang, Hongbing Wu, Qingsong Zheng, Jiafei Soochow Univ Sch Mech & Elect Engn Suzhou 215006 Jiangsu Peoples R China

This paper addresses a path planning problem for unmanned aerial vehicles with correcting position errors through correction-point navigation, which requires a rapid response when determining the flight path. A two-layer nested iterative hybrid algorithm based on Q learning is proposed to achieve multiobjective optimization by minimizing path lengths and correction times while reducing the complexity of the algorithm and improving the efficiency of path planning. The lower-layer algorithm uses a Q-learning framework based on the experience playback mechanism and exploration/exploitation mechanism. The rewards and punishments for the Q-table values in the lower-layer algorithm are innovatively managed with the unit "path." The upper-layer algorithm is based on the Pareto multiobjective algorithm. The Pareto frontier is continuously updated with the solutions from the lower-layer algorithm, which timely provides the lower-layer algorithm feedback. Finally, simulation experiments are conducted to evaluate the effectiveness of the algorithm, and the results show that the proposed algorithm outperforms particle swarm optimization.

关键词： Path Planning UAV Particle Swarm Optimization Pareto Frontier Reinforcement Learning stochastic dynamic programming Optimization Algorithm Computing Performance Mathematical Models Genetic Algorithm

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Supply chain operations in the presence of a spot market:: a review with discussion

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JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 2007年第11期58卷 1412-1429页

作者： Haksoz, C. Seshadri, S. City Univ London CASS Business Sch Fac Management London EC1Y 8TZ England NYU New York NY USA

We survey the recent literature on the use of spot market operations to manage procurement in supply chains. We present results in two categories: work that deals with optimal procurement strategies and work related to the valuation of procurement contracts. As an example of the latter, we provide new results on valuation of a supply contract with abandonment option. Based on our review, we also discuss the scope for doing further work.

关键词： supply chain contracts stochastic dynamic programming risk real options practice of OR

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Control strategy optimization of plug-in hybrid electric vehicle based on driving data mining

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING 2023年第2-3期237卷 333-346页

作者： Wang, Pengyu Pan, Chunyan Sun, Tianjun Jilin Univ State Key Lab Automot Simulat & Control Renmin Rd 5988 Changchun 130012 Peoples R China Jilin Univ Coll Automot Engn Changchun Peoples R China

SDP (stochastic dynamic programming) control strategy can mine the travel data of drivers, so that the energy-saving potential of vehicles could be improved. However, there are two problems need to be solved in the current SDP: firstly, the analysis and construction method of driver's typical driving cycle is not clear;secondly, the adaptability of SDP algorithm to a typical driving cycle is insufficient. To solve the above problems, a driving cycle construction method for off-line SDP solution is proposed, which is based on "analysis, dimension reduction and clustering" process. In addition, a coupled control strategy (ECMS-SDP) based on driving conditions identification is developed. Because it is difficult to predict the driving conditions in real time, the working part of the coupled control strategy is calculated by the method of improved random forest. The simulation results show that ECMS-SDP control strategy can save 8%-15% fuel on average compared with CD-CS control strategy, and can save 4%-7% fuel on average compared with ECMS control strategy. The results prove that the ECMS-SDP coupled control strategy can respond well to the changing driving environment, and the fuel economy of vehicles is enhanced.

关键词： PHEV random forest driving data mining stochastic dynamic programming coupled control strategy

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Suitability of short or long conservation contracts under ecological and socio-economic uncertainty

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ECOLOGICAL MODELLING 2011年第15期222卷 2856-2866页

作者： Lennox, Gareth D. Armsworth, Paul R. Univ Sheffield Dept Anim & Plant Sci Sheffield S10 2TN S Yorkshire England Univ Tennessee Dept Ecol & Evolutionary Biol Knoxville TN USA

Acquisition of land rights has become a primary tool used to protect terrestrial biodiversity. Fixed length contracts are often used when trying to secure conservation benefits on private land in agri-environment schemes and payment for environmental services schemes, but the duration of the conservation contracts used in different programmes varies. To date, very little research has been undertaken to determine the situations in which contracts of differing lengths are optimal or when conservation agencies or groups should use a portfolio of different contract lengths rather than relying on a single type. Using stochastic dynamic programming and related heuristic methods, we investigate how the choice between short or long conservation contracts is affected by uncertainty regarding the future availability of sites and their ecological condition. We also examine the benefits offered by using a portfolio of different contract lengths. Conservation agencies must pay private landowners a premium to secure longer agreements and because of this, shorter contracts are advantageous if sites are likely to remain available for conservation in the future. Long contracts are preferred when future site availability becomes more unlikely. In contrast to uncertainty over site availability, uncertainty over future ecological conditions has little effect on contract selection and only markedly influences the choice between short and long contracts when there is heterogeneity across sites in expected conservation outcomes and future availability of sites is also uncertain. Finally, when future site availability is unlikely, the use of a portfolio of short and long contracts would offer greater conservation gains than using either type in isolation, even though this option is not yet one that is commonly found in conservation practice. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Conservation contract stochastic dynamic programming Private land Site selection Agri-environment scheme Payment for environmental services

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Monotone Optimal Threshold Feedback Policy for Sequential Weapon Target Assignment

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JOURNAL OF AEROSPACE INFORMATION SYSTEMS 2017年第1期14卷 68-72页

作者： Kalyanam, Krishnamoorthy Casbeer, David Pachter, Meir Infoscitex Corp Dayton OH 45431 USA US Air Force Res Lab Autonomous Control Branch Wright Patterson AFB OH 45433 USA US Air Force Inst Technol Wright Patterson AFB OH 45433 USA

THE operational scenario is the following. Abomber with identical weapons travels along a designated route/path and sequentially encounters enemy ( ground) targets. Should the bomber decide to engage a target, the target will be destroyed with a probability of p < 1. Upon successful elimination, the bomber receives a positive reward r drawn from a fixed known distribution. We stipulate that, before engagement, the bomber observes the target and is made aware of the reward r. Furthermore, upon releasing a weapon, the bomber is alerted as to whether or not the deployed weapon was successful. In other words, we employ a shoot-look-shoot policy. If the target is destroyed, the bomber moves on to the next target. On the other hand, if the target was not destroyed, the bomber can either reengage the current target or move on to the next target in the sequence. The optimal closed-loop control policy that results in the maximal expected cumulative reward is obtained via stochastic dynamic programming. Not surprisingly, a weapon is dropped on a target if, and only if, the observed reward is no less than a stage- and state-dependent threshold value. We show that the threshold value, as a function, is monotonic decreasing in the number of weapons and monotonic nondecreasing in the number of targets left to be engaged.

关键词： Weapon Target Assignment stochastic dynamic programming Closed Loop Control Missile Defense

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Assessing opportunity and relocation costs of marine protected areas using a behavioural model of longline fleet dynamics

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FISH AND FISHERIES 2012年第2期13卷 139-157页

作者： Dowling, Natalie A. Wilcox, Chris Mangel, Marc Pascoe, Sean CSIRO Marine & Atmospher Res Pelag Fisheries & Ecosyst Hobart Tas 7000 Australia Univ Calif Santa Cruz Dept Appl Math & Stat MS E 2 Ctr Stock Assessment Res Santa Cruz CA 95064 USA CSIRO Marine & Atmospher Res Ecosci Precinct Dutton Pk Qld 4102 Australia Univ Bergen Dept Biol Bergen Norway

Increasing use of spatial management tools in fisheries requires an understanding of fleet response, and in particular to where displaced fishing effort is likely to move. We develop a state-dependent decision-making model to address the spatial allocation of effort in an Australian tuna longline fishery. We assume that fishers have an economic objective in deciding where to fish, but that decisions in any period are also influenced by the remaining quota held at the time of the decision. Key features of the model include endogenous price dynamics, a moving stock and a competitive pool of different vessel types operating from different port locations. We utilize this model to illustrate fleet responses to marine reserves and limits on fishing effort. The results illustrate that the model framework provides advantages over statistically based models in that decisions made in response to the imposition of a reserve are not consistent with a proportional reallocation of effort. Rather, the stochastic dynamic model yielded an overall profit level of similar to 4% higher relative to scenarios with no reserve. Incorporating the opportunity cost of a quota into the model resulted in an optimal utilization of effort, in which effort was concentrated in time periods and locations yielding maximized profit. Under a low level of effort relative to the season length, the model indicated an overall profit level 43% greater than the highest obtained when the same level of effort was applied solely within any given quarter of the season.

关键词： Fishery fleet dynamics location choice model spatial fisheries management state-dependent model stochastic dynamic programming tuna longline fishery

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