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Conference on Performance Evaluation 2010

作者： Ayesta, Urtzi Erausqum, Martin Jacko, Peter BCAM Bilbao 48170 Spain IKERBASQUE Basque Fdn Sci Bilbao 48011 Spain Univ Basque Country UPV EHU Bilbao Spain

We introduce a comprehensive modeling framework for the problem of scheduling a finite number of finite-length jobs where the available service rate is time-varying The main motivation comes from wireless data networks where the service rate of each user varies randomly due to fading We employ recent advances on the restless bandit problem that allow us to obtain an opportunistic scheduling rule for the system without arrivals When the objective is to minimize the mean number of users in the system or to minimize the mean waiting time, we obtain a priority-based policy which we call the Potential Improvement (PI) rule, since the priority index equals the ratio between the current available service rate and the expected potential improvement of the service rate We also show that for certain objective functions the index rule takes the form of known opportunistic scheduling rules like Relatively Best (RB) or Proportionally Best" (PB) Thus our model provides a formal justification for the deployment of opportunistic scheduling rules in order to improve the flow-level performance in the presence of time-varying capacities We further analyze the performance of the PI rule in the presence of randomly arriving users When the service rates are constant PI is equivalent to the c mu-rule which is known to be optimal with any distribution of arrivals Using a recent characterization for the stability region of flow-level scheduling rules under random arrivals we show that PI achieves the maximum stability region We perform numerical experiments in a wide range of scenarios and compare the performance of PI with other popular disciplines like RB PB Score-Based (SB) and the c mu-rule Our results show that RB PB SB or the c mu-rule might outperform the others depending on the scenario, but regardless of this the performance of PI is always superior or equivalent to the best of these opportunistic rules (C) 2010 Elsevier B V All rights reserved

关键词： Multi-armed restless bandit problem Markov Decision Process stochastic dynamic programming Opportunistic scheduling Optimal scheduling c mu-rule Index policy

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Approximate dynamic programming approach for process control

Approximate dynamic programming approach for process control

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IFAC Symposium on Advanced Control of Chemical Processes (ADCHEM)

作者： Lee, Jay H. Wong, Weechin Georgia Inst Technol Sch Chem & Biomol Engn Atlanta GA 30332 USA

We assess the potentials of the approximate dynamic programming (ADP) approach for process control, especially as a method to complement the model predictive control (MPC) approach. In the artificial intelligence (AI) and operations research (OR) research communities, ADP has recently seen significant activities as an effective method for solving Markov decision processes (MDPs), which represent a type of multi-stage decision problems under uncertainty. Process control problems are similar to MDPs with the key difference being the continuous state and action spaces as opposed to discrete ones. In addition, unlike in other popular ADP application areas like robotics or games, in process control applications first and foremost concern should be on the safety and economics of the on-going operation rather than on efficient learning. We explore different options within ADP design, such as the pre-decision state vs. post-decision state value function, parametric vs. nonparametric value function approximator, batch-mode vs. continuous-mode learning, and exploration vs. robustness. We argue that ADP possesses great potentials, especially for obtaining effective control policies for stochastic constrained nonlinear or linear systems and continually improving them towards optimality. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： stochastic process control stochastic dynamic programming Approximate dynamic programming Dual control Constrained control

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Optimal production control under uncertainty with revenue management considerations

Optimal production control under uncertainty with revenue ma...

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作者： Ceryan, Oben University of Michigan

学位级别：Ph.D.

This dissertation consists of three essays on supply chain and revenue management. Its main focus is the integration of dynamic production and demand management decisions for multiple products facing uncertain demand. The study considers three problem settings to inquire into flexibility's influence on a dynamic pricing strategy, managing exogenous demand for intermediary products, and allocation of shared resources among multiple products in a make-to-order environment. The first chapter studies a joint mechanism of dynamic pricing and capacity flexibility to mitigate demand and supply mismatches. We consider a firm producing two substitutable products with price-correlated demands utilizing capacitated product-dedicated and flexible resources. We characterize the structure and sensitivity of the optimal production and pricing decisions and find that the existence of a flexible resource in the firm's capacity portfolio helps maintain stable price differences across items over time. This result has favorable ramifications from a marketing standpoint as it suggests that even when a firm applies a dynamic pricing strategy, it may still establish consistent price positioning among multiple products if it can employ a flexible replenishment resource. We also investigate the economic benefits of a joint strategy versus applying each tool individually. The second chapter considers a setting where a single end-product is assembled from many intermediate components with external demand for the intermediate products as well as the end-product. We address the questions on how to decide on the production quantities for each component, when to initiate an assembly operation and how to set admission rules for demands targeted at various products. In addition to providing structural results for the optimal policy and its sensitivity to product revenues, we also extend the model to multiple customer classes and to settings with partial revenue collecting schemes. We propose a nove

关键词： dynamic Pricing Production Control stochastic dynamic programming Revenue Management Supply Chain Management Assemble-to-Order Systems Thesis

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Incorporating drivability metrics into optimal energy management strategies for hybrid vehicles

Incorporating drivability metrics into optimal energy manage...

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作者： Opila, Daniel F. University of Michigan

学位级别：Ph.D.

Hybrid Vehicle fuel economy performance is highly sensitive to the "Energy Management" strategy used to regulate power flow among the various energy sources and sinks. Optimal solutions are easy to specify if the drive cycle is known a priori. It is very challenging to compute controllers that yield good fuel economy for a class of drive cycles representative of typical driver behavior. Additional challenges come in the form of constraints on powertrain activity, like shifting and starting the engine, which are commonly called "drivability" metrics. These constraints can adversely affect fuel economy. In this dissertation, drivability restrictions are included in a Shortest Path stochastic dynamic programming (SPSDP) formulation of the energy management problem to directly address this tradeoff and generate optimal, causal controllers. The controllers are evaluated on Ford Motor Company's highly accurate proprietary vehicle model and compared to a controller developed by Ford for a prototype vehicle. The SPSDP-based controllers improve fuel economy more than 15% compared to the industrial controller on government test cycles. In addition, the SPSDP-based controllers can directly quantify tradeoffs between fuel economy and drivability. Hundreds of thousands of simulations are conducted using real-world drive cycles to evaluate performance and robustness in the real world, demonstrating 10% improvement compared to the baseline. Finally, the controllers are tested in a real vehicle.

关键词： Hybrid Vehicles stochastic dynamic programming dynamic programming Optimal Control Energy Management HEV Thesis

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Terrain and Traffic Optimized Vehicle Speed Control

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IFAC Proceedings Volumes 2010年第7期43卷 378-383页

作者： Ilya V. Kolmanovsky Dimitar P. Filev Dept. Of Aerospace Engineering The University of Michigan Ann Arbor MI USA (Tel: 734-615-9655 Ford Research and Advanced Engineering Dearborn MI USA

The paper considers optimal control of vehicle speed when the vehicle is driven in a particular geographic region with specific terrain and traffic patterns. The vehicle route is assumed to be unknown in advance. The properties of the terrain and traffic flow are modeled stochastically. A method is proposed for constructing a control policy off-line to optimally prescribe vehicle speed set-point as a function of current driving conditions, for best on average fuel economy and travel speed performance. A related method is proposed to evaluate expected average fuel economy and travel speed performance of sub-optimal control policies, such as the policies which use constant speed offset relative to average traffic speed. The optimal control law which prescribes vehicle speed set-point can be deployed in advanced vehicle cruise control systems or incorporated into a driver advisory function. In addition, the value function of optimal or suboptimal control policies may be used as a terminal cost in a receding horizon optimization of vehicle speed over routes with known initial segments, or for fuel efficient vehicle routing.

关键词： Automotive control vehicle speed control adaptive cruise control stochastic control stochastic dynamic programming optimal control fuel economy vehicle routing

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Selection of contract suppliers under price and demand uncertainty in a dynamic market

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2009年第3期198卷 830-847页

作者： Li, Shanling Murat, Alper Huang, Wanzhen Wayne State Univ Dept Ind & Mfg Engn Detroit MI 48202 USA McGill Univ Fac Management Montreal PQ H3A 1G5 Canada Lakehead Univ Dept Math Sci Thunder Bay ON P7B 5E1 Canada

In this paper, we consider a supply contracting problem in which the buyer firm faces non-stationary stochastic price and demand. First, we derive analytical results to compare two pure strategies: (i) periodically purchasing from the spot market;and (ii) signing a long-term contract with a single supplier. The results from the pure strategies show that the selection of suppliers can be complicated by many parameters, and is particularly affected by price uncertainty. We then develop a stochastic dynamic programming model to incorporate mixed strategies, purchasing commitments and contract cancellations. Computational results show that increases in price (demand) uncertainty favor long-term (short-term) suppliers. By examining the two-way interactions of contract factors (price, demand, purchasing bounds, learning and technology effect, salvage values and contract cancellation), both intuitive and non-intuitive managerial insights in outsourcing strategies are derived. (C) 2008 Published by Elsevier B.V.

关键词： Supply chain contracts stochastic dynamic programming Purchasing Supplier selection

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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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Modelling Water Blending-Sensitivity of Optimal Policies

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ENVIRONMENTAL MODELING & ASSESSMENT 2009年第6期14卷 749-757页

作者： Webby, R. B. Green, D. A. Metcalfe, A. V. Univ Adelaide Sch Math Sci Adelaide SA 5005 Australia

Water blending is modelled as a combination of a linear program and a stochastic dynamic program. Optimal policies are found for linear and integer-linear formulations using both an expected monetary value and conditional value-at-risk criterion. The sensitivity of these solutions to the discretisation over volume and over time is investigated.

关键词： Water resource allocation Linear programming stochastic dynamic programming Conditional value-at-risk

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On the structural properties of a discrete-time single product revenue management problem

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OPERATIONS RESEARCH LETTERS 2009年第4期37卷 273-279页

作者： Aydin, Seray Akcay, Yalcin Karaesmen, Fikri Koc Univ Dept Ind Engn TR-34450 Istanbul Turkey Koc Univ Coll Business Adm & Econ TR-34450 Istanbul Turkey

We consider a multi-period revenue management problem in which multiple classes of demand arrive over time for the common inventory. The demand classes are differentiated by their revenues and their arrival distributions. We investigate monotonicity properties of varying problem parameters on the optimal reward and the policy. (C) 2009 Elsevier B.V. All rights reserved.

关键词： Revenue management stochastic dynamic programming Optimal control policies

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Modeling sustainable product lifecycle decision support systems

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2009年第1期122卷 366-375页

作者： Hu, Guiping Bidanda, Bopaya Univ Pittsburgh Dept Ind Engn Pittsburgh PA 15261 USA Iowa State Univ Ames IA 50011 USA

Sustainable product lifecycle systems are attracting increasing attention because of cost competition, resource constraints and environmental issues. Short lifecycle products, such as consumer and defense electronics, are of particular concern. We formulate a product lifecycle evolution system based on stochastic dynamic programming. By applying the concept of a sustainable product lifecycle system on a product line, conclusions and guidelines for rational decision making can be developed through each phase of the product life cycle. Published by Elsevier B.V.

关键词： Sustainable product lifecycle Closed-loop supply chain Environmental regulation stochastic dynamic programming

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