David B. Brown

Journal Article Operations Research · November 1, 2023 Many stochastic dynamic programs (DPs) have a weakly coupled structure in that a set of linking constraints in each period couples an otherwise independent collection of subproblems. Two widely studied approximations of such problems are approximate linear ... Full text Cite

Dynamic Programs with Shared Resources and Signals: Dynamic Fluid Policies and Asymptotic Optimality

Journal Article Operations Research · September 1, 2022 We consider a sequential decision problem involving shared resources and signals in which a decision maker repeatedly observes some exogenous information (the signal), modeled as a finite-state Markov process, then allocates a limited amount of a shared re ... Full text Cite

Dynamic pricing of relocating resources in large networks

Journal Article Management Science · July 1, 2021 Motivated by applications in shared vehicle systems, we study dynamic pricing of resources that relocate over a network of locations. Customers with private willingness to pay sequentially request to relocate a resource from one location to another, and a ... Full text Cite

Index policies and performance bounds for dynamic selection problems

Journal Article Management Science · July 1, 2020 We consider dynamic selection problems, where a decision maker repeatedly selects a set of items from a larger collection of available items. A classic example is the dynamic assortment problem with demand learning, where a retailer chooses items to offer ... Full text Cite

Dynamic Pricing of Relocating Resources in Large Networks

Conference Performance Evaluation Review · December 17, 2019 We study dynamic pricing of resources that are distributed over a network of locations (e.g., shared vehicle systems and logistics networks). Customers with private willingness-To-pay sequentially request to relocate a resource from one location to another ... Full text Cite

Approximations to stochastic dynamic programs via information relaxation duality

Journal Article Operations Research · January 1, 2019 In the analysis of complex stochastic dynamic programs, we often seek strong theoretical guarantees on the suboptimality of heuristic policies. One technique for obtaining performance bounds is perfect information analysis: this approach provides bounds on ... Full text Cite

Static routing in stochastic scheduling: Performance guarantees and asymptotic optimality

Journal Article Operations Research · November 1, 2018 We study the problem of scheduling a set of J jobs on M machines with stochastic job processing times when no preemptions are allowed and with a weighted sum of expected completion times objective. Our model allows for “unrelated” machines: the distributio ... Full text Cite

Information relaxation bounds for infinite horizon markov decision processes

Journal Article Operations Research · September 1, 2017 We consider the information relaxation approach for calculating performance bounds for stochastic dynamic programs (DPs), following Brown et al. [Brown DB, Smith JE, Sun P (2010) Information relaxations and duality in stochastic dynamic programs. Oper. Res ... Full text Cite

Information relaxations, duality, and convex stochastic dynamic programs

Journal Article Operations Research · November 1, 2014 We consider the information relaxation approach for calculating performance bounds for stochastic dynamic programs (DPs). This approach generates performance bounds by solving problems with relaxed nonanticipativity constraints and a penalty that punishes ... Full text Cite

Optimal sequential exploration: Bandits, clairvoyants, and wildcats

Journal Article Operations Research · May 1, 2013 This paper was motivated by the problem of developing an optimal policy for exploring an oil and gas field in the North Sea. Where should we drill first? Where do we drill next? In this and many other problems, we face a trade-off between earning (e.g., dr ... Full text Cite

Aspirational preferences and their representation by risk measures

Journal Article Management Science · November 1, 2012 We consider choice over uncertain, monetary payoffs and study a general class of preferences. These preferences favor diversification, except perhaps on a subset of sufficiently disliked acts over which concentration is instead preferred. This structure en ... Full text Cite

Theory and applications of robust optimization

Journal Article SIAM Review · December 1, 2011 In this paper we survey the primary research, both theoretical and applied, in the area of robust optimization (RO). Our focus is on the computational attractiveness of RO approaches, as well as the modeling power and broad applicability of the methodology ... Full text Cite

Dynamic portfolio optimization with transaction costs: Heuristics and dual bounds

Journal Article Management Science · October 1, 2011 We consider the problem of dynamic portfolio optimization in a discrete-time, finite-horizon setting. Our general model considers risk aversion, portfolio constraints (e.g., no short positions), return predictability, and transaction costs. This problem is ... Full text Cite

Optimal portfolio liquidation with distress risk

Journal Article Management Science · November 1, 2010 We analyze the problem of an investor who needs to unwind a portfolio in the face of recurring and uncertain liquidity needs, with a model that accounts for both permanent and temporary price impact of trading. We first show that a risk-neutral investor wh ... Full text Open Access Cite

A Soft Robust Model for Optimization Under Ambiguity

Journal Article · August 2010 In this paper, we propose a framework for robust optimization that relaxes the standard notion of robustness by allowing the decision maker to vary the protection level in a smooth way across the uncertainty set. We apply our approach to the problem of max ... Cite

Information Relaxations and Duality in Stochastic Dynamic Programs

Journal Article · August 2010 We describe a general technique for determining upper bounds on maximal values (or lower bounds on minimal costs) in stochastic dynamic programs. In this approach, we relax the nonanticipativity constraints that require decisions to depend only on the info ... Cite

A soft robust model for optimization under ambiguity

Journal Article Operations Research · July 1, 2010 In this paper, we propose a framework for robust optimization that relaxes the standard notion of robustness by allowing the decision maker to vary the protection level in a smooth way across the uncertainty set. We apply our approach to the problem of max ... Full text Open Access Cite

Information relaxations and duality in stochastic dynamic programs

Journal Article Operations Research · July 1, 2010 We describe a general technique for determining upper bounds on maximal values (or lower bounds on minimal costs) in stochastic dynamic programs. In this approach, we relax the nonanticipativity constraints that require decisions to depend only on the info ... Full text Open Access Cite

Constructing uncertainty sets for robust linear optimization

Journal Article Operations Research · November 1, 2009 In this paper, we propose a methodology for constructing uncertainty sets within the framework of robust optimization for linear optimization problems with uncertain parameters. Our approach relies on decision maker risk preferences. Specifically, we utili ... Full text Cite

Satisficing measures for analysis of risky positions

Journal Article Management Science · January 1, 2009 In this work we introduce a class of measures for evaluating the quality of financial positions based on their ability to achieve desired financial goals. In the spirit of Simon (Simon, H. A. 1959. Theories of decisionmaking in economics and behavioral sci ... Full text Cite

Technical Note-On the Strength of Relaxations of Weakly Coupled Stochastic Dynamic Programs

Dynamic Programs with Shared Resources and Signals: Dynamic Fluid Policies and Asymptotic Optimality

Dynamic pricing of relocating resources in large networks

Index policies and performance bounds for dynamic selection problems

Dynamic Pricing of Relocating Resources in Large Networks

Approximations to stochastic dynamic programs via information relaxation duality

Static routing in stochastic scheduling: Performance guarantees and asymptotic optimality

Information relaxation bounds for infinite horizon markov decision processes

Information relaxations, duality, and convex stochastic dynamic programs

Optimal sequential exploration: Bandits, clairvoyants, and wildcats

Aspirational preferences and their representation by risk measures

Theory and applications of robust optimization

Dynamic portfolio optimization with transaction costs: Heuristics and dual bounds

Optimal portfolio liquidation with distress risk

A Soft Robust Model for Optimization Under Ambiguity

Information Relaxations and Duality in Stochastic Dynamic Programs

A soft robust model for optimization under ambiguity

Information relaxations and duality in stochastic dynamic programs

Constructing uncertainty sets for robust linear optimization

Satisficing measures for analysis of risky positions

Large deviations bounds for estimating conditional value-at-risk

Journal Article Operations Research Letters · November 1, 2007 In this paper, we prove an exponential rate of convergence result for a common estimator of conditional value-at-risk for bounded random variables. The bound on optimistic deviations is tighter while the bound on pessimistic deviations is more general and ... Full text Cite

Constrained stochastic LQC: A tractable approach

Journal Article IEEE Transactions on Automatic Control · October 1, 2007 Despite the celebrated success of dynamic programming for optimizing quadratic cost functions over linear systems, such an approach is limited by its inability to tractably deal with even simple constraints. In this paper, we present an alternative approac ... Full text Cite