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MONOTONE POLICIES AND INDEXABILITY FOR BIDIRECTIONAL RESTLESS BANDITS

ADVANCES IN APPLIED PROBABILITY 2013年第1期45卷 51-85页

作者： Glazebrook, K. D. Hodge, D. J. Kirkbride, C. Univ Lancaster Dept Management Sci Lancaster LA1 4YX England Univ Nottingham Sch Math Sci Nottingham NG7 2RD England

Motivated by a wide range of applications, we consider a development of Whittle's restless bandit model in which project activation requires a state-dependent amount of a key resource, which is assumed to be available at a constant rate. As many projects may be activated at each decision epoch as resource availability allows. We seek a policy for project activation within resource constraints which minimises an aggregate cost rate for the system. Project indices derived from a Lagrangian relaxation of the original problem exist provided the structural requirement of indexability is met. Verification of this property and derivation of the related indices is greatly simplified when the solution of the Lagrangian relaxation has a state monotone structure for each constituent project. We demonstrate that this is indeed the case for a wide range of bidirectional projects in which the project state tends to move in a different direction when it is activated from that in which it moves when passive. This is natural in many application domains in which activation of a project ameliorates its condition, which otherwise tends to deteriorate or deplete. In some cases the state monotonicity required is related to the structure of state transitions, while in others it is also related to the nature of costs. Two numerical studies demonstrate the value of the ideas for the construction of policies for dynamic resource allocation, most especially in contexts which involve a large number of projects.

关键词： Asset management Gittins index indexability inventory management Lagrangian relaxation machine maintenance monotone policy stochastic dynamic programming restless bandit Whittle index

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An optimization framework for addressing aquatic invasive species

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ECOLOGICAL ECONOMICS 2013年 91卷 69-79页

作者： Hyytiainen, Kari Lehtiniemi, Maiju Niemi, Jarkko K. Tikka, Kimmo MTT Agrifood Res Finland Helsinki 00790 Finland Finnish Environm Inst Ctr Marine Res Helsinki 00251 Finland MTT Agrifood Res Finland Seinajoki 60320 Finland Finnish Meteorol Inst FIN-00101 Helsinki Finland

This study develops a bio-economic model framework to optimize the management of aquatic invasive species. stochastic dynamic programming is applied to investigate when and to what extent a society should engage in efforts to reduce the likelihood of an invasion, to control and eradicate a newly established population, and to adapt to damages. The framework is parameterized for a potential Asian clam (Corbicula fluminea) invasion in the warm water discharge area of a nuclear power plant planned on the northern shores of the Baltic Sea. The sensitivity analysis reveals three distinct strategies: an adaptive strategy, which reduces the damage that an existing invasive species population causes to the private sector;a preventive strategy, which delays the invasion and the resulting damage;and a mitigative strategy, which puts effort into timely detection, control and eradication of the newly established population. Choice of the optimal strategy is sensitive to the unit costs and effectiveness of the measures required, to the level of externalities and to the size of the clam population after the invasion has been detected. The results emphasize the need for the energy sector to identify and internalize the external costs of potential invasions when making any large-scale investment plans. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Ballast water treatment Bio-economic modeling Industrial biofouling Invasive alien species stochastic dynamic programming Thermal pollution

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Evaluating a multispecies adaptive management framework: must uncertainty impede effective decision-making?

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JOURNAL OF APPLIED ECOLOGY 2013年第6期50卷 1431-1440页

作者： Smith, David R. McGowan, Conor P. Daily, Jonathan P. Nichols, James D. Sweka, John A. Lyons, James E. US Geol Survey Leetown Sci Ctr Kearneysville WV 25443 USA Auburn Univ Sch Forestry & Wildlife Sci Alabama Cooperat Fish & Wildlife Res Unit Auburn AL 36849 USA US Geol Survey Patuxent Wildlife Res Ctr Laurel MD 20708 USA US Fish & Wildlife Serv Northeast Fishery Ctr Lamar PA 16848 USA US Fish & Wildlife Serv Div Migratory Bird Management Patuxent Wildlife Res Ctr Laurel MD 20708 USA

Application of adaptive management to complex natural resource systems requires careful evaluation to ensure that the process leads to improved decision-making. As part of that evaluation, adaptive policies can be compared with alternative nonadaptive management scenarios. Also, the value of reducing structural (ecological) uncertainty to achieving management objectives can be quantified. A multispecies adaptive management framework was recently adopted by the Atlantic States Marine Fisheries Commission for sustainable harvest of Delaware Bay horseshoe crabs Limulus polyphemus, while maintaining adequate stopover habitat for migrating red knots Calidris canutus rufa, the focal shorebird species. The predictive model set encompassed the structural uncertainty in the relationships between horseshoe crab spawning, red knot weight gain and red knot vital rates. stochastic dynamic programming was used to generate a state-dependent strategy for harvest decisions given that uncertainty. In this paper, we employed a management strategy evaluation approach to evaluate the performance of this adaptive management framework. Active adaptive management was used by including model weights as state variables in the optimization and reducing structural uncertainty by model weight updating. We found that the value of information for reducing structural uncertainty is expected to be low, because the uncertainty does not appear to impede effective management. Harvest policy responded to abundance levels of both species regardless of uncertainty in the specific relationship that generated those abundances. Thus, the expected horseshoe crab harvest and red knot abundance were similar when the population generating model was uncertain or known, and harvest policy was robust to structural uncertainty as specified. Synthesis and *** combination of management strategy evaluation with state-dependent strategies from stochastic dynamic programming was an informative approach to e

关键词： adaptive resource management Calidris canutus rufa expected value of information horseshoe crab Limulus polyphemus management strategy evaluation multispecies management red knot stochastic dynamic programming

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Integrated joint pest management strategies in the presence of control spillovers

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EUROPEAN REVIEW OF AGRICULTURAL ECONOMICS 2013年第5期40卷 785-805页

作者： Yigezu, Yigezu A. Alexander, Corinne E. Preckel, Paul V. Maier, Dirk E. Mason, Linda J. Woloshuk, Charles P. Lawrence, John Moog, Dale J. Int Ctr Agr Res Dry Areas Amman Jordan Purdue Univ W Lafayette IN 47907 USA Kansas State Univ Manhattan KS 66506 USA

Integrated pest management has proved cost-effective in coping with crop pests. This article identifies characteristics of pests, controls and economic incentives that may make the development of an integrated joint pest management (IJPM) strategy designed for simultaneous control of multiple pests worthwhile. We demonstrate via a case study that an IJPM strategy may add considerable value for on-farm corn storage. Critical factors for an IJPM strategy are that the pests are affected by the same environmental variables, but with different thresholds and response functions;controls for one pest impact other pests;and the pests have similar economic importance.

关键词： integrated pest management stochastic dynamic programming insect management mould management stored corn

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Optimal dynamic asset allocation strategy for ELA scheme of DC pension plan during the distribution phase

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INSURANCE MATHEMATICS & ECONOMICS 2013年第2期52卷 404-410页

作者： He, Lin Liang, Zongxia Renmin Univ China Sch Finance Beijing 100084 Peoples R China Tsinghua Univ Dept Math Sci Beijing 100084 Peoples R China

In this paper, we study the optimal dynamic asset allocation strategy for the ELA scheme of DC pension plan during the distribution phase. In an ELA scheme of DC pension plan, the assets are invested in equities and bonds, and are distributed to the plan participants by an actuarial method. The survived participant can also obtain a survival credit from the mortality risk-sharing implicit in the pension plan. The goal of the scheme is to maintain the stable purchasing power of the plan participants, i.e., to minimize the square deviations of the distribution and a predetermined level by choosing the optimal dynamic asset allocation proportions. We formalize the problem into a continuous-time stochastic optimal control problem and establish the optimal dynamic asset allocation strategy by stochastic dynamic programming method. We obtain the optimal dynamic asset allocation proportions invested in the equities and bonds, and give an economical explanation of the key factors influencing the strategy. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Defined contribution pension plan Equity-linked annuity (ELA) scheme Optimal dynamic asset allocation stochastic dynamic programming HJB equations

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Valuing flexible operating strategies in nickel production under uncertainty 20

Valuing flexible operating strategies in nickel production u...

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20th International Congress on Modelling and Simulation (MODSIM)

作者： Bao, C. Mortazavi-Naeini, M. Northey, S. Tarnopolskaya, T. Monch, A. Zhu, Z. CSIRO Computat Informat Minerals Flagship Melbourne Vic Australia CSIRO Proc Sci & Engn Minerals Flagship Melbourne Vic Australia

ISBN: (纸本)9780987214331

With increasing global demand for nickel (which is a key component of stainless steel) the focus of mineral industry is currently on the abundant low-grade nickel laterite reserves. The extraction of nickel from the low-grade laterites is a technically difficult and expensive process and, as a result, the profitability of nickel production projects is highly affected by uncertainty over future market conditions. The project value can be increased by utilizing flexible operating strategies in response to changing future market conditions and Real Options analysis provides a suitable tool for optimizing flexible operating strategies over a long planning horizon in the face of uncertainty. This paper presents the first study on the valuation of flexible operating strategies in a realistic nickel laterite production system under uncertainty of nickel price and exchange rate. In this paper, the production of ore from the three hypothetical nickel laterite mines being fed to a central processing facility is studied. The common features of nickel laterite production, such as a two-fraction (limonite and saprolite) structure of the laterite ore body, layering of each fraction, with different ore grades (concentration of nickel) in each layer, and a simultaneous mining of several ore bodies, are incorporated into the model. It is common in the minerals industry that the ore from each mine is blended to provide as constant a feed rate and grade as possible to the processing facility. However, such a constant feed strategy may not generate the best financial return. In this paper, we investigate whether higher returns can be achieved by adopting a flexible strategy of switching, at prescribed intervals of time, between different feed rates of ore from the three mines that have different quality of nickel laterite. Such flexible strategy allows the operator to change the production rate of nickel in response to changing projected market conditions. In this paper, we use an appr

关键词： Real options stochastic dynamic programming Least Squares Monte Carlo (LSM) nickel laterite multiple mine-site operation genetic algorithm

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Upper and lower bounds for convex value functions of derivative contracts

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ECONOMIC MODELLING 2013年 34卷 69-75页

作者： Ben-Ameur, Hatem de Frutos, Javier Fakhfakh, Tarek Diaby, Vacaba HEC Montreal Montreal PQ Canada Univ Valladolid Inst Math IMUVA E-47002 Valladolid Spain FSEG Sfax Sfax Tunisia ISG Tunis Tunis Tunisia

The aim of this paper is to compute upper and lower bounds for convex value functions of derivative contracts. Laprise et al. (2006) compute bounds for American-style vanilla options by selected portfolios of call options. We provide an alternative interpretation of their numerical procedure as a stochastic dynamic program for which the Bellman value function is approximated by selected piecewise linear interpolations at each decision date. The stochastic dynamic program does not (directly) depend on portfolios of call options, but rather on a key ingredient: some transition parameters of the underlying asset. More in line with the literature on dynamic programming, our procedure is contract free and is well designed to accommodate all one-dimensional convex value functions of derivative contracts. In support of this, we revisit the numerical investigation of Laprise et al. (2006) and enlarge their findings to include options embedded in bonds under affine term-structure models of interest rates. (C) 2012 Elsevier B.V. All rights reserved.

关键词： American options Derivative contracts Convex functions Upper and lower bounds stochastic dynamic programming Piecewise linear interpolations

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KALMAN-LIKE STATE TRACKING AND CONTROL IN POMDPS WITH APPLICATIONS TO BODY SENSING NETWORKS

KALMAN-LIKE STATE TRACKING AND CONTROL IN POMDPS WITH APPLIC...

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IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Zois, Daphney-Stavroula Levorato, Marco Mitra, Urbashi Univ So Calif Ming Hsieh Dept Elect Enginering Los Angeles CA 90089 USA

ISBN: (纸本)9781479903566

In this paper, the problem of state tracking with controlled observations is considered for a system modeled by a discrete-time, finite-state Markov chain. The system state is 'hidden' and observed via conditionally Gaussian measurements that are shaped by the underlying state and an exogenous control input. Following an innovations approach, a Kalman-like 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 for a partially observable Markov Decision Process (POMDP). The optimal solution is determined via stochastic dynamic programming. Numerical results are presented for the application of physical activity detection in heterogeneous, wireless body area networks.

关键词： Markov models approximate MMSE POMDP stochastic dynamic programming innovations approach

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OPTIMAL ALLOCATION OF INVENTORY AND DEMAND FOR MANAGING SUPPLY CHAIN REVENUES

OPTIMAL ALLOCATION OF INVENTORY AND DEMAND FOR MANAGING SUPP...

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作者： ABHILASHA KATARIYA Texas A&M University

学位级别：博士

This dissertation focuses on three distinct yet related problems that are motivated by practices of electronics manufacturers, who satisfy stochastic demand from multiple markets and multisource parts from several suppliers. The first problem investigates joint replenish- ment and allocation decisions for a supplier who satisfies stochastic demand from a primary market and a spot market. We formulate the problem as a multi-period stochastic dynamic program and show that the optimal policy is characterized by two quantities: the critical produce-up-to level and the critical retain-up-to level. We establish bounds for these two quantities, discuss their economic interpretation, and use them to construct a new and effec- tive heuristic policy. We identify two practical benchmark policies and establish thresholds on the unit revenue earned from the spot market such that one of the two benchmark poli- cies is optimal. Using a computational study, we quantify the benefits of the optimal policy relative to the benchmark policies and examine the effects of demand correlation. The second problem investigates an important extension where a supplier faces stochas- tic demand from Class 1 along with price-sensitive stochastic demand from Class 2. We investigate the supplier's joint replenishment, allocation and pricing problem by formulating it as a multi-period, two-stage stochastic dynamic program. We show that a dynamic pricing policy is optimal at stage 2, and the stage 1 optimal policy is characterized by two quan- tities: the critical produce-up-to level and the critical amount of inventory to be protected from Class 1. In contrast to the optimal policy, myopic policies are less costly to evaluate, and hence, are more practical. We establish two sufficient conditions under which a myopic joint inventory and pricing policy is optimal. Using a computational study, we show that the benefits of dynamic pricing to Class 2 are higher than the benefits of discretionary sales to

关键词： Inventory/production systems production capacity spot market stochastic dynamic programming dynamic pricing myopic policies replenishment inventory allocation demand allocation bullwhip effect cyclic consumption policy multi-sourcing multiple

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Balancing learning and economies of scale for adaptive clinical trials

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OPERATIONS RESEARCH FOR HEALTH CARE 2013年第3期2卷 42-51页

作者： Fleischhacker, Adam J. Zhao, Yao Univ Delaware Dept Business Adm Newark DE 19716 USA State Univ New Jersey Rutgers Univ Dept Supply Chain Management & Mkt Sci Newark NJ 07102 USA

Prior to the start of an adaptive clinical trial, demand for an investigational drug can be highly uncertain. Treatment length, recommended dosages, and forecasted patient recruitment can fluctuate in response to early trial results. While initial demand forecasts can be very wrong, the factors influencing future demand can be learned during the trial. To take advantage of this learning, intra-trial production and/or packaging can be leveraged, but this is done at the expense of scale economies. In this paper, we study the balance between learning and economies of scale for adaptive clinical trials. We characterize the optimal production (or packaging) decisions and through analytical and numerical studies, we develop insights on the impact of fixed costs, learning rates in terms of forecasting future demand, inventory overage costs, and inventory underage costs on the value of having intra-trial flexibility and on decisions regarding quantity and timing of drug supply. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Clinical trial supply stochastic dynamic programming Production planning

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