Hot off the presses! Jan 01 Oper Res

The Jan 01 issue of the Oper Res is now up on Pubget (About Oper Res): if you're at a subscribing institution, just click the link in the latest link at the home page. (Note you'll only be able to get all the PDFs in the issue if your institution subscribes to Pubget.)

Latest Articles Include:

• In This Issue
  - Oper Res 57(1):ii (2009)
  No abstract available.
• From the Editor
  - Oper Res 57(1):1-3 (2009)
  No abstract available.
• Area Editors' Statements
  - Oper Res 57(1):4-9 (2009)
  No abstract available.
• OR FORUM--The Evolution of Closed-Loop Supply Chain Research
  - Oper Res 57(1):10-18 (2009)
  The purpose of this paper is to introduce the reader to the field of closed-loop supply chains with a strong business perspective, i.e., we focus on profitable value recovery from returned products. It recounts the evolution of research in this growing area over the past 15 years, during which it developed from a narrow, technically focused niche area to a fully recognized subfield of supply chain management. We use five phases to paint an encompassing view of this evolutionary process for the reader to understand past achievements and potential future operations research opportunities.
• OR Practice--Modeling Potential Demand for Supply-Constrained Drugs: A New Hemophilia Drug at Bayer Biological Products
  - Oper Res 57(1):19-31 (2009)
  This paper describes the evolution and application of a novel approach for forecasting drug demand in markets where supply limitations have significantly curtailed sales volumes and thus reduced the usefulness of conventional sales-based forecasting methods. This occurs frequently with biological (biotech) drugs. We use methods from decision analysis to explicitly model the variability in epidemiological data together with the variability in treatment modalities to estimate latent therapeutic demand (LTD)--the underlying demand that captures how physicians would prescribe treatment and how patients would comply if ample supplies of drugs were available and affordable. Our approach evolved from efforts to help Bayer Biological Products with strategic decisions regarding its drug for treating hemophilia A, the future of which had been clouded for several years, primarily due to a lack of confidence in demand estimates. Use of the LTD model resulted in a better understand! ing of the therapeutic needs of the global hemophilia community and helped Bayer make good decisions. We believe this approach is widely applicable to forecasting potential demand for supply-constrained as well as brand-new drugs, and thus can be very useful in helping both drug manufacturers and health-care agencies worldwide to ensure adequate supplies of critical drugs.
• Stochastic Power Generation Unit Commitment in Electricity Markets: A Novel Formulation and a Comparison of Solution Methods
  - Oper Res 57(1):32-46 (2009)
  We propose a stochastic unit commitment model for a power generation company that takes part in an electricity spot market. The relevant feature of this model is its detailed representation of the spot market during a whole week, including seven day-ahead market sessions and the corresponding adjustment market sessions. The adjustment market sessions can be seen as an hour-ahead market mechanism. This representation takes into account the influence that the company's decisions exert on the market-clearing price by means of a residual demand curve for each market session. We introduce uncertainty in the form of several possible spot market outcomes for each day, which leads to a weekly scenario tree. The model also represents in detail the operation of the company's generation units. The model leads to large-scale mixed linear-integer problems that are hard to solve with commercial optimizers. This suggests the use of alternative solution methods. We test four solution! approaches with a realistic numerical example in the context of the Spanish electricity spot market. The first is a direct solution with a commercial optimizer, which illustrates the mentioned limitations. The second is a standard Lagrangean relaxation algorithm. The third and fourth methods are two original variants of Benders decomposition for multistage stochastic integer programs. The first Benders decomposition algorithm builds approximations for the recourse function relaxing the integrality constraints of the subproblems. The second variant strengthens these cuts by performing one iteration of the Lagrangean of each subproblem. We analyze the advantages of these four methods and compare the results.
• Supply Contracts with Financial Hedging
  - Oper Res 57(1):47-65 (2009)
  We study the performance of a stylized supply chain where two firms, a retailer and a producer, compete in a Stackelberg game. The retailer purchases a single product from the producer and afterward sells it in the retail market at a stochastic clearance price. The retailer, however, is budget constrained and is therefore limited in the number of units that he may purchase from the producer. We also assume that the retailer's profit depends in part on the realized path or terminal value of some observable stochastic process. We interpret this process as a financial process such as a foreign exchange rate or interest rate. More generally, the process can be interpreted as any relevant economic index. We consider a variation (the flexible contract) of the traditional wholesale price contract that is offered by the producer to the retailer. Under this flexible contract, at t = 0 the producer offers a menu of wholesale prices to the retailer, one for each realization of th! e financial process up to a future time {tau}. The retailer then commits to purchasing at time {tau} a variable number of units, with the specific quantity depending on the realization of the process up to time {tau}. Because of the retailer's budget constraint, the supply chain might be more profitable if the retailer was able to shift some of the budget from states where the constraint is not binding to states where it is binding. We therefore consider a variation of the flexible contract, where we assume that the retailer is able to trade dynamically between zero and {tau} in the financial market. We refer to this variation as the flexible contract with hedging. We compare the decentralized competitive solution for the two contracts with the solutions obtained by a central planner. We also compare the supply chain's performance across the two contracts. We find, for example, that the producer always prefers the flexible contract with hedging to the flexible contract with! out hedging. Depending on model parameters, however, the retai! ler might or might not prefer the flexible contract with hedging.
• The Impact of Delay Announcements in Many-Server Queues with Abandonment
  - Oper Res 57(1):66-81 (2009)
  This paper studies the performance impact of making delay announcements to arriving customers who must wait before starting service in a many-server queue with customer abandonment. The queue is assumed to be invisible to waiting customers, as in most customer contact centers, when contact is made by telephone, e-mail, or instant messaging. Customers who must wait are told upon arrival either the delay of the last customer to enter service or an appropriate average delay. Models for the customer response are proposed. For a rough-cut performance analysis, prior to detailed simulation, two approximations are proposed: (1) the equilibrium delay in a deterministic fluid model, and (2) the equilibrium steady-state delay in a stochastic model with fixed delay announcements. These approximations are shown to be effective in overloaded regimes, where delay announcements are important, by making comparisons with simulations. Within the fluid model framework, conditions are est! ablished for the existence and uniqueness of an equilibrium delay, where the actual delay coincides with the announced delay. Multiple equilibria can occur if a key monotonicity condition is violated.
• Dynamic Capacity Expansion for a Service Firm with Capacity Deterioration and Supply Uncertainty
  - Oper Res 57(1):82-93 (2009)
  Motivated by the challenges faced by the telecom industry during the past decade, in this paper we study a dynamic capacity expansion problem for service firms. There is a random demand for the firm's capacity in each period: the demand in excess of the capacity is lost, and revenue is generated for the fulfilled demand. At the beginning of each period, the firm might increase its capacity through purchasing equipment for immediate delivery, which is constrained by a random supply limit, or it might sign a future contract for equipment delivery in the following period. We assume that the firm's capacity might partially become obsolete due to natural deterioration or technology innovation. We aim at characterizing optimal capacity expansion strategies and comparing the profit functions as well as the optimal control policies of different options. Specifically, we show that the optimal capacity expansion policy for the current period is determined by a base-stock policy.! Compared with the case where no future contracts are available, the optimal control parameters of capacity expansion are always smaller. We further show that when the obsolescence rate is deterministic, the optimal policy for capacity expansion through future contracts is also a base-stock type. The results are extended to the cases with stochastically dependent capacity supply limits and stochastically dependent demand processes, which establish the robustness of the optimal policy in various market conditions.
• Dynamic Control of a Make-to-Order, Parallel-Server System with Cancellations
  - Oper Res 57(1):94-108 (2009)
  Motivated by make-to-order production systems, we consider a dynamic control problem for a multiclass, parallel-server queueing system. The production system serves multiple classes of customers who require rigid due-date lead times and may cancel their order subject to a cancellation penalty. To meet the due-date constraints, a system manager may outsource orders when the backlog of work is judged excessive, thereby incurring outsourcing costs. The system manager strives to minimize long-run average costs by dynamically making outsourcing and resource allocation decisions. Under heavy-traffic conditions, the scheduling problem is approximated by a Brownian control problem. Interpreting the solution of the Brownian control problem in the context of the original queueing system, a nongreedy outsourcing and resource allocation policy is proposed. A simulation experiment is performed to demonstrate the effectiveness of this policy.
• Omitting Meaningless Digits in Point Estimates: The Probability Guarantee of Leading-Digit Rules
  - Oper Res 57(1):109-117 (2009)
  Motivated by the question of which point-estimator digits to report in a statistical experiment, we study the probabilistic behavior of the digits as a function of the true performance measure and the point estimator's standard error. We investigate the family of Leading-Digit Rules, which guarantees that every unreported digit has correctness probability below a given threshold. Choosing the threshold to be about 0.198 yields Yoneda's rule. The easy-to-implement rule that reports the point estimate through the leading digit of the standard error has threshold (approximately) 0.117, which is not much larger than the one-in-ten probability of a uniformly distributed random digit being correct.
• Estimating Quantile Sensitivities
  - Oper Res 57(1):118-130 (2009)
  Quantiles of a random performance serve as important alternatives to the usual expected value. They are used in the financial industry as measures of risk and in the service industry as measures of service quality. To manage the quantile of a performance, we need to know how changes in the input parameters affect the output quantiles, which are called quantile sensitivities. In this paper, we show that the quantile sensitivities can be written in the form of conditional expectations. Based on the conditional-expectation form, we first propose an infinitesimal-perturbation-analysis (IPA) estimator. The IPA estimator is asymptotically unbiased, but it is not consistent. We then obtain a consistent estimator by dividing data into batches and averaging the IPA estimates of all batches. The estimator satisfies a central limit theorem for the i.i.d. data, and the rate of convergence is strictly slower than n-1/3. The numerical results show that the estimator works well for p! ractical problems.
• Coalition Stability in Assembly Models
  - Oper Res 57(1):131-145 (2009)
  In this paper, we study dynamic supplier alliances in a decentralized assembly system. We examine a supply chain in which n suppliers sell complementary components to a downstream assembler, who faces a price-sensitive deterministic demand. We analyze alliance/coalition formation between suppliers, using a two-stage approach. In Stage 1, suppliers form coalitions that each agree to sell a kit of components to the assembler. In Stage 2, coalitions make wholesale price decisions, whereas the assembler buys the components (kits) from the coalitions and sets the selling price of the product. Stage 2 is modeled as a competitive game, in which the primary competition is vertical (i.e., supplier coalitions compete against the downstream assembler), and the secondary competition is horizontal, in that coalitions compete against each other. Here, we consider three modes of competition--Supplier Stackelberg, Vertical Nash, and Assembler Stackelberg models--that correspond to dif! ferent power structures in the market. In Stage 1, we analyze the stability of coalition structures. We assume that suppliers are farsighted, that is, each coalition considers the possibility that once it acts, another coalition may react, and a third coalition might in turn react, and so on. Using this framework, we predict the structure of possible supplier alliances as a function of the power structure in the market, the number of suppliers, and the structure of the demand.
• Cost Allocation for Joint Replenishment Models
  - Oper Res 57(1):146-156 (2009)
  We consider the one-warehouse multiple retailer inventory model with a submodular joint setup cost function. The objective of this model is to determine an inventory replenishment policy that minimizes the long-run average system cost over an infinite time horizon. Although the optimal policy for this problem is still unknown, a class of easy-to-implement power-of-two policies are 98% effective. This paper focuses on how the cost, under an optimal power-of-two policy, should be allocated to the retailers. This question generates an interesting cooperative game. We prove that this cooperative game has a nonempty core. The key to our result is a strong duality theorem for the one-warehouse multiple retailer problem under power-of-two policies.
• The Adoption of Multiple Dependent Technologies
  - Oper Res 57(1):157-169 (2009)
  A firm often makes an adoption decision regarding an improvement of one technology depending on changes in other technologies. For example, a manufacturer with a serial production line considers jointly upgrading multiple machines, or a firm producing an assembled product considers improving several components simultaneously. Economies or diseconomies of scope in the fixed cost of adoption when multiple improvements are undertaken at the same time generate an economic dependence among the technological innovations. Although the literature on technological innovations has attributed slow adoption mainly to uncertainties outside the firm, this paper shows that the economic dependence that inherently defines cost relationships inside the firm can significantly influence the timing of adoption. Furthermore, this impact is not unidirectional: economic dependence can either expedite or delay the adoption of an improved technology.
• Connectivity Upgrade Models for Survivable Network Design
  - Oper Res 57(1):170-186 (2009)
  Disruptions in infrastructure networks to transport material, energy, and information can have serious economic, and even catastrophic, consequences. Since these networks require enormous investments, network service providers emphasize both survivability and cost effectiveness in their topological design decisions. This paper addresses the survivable network design problem, a core model incorporating the cost and redundancy trade-offs facing network planners. Using a novel connectivity upgrade strategy, we develop several families of inequalities to strengthen a multicommodity flow-based formulation for the problem, and show that some of these inequalities are facet defining. By increasing the linear programming lower bound, the valid inequalities not only lead to better performance guarantees for heuristic solutions, but also accelerate exact and approximate solution methods. We also consider a heuristic strategy that sequentially rounds the fractional values, starti! ng with the linear programming solution to our strong model. Extensive computational tests confirm that the valid inequalities, added via a cutting plane algorithm, and the heuristic procedure are very effective, and their performance is robust to changes in the network dimensions and connectivity structure. Our solution approach generates tight lower and upper bounds with average gaps that are less than 1.2% for various problem sizes and connectivity requirements.
• Generating a Representative Subset of the Nondominated Frontier in Multiple Criteria Decision Making
  - Oper Res 57(1):187-199 (2009)
  In this paper, we address the problem of generating a discrete representation of the nondominated frontier in multiple objective linear problems. We find a surface that approximates the shape of the nondominated frontier. Utilizing the surface, we generate a set of discrete points that is representative of the frontier. Our experience on randomly generated problems demonstrates that the approach performs well in terms of both the quality of the representation and the computation time.
• Allocation of Cost Savings in a Three-Level Supply Chain with Demand Information Sharing: A Cooperative-Game Approach
  - Oper Res 57(1):200-213 (2009)
  We analyze the problem of allocating cost savings from sharing demand information in a three-level supply chain with a manufacturer, a distributor, and a retailer. To find a unique allocation scheme, we use concepts from cooperative game theory. First, we analytically compute the expected cost incurred by the manufacturer and then use simulation to obtain expected costs for the distributor and the retailer. We construct a three-person cooperative game in characteristic-function form and derive necessary conditions for the stability of each of five possible coalitions. To divide the cost savings between two members, or among three supply chain members, we use various allocation schemes. We present numerical analyses to investigate the impacts of the demand autocorrelation coefficient, {rho}, and the unit holding and shortage costs on the allocation scheme.
• Reoptimization Approaches for the Vehicle-Routing Problem with Stochastic Demands
  - Oper Res 57(1):214-230 (2009)
  We consider the vehicle-routing problem with stochastic demands (VRPSD) under reoptimization. We develop and analyze a finite-horizon Markov decision process (MDP) formulation for the single-vehicle case and establish a partial characterization of the optimal policy. We also propose a heuristic solution methodology for our MDP, named partial reoptimization, based on the idea of restricting attention to a subset of all the possible states and computing an optimal policy on this restricted set of states. We discuss two families of computationally efficient partial reoptimization heuristics and illustrate their performance on a set of instances with up to and including 100 customers. Comparisons with an existing heuristic from the literature and a lower bound computed with complete knowledge of customer demands show that our best partial reoptimization heuristics outperform this heuristic and are on average no more than 10%-13% away from this lower bound, depending on the! type of instances.
• Airline Fleet Assignment with Enhanced Revenue Modeling
  - Oper Res 57(1):231-244 (2009)
  The airline fleet assignment problem addresses the question of how to best assign aircraft fleet types to scheduled flight legs. This paper presents the subnetwork fleet assignment model: a model that employs composite decision variables representing the simultaneous assignment of fleet types to subnetworks of one or more flight legs. The formulation is motivated by the need to better model the revenue side of the objective function. We present a solution method designed to balance revenue approximation and model tractability. Computational results suggest that the approach yields profit improvements over comparable models and that it is computationally tractable for problems of practical size.
• Technical Note--Optimal Dynamic Joint Inventory-Pricing Control for Multiplicative Demand with Fixed Order Costs and Lost Sales
  - Oper Res 57(1):245-250 (2009)
  This note studies the optimal dynamic decision-making problem for a retailer in a price-sensitive, multiplicative demand framework. Our model incorporates lost sales, holding cost, fixed and variable procurement costs, as well as salvage value. We characterize the structure of the retailer's (discounted) expected profit-maximizing dynamic inventory policy for both finite and infinite selling horizon problems.
• Technical Note--Approximating Vehicle Dispatch Probabilities for Emergency Service Systems with Location-Specific Service Times and Multiple Units per Location
  - Oper Res 57(1):251-255 (2009)
  To calculate many of the important performance measures for an emergency response system, one requires knowledge of the probability that a particular server will respond to an incoming call at a particular location. Estimating these "dispatch probabilities" is complicated by four important characteristics of emergency service systems. We discuss these characteristics and extend previous approximation methods for calculating dispatch probabilities to account for the possibilities of workload variation by station, multiple vehicles per station, call- and station-dependent service times, and server cooperation and dependence.
• Contributors
  - Oper Res 57(1):256-260 (2009)
  No abstract available.