bluuebunny/crossref_metadata_2025 huggingface dataset:
Integrated Simulation and Optimization Models for Tracking Indices of Fixed-Income Securities
Authors: Worzel Kenneth J. , Vassiadou-Zeniou Christiana , Zenios Stavros A.
Published: November 2008

Increasing performance pressures on fixed-income managers have led to a search for new and creative ways to add to portfolio returns. The largest pension plan sponsors, insurance companies, foundations, and money management firms are using indexed portfolios as their fixed-income assets management strategies since the late 1970s. Tracking a fixed-income index is a difficult task due to transaction costs, portfolio size and diversification restrictions, liquidity requirements, bid/ask spreads, etc. This paper develops an integrated simulation and optimization approach for tracking fixed-income indices. The model was implemented at Metropolitan Life Insurance Company. We introduce a simulation model for generating scenarios of holding period returns of the securities in the index. Then we develop optimization models to select a portfolio that tracks the index. The models penalize downside deviations of the portfolio return from the index. The developed framework is used to track the Salomon Brothers Mortgage Index. In backtesting over the period 1989–1991, the models outperformed the index by 50bp. Underperformance never exceeded more than −5bp in any single month. A small tracking error was also observed during the recent months that the model has been in use.
The Multi-Airport Ground-Holding Problem in Air Traffic Control
Authors: Vranas Peter B. , Bertsimas Dimitris J. , Odoni Amedeo R.
Published: November 2008

Motivated by the important problem of congestion costs (they were estimated to be $2 billion in 1991) in air transportation and observing that ground delays are more preferable than airborne delays, we have formulated and studied several integer programming models to assign ground-holding delays optimally in a general network of airports, so that the total (ground plus airborne) delay cost of all flights is minimized. All previous research on this problem has been restricted to the single-airport case, which neglects “down-the-road” effects due to transmission of delays between successive flights performed by the same aircraft. We formulate several models, and then propose a heuristic algorithm which finds a feasible solution to the integer program by rounding the optimal solution of the LP relaxation. Finally, we present extensive computational results with the goal of obtaining qualitative insights on the behavior of the problem under various combinations of the input parameters. We demonstrate that the problem can be solved in reasonable computation times for networks with at least as many as 6 airports and 3,000 flights.
Heuristic and Special Case Algorithms for Dispersion Problems
Authors: Ravi S. S. , Rosenkrantz D. J. , Tayi G. K.
Published: November 2008

The dispersion problem arises in selecting facilities to maximize some function of the distances between the facilities. The problem also arises in selecting nondominated solutions for multiobjective decision making. It is known to be NP-hard under two objectives: maximizing the minimum distance (MAX-MIN) between any pair of facilities and maximizing the average distance (MAX-AVG). We consider the question of obtaining near-optimal solutions. for MAX-MIN, we show that if the distances do not satisfy the triangle inequality, there is no polynomial-time relative approximation algorithm unless P = NP. When the distances satisfy the triangle inequality, we analyze an efficient heuristic and show that it provides a performance guarantee of two. We also prove that obtaining a performance guarantee of less than two is NP-hard. for MAX-AVG, we analyze an efficient heuristic and show that it provides a performance guarantee of four when the distances satisfy the triangle inequality. We also present a polynomial-time algorithm for the 1-dimensional MAX-AVG dispersion problem. Using that algorithm, we obtain a heuristic which provides an asymptotic performance guarantee of π/2 for the 2-dimensional MAX-AVG dispersion problem.
Conditional Stochastic Decomposition: An Algorithmic Interface for Optimization and Simulation
Authors: Higle Julia L. , Lowe Wing W. , Odio Ronald
Published: November 2008

Simulation and optimization are among the most commonly used elements in the OR toolkit. Often times, some of the data elements used to define an optimization problem are best described by random variables, yielding a stochastic program. If the distributions of the random variables cannot be specified precisely, one may have to resort to simulation to obtain observations of these random variables. In this paper, we present conditional stochastic decomposition (CSD), a method that may be construed as providing an algorithmic interface between simulation and optimization for the solution of stochastic linear programs with recourse. Derived from the concept of the stochastic decomposition of such problems, CSD uses randomly generated observations with a Renders decomposition of the problem. In this paper, our method is analytically verified and graphically illustrated. In addition, CSD is used to solve several test problems that have appeared in the literature. Our computational experience suggests that CSD may be particularly well suited for situations in which randomly generated observations are difficult to obtain.
Co-Production Processes with Random Yields in the Semiconductor Industry
Authors: Bitran Gabriel R. , Gilbert Stephen M.
Published: November 2008

A wide variety of manufacturing operations can be characterized as co-production with substitutable demand. That is, there are many situations in which the availability of two or more items are related, and because of randomness in either supply or demand, it can be advantageous to substitute one of these items for another. Our research was motivated by the semiconductor industry, where chips are produced in large batches. Because of the presence of randomness in the process, individual chips in a given batch can perform differently. Because some customers have stricter specifications than others, chips within the same batch can be classified and sold as different products according to their measurable performance. We model the production and inventory problem as a stochastic dynamic program in which the objective is to minimize the costs of meeting contractual obligations. After developing heuristic methods of solving the problem in practice, we validate them against a lower bound on the cost of an optimal solution to the dynamic program.
Return-State Independent Quantities in Regenerative Simulation
Authors: Calvin James
Published: November 2008

An important parameter of the regenerative method of simulation output analysis is the choice of return state used for blocking observations. Computational experience has shown that the statistical properties of estimators based on different regeneration points can vary widely. In this paper we study the limiting joint distribution of the normalized regenerative point and standard-deviation estimators for general state-space Markov chains. The asymptotic covariance between the point and standard-deviation estimators is shown to be the same for all return states, and the quantity is related to the normalized skewness of the partial sums of the chain. Since the covariance is constant, it follows that the choice of return state that minimizes the asymptotic variance of the standard-deviation estimator will maximize the correlation between the point and standard-deviation estimator. Consideration of asymptotic variance and covariance alone suggests that confidence intervals have the best coverage probabilities if the asymptotic variance of the standard-deviation estimator is minimized (thereby maximizing the correlation).
On Statistical Testing for Intransitivity in Multiattribute Consumer Preference Surveys
Authors: du Preez J. P.
Published: November 2008

In recent years various structures have been proposed for estimating intensity of consumer preference in consumer surveys. Empirical studies have shown intensity measures to be reliable and cost effective by providing more information per question. These structures use consumers' responses to determine whether the relevant preference function to be estimated is interval, ratio or ordinal in nature. This paper shows that the statistical tests to determine the nature of the preference function in one of the more popular structures often introduce bias in subsequent analysis. An alternative approach is indicated for use in some situations, which avoids some of the complexities involved in the more commonly used tests.
Dynamic Recomputation Cannot Extend the Optimality-Range of Priority Indices
Authors: Rothblum Uriel G. , Rothkopf Michael H.
Published: November 2008

Sequencing rules that rely on priority indices are particularly attractive because they are simple to calculate and easy to implement. It has been established that there are exactly two classes of delay cost functions for which policies that are determined by time-invariant priority indices are capable of producing optimal sequences: linear delay costs and discounted linear delay costs. We consider index-based policies that allow dynamic recalculation of priority indices and show that this class does not enlarge the set of delay cost functions for which index-based rules can produce optimal policies. Our analysis relies on the argument that index-based rules must induce a transitive ranking of the tasks. We show that the classes of linear and discounted linear functions are the only ones that can be associated with such rankings.
Computational Complexity of Some Maximum Average Weight Problems with Precedence Constraints
Authors: Faigle Ulrich , Kern Walter
Published: November 2008

Maximum average weight ideal problems in ordered sets arise from modeling variants of the investment problem and, in particular, learning problems in the context of concepts with tree-structured attributes in artificial intelligence. Similarly, trying to construct tests with high reliability leads to a nontrivial maximum average weight ideal problem. This paper investigates the computational complexity and shows that the general problem is NP-complete. Important special cases (e.g., finding rooted subtrees of maximal average weight), however, can be handled with efficient algorithms.
Optimality of Monotone Assemblies for Coherent Systems Composed of Series Modules
Authors: Hwang Frank K. , Rothblum Uriel G.
Published: November 2008

We consider a system with m modules as components. These modules are composed of parts of finitely many types, and the number of parts of each type that is needed in each of the modules is given, e.g., module i requires nui parts of type u. Parts of the same type may have different reliabilities, but they are functionally interchangeable. A module works if and only if all of its parts work, i.e., the internal composition of the modules has series structure. An assembly of the modules consists of an assignment of each of the ∑u ∑i nui parts to the modules such that each module meets its specification by getting the required number of parts of each type. Such an assembly is called monotone if the best parts of each type go to one module, the next best parts of each type go to a second module, and so on, until finally the last module gets the worst parts of each type. We prove that for coherent systems, there always exists a monotone assembly which maximizes the reliability of the system. Furthermore, we obtain sufficient conditions under which every optimal assembly is monotone.
A Greedy Randomized Adaptive Search Procedure for Maximum Independent Set
Authors: Feo Thomas A. , Resende Mauricio G. C. , Smith Stuart H.
Published: November 2008

An efficient randomized heuristic for a maximum independent set is presented. The procedure is tested on randomly generated graphs having from 400 to 3,500 vertices and edge probabilities from 0.2 to 0.9. The heuristic can be implemented trivially in parallel and is tested on an MIMD computer with 1, 2, 4 and 8 processors. Computational results indicate that the heuristic frequently finds the optimal or expected optimal solution in a fraction of the time required by implementations of simulated annealing, tabu search, and an exact partial enumeration method.
Single-Visit Policies for Allocating a Single Resource in a Stochastic Environment
Authors: Benkherouf I. , Glazebrook K. D. , Owen R. W.
Published: November 2008

Conventional analyses of stochastic resource allocation problems based on Gittins' indices frequently yield policies which involve an unacceptable amount of switching of the resource from one option to another. This paper discusses a variety of methodologies aimed at solving this problem. They principally involve the development and analysis of stochastic resource allocation models incorporating switching costs together with a consideration of a new class of single-visit policies for which each option has a single (random) period during which it is in receipt of the key resource.
Bargaining and Search with Recall: A Two-Period Model with Complete Information
Authors: Lee Ching Chyi
Published: November 2008

Two standard results of previous bargaining models state that delay is generally not expected to occur under complete information, and bargaining outcome depends crucially on the bargainers' intrinsic characteristics that determine their reservation prices, and, in general, bargainers with “better” reservation prices tend to get better outcomes. This paper considers a bilateral bargaining problem with complete information in which one of the bargainers, the buyer, is allowed to search while bargaining. More importantly, we assume that the buyer is allowed to recall past outside offers. We find that, quite contrary to the standard results of previous complete information bargaining models, complete information renders no guarantee for immediate resolution of bargaining, and the effect of changing the buyer's search cost on each player's bargaining outcome is unpredictable. The major driving force of these two results is the assumption that the buyer can recall past outside offers.
A Simple Release Policy for Networks of Queues with Controllable Inputs
Authors: Duenyas Izak
Published: November 2008

In a recent paper, L. M. Wein (1992) addressed the problem of scheduling a network of queues. Given a multistation, multiclass queueing network, the problem involves deciding when to release a job to the network as well as how to sequence jobs at each machine in the network to meet a desired throughput level. By approximating this problem by a control problem involving Brownian motion, Wein derived effective heuristics, which easily outperformed traditional work release and sequencing rules. However, Wein's work release rules are complex and his sequencing rules are dynamic. In this paper, we test the performance of a simpler work release policy based on CONWIP (constant work-in-process) in conjunction with static sequencing rules. The results of our simulation study indicate that this simple work release rule can be effective.
A Logical Topology and Discrete Capacity Assignment Algorithm for Reconfigurable Networks
Authors: Lee Ming-Jeng , Yee James R.
Published: November 2008

A reconfigurable network is a circuit-switched network where the effective topology and capacities can be dynamically adapted to changes in the traffic requirements or to changes in the structure of the network due to failures. The application of reconfigurable networks considered in this paper is data communications. We formulated the joint topology, capacity and routing problem in a reconfigurable network as a nonlinear, mixed integer programming problem. To solve this problem, we present a partial branch-and-bound algorithm. The reduced gradient method is used to solve the problem with the integrality constraints relaxed. Lagrangian relaxation is applied to obtain lower bounds. In the computational experiments, the algorithm found good solutions in a few minutes of CPU time. In addition, the reduction in the minimal delay due to the reconfiguration capability can be as large as 62%.
Telecommunications—A Revolution in Progress
Authors: Gavish Bezalel
Published: November 2008

Putting together a special issue of the ORSA journal that concentrates on the application of operations research in telecommunications was a pleasant task of assembling some of the best papers on different modeling and analysis techniques. At the same time, it was disappointing to realize how little operation researchers know about recent and emerging developments in the field and the opportunities they present for innovative research applied to telecommunication problems. In an attempt to remedy this situation, I decided to accomplish two tasks in writing the preface: To present and highlight some of the important research issues in telecommunications vying for contributions by operation researchers, applied mathematicians, and economists, and to link them, in the appropriate places, to the papers published in the special issue.
MS/OR Enabled Systems Design
Authors: O'Keefe Robert M.
Published: November 2008

Management (at least as reflected by popular management culture) is now more interested in redesigning systems completely than in marginal or continuing improvements. Some practical MS/OR work has recognized this and produced new systems that have changed their sponsoring organizations and provided them with competitive advantages. This paper considers the importance for MS/OR workers of focusing on system design rather than analysis aimed at supporting improvements in existing systems. It notes that MS/OR has traditionally perceived itself predominantly as analysis in this latter sense, and discusses the difference between design and this form of analysis. It then uses some Edelman prize finalist papers to illustrate the cycle of design-oriented MS/OR projects. Finally, this paper considers the opportunities and challenging problems afforded by system design, with particular reference to techniques, education, and the future success of MS/OR.
Aluminum Production Modeling—A Nonlinear Bilevel Programming Approach
Authors: Nicholls Miles G.
Published: November 2008

This paper develops a nonlinear bilevel programming model of an aluminium smelter that is capable of representing all the major production processes. The model encompasses all the areas of the smelter which operates in a multilevel way. However, as shown, it can be reduced quite simply to a bilevel programming problem. The problem specification involves nonlinearities with respect to the variables and the presence of ratios among the constraints. The problem is also characterized by a two-way material flow in the production process. A relatively simple solution algorithm that facilitates the attainment of the global optimum is developed. While the problem specification appears daunting, a number of simplifications can be made, due to nature of the problem, allowing its quick solution. While the model developed in this paper together with the solution algorithm appear simple, considerable effort was required to identify the fundamental relationships in the aluminium smelting process, quantify them, and then develop appropriate expressions to represent them. It is believed that the solution of this class of nonlinear bilevel programming problems will have implications for other applications.
Optimal and Approximate Control Policies for Airline Booking with Sequential Nonmonotonic Fare Classes
Authors: Robinson Lawrence W.
Published: November 2008

This paper addresses the question of when to refuse discount bookings from airline passengers to reserve seats for potential future passengers who are willing to pay a higher fare. When passengers arrive in sequential fare classes, the optimal policy will be to accept reservation requests as long as the cumulative seats booked does not exceed a given booking limit. This paper relates the probability of filling the plane, under the optimal policy, with the ratios of the current to the highest remaining fare classes. In addition, it extends the solution from monotonically increasing fares to fares occurring in arbitrary order. Finally, it demonstrates how Monte Carlo integration is easy to use to get arbitrarily close approximations to the optimal policy.
On the Strategic Role of Outside Options in Bilateral Bargaining
Authors: Muthoo Abhinay
Published: November 2008

This paper studies a model of the situation in which two players are bargaining face-to-face over the partition of a unit size cake and, moreover, one of the players can choose to temporarily leave the negotiating table to search for an outside option. A main conclusion is that the equilibrium outcome does not depend on whether a bargainer is allowed (within the game form) to choose to return to the negotiating table to resume bargaining after having searched for some finite time. Moreover, it is shown that our strategic bargaining-search game approximately implements an appropriately defined Nash bargaining solution.
98%-Effective Lot Sizing for Series Inventory Systems with Backlogging
Authors: Atkins Derek , Sun Daning
Published: November 2008

For deterministic series inventory systems with backlogging, we show that the continuous relaxation of the best integer frequency policies is a lower bound on all feasible policies. The problem with backlogging can be reduced, in O(n) time, to an equivalent problem without backlogging. Therefore, based on the result of R. O. Roundy (Roundy, R. O. 1983. 94%-Effective lot-sizing in multistage assembly systems. Technical Report 674, School of Operations Research and Industrial Engineering, Cornell University, Ithaca, New York.), the best integer frequency policy provides a solution which is within 2% of the optimal.
An Optimal Algorithm for the Traveling Salesman Problem with Time Windows
Authors: Dumas Yvan , Desrosiers Jacques , Gelinas Eric , Solomon Marius M.
Published: November 2008

This paper presents the development of new elimination tests which greatly enhance the performance of a relatively well established dynamic programming approach and its application to the minimization of the total traveling cost for the traveling salesman problem with time windows. The tests take advantage of the time window constraints to significantly reduce the state space and the number of state transitions. These reductions are performed both a priori and during the execution of the algorithm. The approach does not experience problems stemming from increasing problem size, wider or overlapping time windows, or an increasing number of states nearly as rapidly as other methods. Our computational results indicate that the algorithm was successful in solving problems with up to 200 nodes and fairly wide time windows. When the density of the nodes in the geographical region was kept constant as the problem size was increased, the algorithm was capable of solving problems with up to 800 nodes. For these problems, the CPU time increased linearly with problem size. These problem sizes are much larger than those of problems previously reported in the literature.
Regulation by Simulation: The Role of Production Cost Models in Electricity Planning and Pricing
Authors: Kahn Edward
Published: November 2008

This paper is a case study on the role of complex computer simulation models in the regulation of the electricity industry. The analysis focuses on electricity production cost simulation models as they are used to set prices for certain nonutility generators in California. This represents an early part of the trend toward “markets” for electric power, and away from pure monopoly supply. The introduction of even limited competition creates conditions both favoring and hindering the reliability of cost estimates, and demonstrates the sensitivity of results to problem specification and model implementation. Attention is focused on the representation of power system operational constraints, particularly the unit commitment problem, in the modeling process and their effect on the prices which result. Examples from the litigation history illustrate the problem of managing the strategic use and abuse of modeling techniques for competitive advantage. Highly structured procedures for using models in such situations offer some constraints on manipulation by competing parties. Otherwise, experts are apt to overwhelm regulators.
Using Judgment in Resource Management: A Multiple Objective Analysis of a Fisheries Management Decision
Authors: McDaniels Timothy L.
Published: November 2008

This paper uses multiple objective decision analysis to conduct an ex post analysis of a specific fisheries management decision involving conflicting long-term objectives for mixed stocks. The paper illustrates the potential role of subjective judgment in fisheries and other resource management contexts and the relevance of decision analysis for in-season salmon management. The decision context is first defined in terms of objectives and alternatives, then subjective probability distributions are elicited from experts regarding uncertain biological parameters. A simulation is then used to estimate the consequences of alternative openings, given the biological uncertainties. A utility function is elicited from a fisheries manager and used to select among alternative commercial fishery openings. The results show that objectives other than those typically assumed in fisheries modeling, and subjective judgments by technical experts, can be important for in-season salmon management. The results also show that, in this application, the equivalent of nearly $8 million in potential benefits are available from delaying the opening of the commercial fishery by a single day.
Efficient Algorithms for Finding Optimal Power-of-Two Policies for Production/Distribution Systems with General Joint Setup Costs
Authors: Federgruen Awi , Zheng Yu-Sheng
Published: November 2008

We consider a production/distribution system represented by a general directed acyclic network. Each node is associated with a specific “product” at a given location and/or production stage. An arc (i, j) indicates that item i is used to “produce” item j. External demands may occur at any of the network's nodes. These demands occur continuously at item-specific constant rates. Components may be assembled in any given proportions. The cost structure consists of inventory carrying, variable, and fixed production/distribution costs. The latter depend, at any given replenishment epoch, on the specific set of items being replenished, according to an arbitrary set function merely assumed to be monotone and submodular. It has been shown that a simply structured, so-called power-of-two policy is guaranteed to come within 2% of a lower bound for the minimum cost. In this paper, we derive efficient algorithms for the computation of an optimal power-of-two policy, possibly in combination with this lower bound. These consist of a limited number of polymatroidal maximum flow calculations in networks closely associated with the original production/distribution network.
A New Scenario Decomposition Method for Large-Scale Stochastic Optimization
Authors: Mulvey John M. , Ruszczyński Andrzej
Published: November 2008

A novel parallel decomposition algorithm is developed for large, multistage stochastic optimization problems. The method decomposes the problem into subproblems that correspond to scenarios. The subproblems are modified by separable quadratic terms to coordinate the scenario solutions. Convergence of the coordination procedure is proven for linear programs. Subproblems are solved using a nonlinear interior point algorithm. The approach adjusts the degree of decomposition to fit the available hardware environment. Initial testing on a distributed network of workstations shows that an optimal number of computers depends upon the work per subproblem and its relation to the communication capacities. The algorithm has promise for solving stochastic programs that lie outside current capabilities.
Breast Cancer Diagnosis and Prognosis Via Linear Programming
Authors: Mangasarian Olvi L. , Street W. Nick , Wolberg William H.
Published: November 2008

Two medical applications of linear programming are described in this paper. Specifically, linear programming-based machine learning techniques are used to increase the accuracy and objectivity of breast cancer diagnosis and prognosis. The first application to breast cancer diagnosis utilizes characteristics of individual cells, obtained from a minimally invasive fine needle aspirate, to discriminate benign from malignant breast lumps. This allows an accurate diagnosis without the need for a surgical biopsy. The diagnostic system in current operation at University of Wisconsin Hospitals was trained on samples from 569 patients and has had 100% chronological correctness in diagnosing 131 subsequent patients. The second application, recently put into clinical practice, is a method that constructs a surface that predicts when breast cancer is likely to recur in patients that have had their cancers excised. This gives the physician and the patient better information with which to plan treatment, and may eliminate the need for a prognostic surgical procedure. The novel feature of the predictive approach is the ability to handle cases for which cancer has not recurred (censored data) as well as cases for which cancer has recurred at a specific time. The prognostic system has an expected error of 13.9 to 18.3 months, which is better than prognosis correctness by other available techniques.
Research Strategies Used by OR/MS Workers as Shown by an Analysis of Papers in Flagship Journals
Authors: Reisman Arnold , Kirschnick Frank
Published: November 2008

It is possible to distinguish seven process categories among OR/MS research strategies: ripple, embedding, bridging, transfer of technology, creative application, structuring, and statistical modeling. To examine how often OR/MS workers use these processes, this paper analyzes as a sample the contents of the papers in the 1992 Issues of Operations Research, Management Science, and Interfaces. It finds that the ripple process is dominantly used in theoretical research and the transfer-of-technology process is the one most frequently used in true applications. The paper also sets forth the full spectrum of results for all seven processes in the 1992 sample, and reaches some conclusions with possible implications for the future of OR/MS.
A Branch-and-Bound Algorithm for Computing Optimal Replacement Policies in K-Out-of-N Systems
Authors: Chung Chia-Shin , Flynn James
Published: November 2008

We study a discrete time, infinite-horizon, dynamic programming model for the replacement of components in a binary coherent system with n components. Costs are incurred when the system fails and when failed components are replaced. The objective is to minimize the expected discounted infinite-horizon cost or the long-run expected average undiscounted cost per period. An earlier paper found general conditions under which it is optimal to follow a critical component policy (CCP), i.e., a policy specified by a critical component set and the rule: Replace a component if and only if it is failed and in the critical component set. Computing an optimal CCP is a binary nonlinear programming problem in n variables. This paper specializes to k-out-of-n systems and develops a branch-and-bound algorithm for finding an optimal decision. Its memory storage requirement is O((n+1)(n-k+1)), and the number of nodes examined is under O(nk). Extensive computational experiments with n ranging from 10 to 100 find it to be effective when k is small or near n. In our 120,000 test problems with k=n (parallel systems), the average computation time on a 20Mhz 386 microcomputer is 0.106 seconds.
Finite Horizon Markov Decision Processes with Uncertain Terminal Payoffs
Authors: White D. J.
Published: November 2008

This paper deals with the problem of finding an estimate of the maximal loss of optimality which can arise when terminal payoffs are uncertain and policies are restricted in some way. The original non-convex optimization problem is converted to a sequence of sub-problems involving the maximization of a bilinear function over a convex region. The paper deals solely with the theoretical issues.
Parallel Service with Vacations
Authors: Browne Sid , Kella Offer
Published: November 2008

We study a system with unlimited service potential where all service requests are served in parallel. The entire system itself becomes unavailable for a random period of time at the first instance that the system becomes idle. A queue builds up while the system is unavailable, and then all waiting customers enter the system simultaneously—each to its own processor—when the system becomes available again. All customers who arrive to find the system in operation proceed directly into service. The analysis of this system entails finding the distribution of the delayed busy period of an M/G/∞ queue. The steady-state distribution of the number of customers in the system is obtained for the special cases of exponential and deterministic service times. Among other applications, our results enable us to analyze and solve for the optimal N-policy for the systems with unlimited service potential. We also study a multiclass model of a polling system with exhaustive service.
An Inventory Model with Exogenous Failures
Authors: David Israel , Mehrez Avraham
Published: November 2008

This note introduces a model where inventory is repeatedly wiped out due to exogenous failure processes. The difference between this model and perishable inventory models is pinpointed by two sample examples. Relevant applications are also mentioned.
Processing Networks with Inventories: Sequential Refinement Systems
Authors: Lee Yong-Joo , Zipkin Paul
Published: November 2008

This paper investigates a model representing a make-to-stock production system, where intermediate and finished goods are produced and stored in advance of demand. In other respects the system operates much like a network of queues. There are several nodes and items. Each item is produced at one of the nodes using another item as input. Customer demands for the items and the unit-processing times at the nodes obey simple Markovian laws. We develop a tractable approximation scheme for estimating performance and test it through computer simulation. Numerical results show that the approximation is quite accurate. The model and the approximation express the effects of different degrees of component commonality.
The Productivity of Financial Intermediation and the Technology of Financial Product Management
Authors: Holmer Martin R. , Zenios Stavros A.
Published: November 2008

Financial intermediaries—banks, thrifts, and life insurance companies—have experienced low productivity over the last decade or two. Low productivity has manifested itself as a declining market share of their products relative to capital market assets. In some cases, low productivity caused a failure to meet contractual obligations embodied in their financial products. These failures resulted in customer losses, and/or taxpayer losses when failed intermediaries were guaranteed by government agencies. This productivity problem has been analyzed mostly from an economic science perspective, by R. C. Merton (Merton, R. C. 1990. The financial system and economic performance. J. Fin. Serv. Res. 263–300.) and Z. Bodie (Bodie, Z. 1990. Pension funds and financial innovation. Finan. Mgmt. (Autumn).). The focus of the economic analysis is the improvement of regulatory measures for intermediaries whose financial products are guaranteed by government agencies. In this paper we take a management science perspective by focusing on the technology of financial product management. An assessment of current technologies finds that their use can leave financial intermediaries exposed to substantial risks. An improved technology—integrated product management (IPM)—is suggested that enables intermediaries to increase productivity. Therefore, they can respond more effectively to market pressures from competing capital market assets and to regulatory pressures from government agencies. Technical and organizational aspects of integrated product management are described, and its application to three examples is discussed. The problem outlined here presents a major challenge to management scientists. It is an example of the service-sector applications that A. Geoffrion (Geoffrion, A. M. 1992. Forces, trends and opportunities in MS/OR. Opns. Res. 40 423–445.) addressed in his 1991 Omega Rho lecture.
Preface—New Directions for Operations Management Research
Authors: Cohen Morris A. , Magazine Michael J.
Published: November 2008

In the summer of 1992, we announced a special issue on “New Directions for Operations Management Research.” The objective of the special issue was to broaden the range of research articles published in Operations Research in the operations management field. We were particularly interested in identifying new problem contexts and new research paradigms for this rapidly evolving field. Traditional, model-based research associated with operations management is being augmented by a wide range of interdisciplinary and empirical approaches. For example, economic models (which are typically more parsimonious than engineering models) have been applied to areas such as global manufacturing strategy and new product development. Similarly, survey research and benchmarking studies, focusing on operations performance metrics concerned with quality, time, and flexibility, have emerged in studies with significant managerial impact.
An Empirical Study of Manufacturing Flexibility in Printed Circuit Board Assembly
Authors: Suarez Fernando F. , Cusumano Michael A. , Fine Charles H.
Published: November 2008

This paper addresses the empirical verification of hypotheses that relate to the strategic use and implementation of manufacturing flexibility. We begin with a literature review and framework for analyzing different types of flexibility in manufacturing. Next, we examine some of the propositions in the framework using data from 31 printed circuit-board plants in Europe, Japan, and the United States. Based on our analysis and findings, we then suggest several new strategic insights related to the management of flexibility and some potentially fruitful areas for further theoretical and empirical research. Our findings include: more automation is associated empirically with less flexibility, as found in other studies; nontechnology factors, such as high involvement of workers in problem-solving activities, close relationships with suppliers, and flexible wage schemes, are associated with greater mix, volume, and new-product flexibility; component reusability is significantly correlated with mix and new-product flexibility; achieving high-mix or new-product flexibility does not seem to involve a cost or quality penalty; mix and new-product flexibility are mutually reinforcing and tend to be supported by similar factors; and mix flexibility may reduce volume fluctuations, which could theoretically reduce the need for volume flexibility.
Management Problems of Large Organizations
Authors: Hitch Charles J.
Published: November 2008

In this paper, which the late Charles J. Hitch gave as a Phi Beta Kappa Lecture in 1978, he surveys his experiences as Comptroller of the U.S. Defense Department and President of the University of California system. He found that, in spite of the widely differing contexts, the two settings exhibited similar structural problems. His planning and strategic decision-making experiences with them support some principles common to both, and contain interesting lessons for the operations research profession.
Monitoring Drug Use Using Bayesian Acceptance Sampling: The Illinois Experiment
Authors: Lattimore Pamela K. , Baker Joanna R. , Matheson Lance A.
Published: November 2008

Bayesian acceptance sampling was used to monitor illegal drug use in a population of probationers. The study utilizes an economic model of drug testing based on single-sample, single-attribute acceptance sampling. This approach reduces from 100% the amount of testing which must be done to monitor the use of illegal drugs in the population and provides a decision rule, vis-à-vis a sampling plan, that specifies under what sampling outcome the entire population must be tested. The objective is to minimize the expected total cost of a drug testing program while ensuring that the proportion of users in the population is not increasing over time. A field study of the acceptance sampling approach was conducted using probationers assigned to Intensive Drug Supervision Programs in six Illinois counties. The degree to which drug testing results were reported to probation officers was controlled during the experiment. Counties were assigned to receive: no feedback of drug-test results; random proportion of feedback using Bayesian acceptance sampling plans; and 100% feedback—the status quo situation. Results show that those counties using acceptance sampling could have reduced the number of drug tests performed without increasing drug use. In those counties with no feedback, there was an upward trend over time in the proportion testing positive for drug use. Acceptance sampling-based drug testing programs are now being implemented by Illinois probation offices.
A New Generation of Vehicle Routing Research: Robust Algorithms, Addressing Uncertainty
Authors: Bertsimas Dimitris J. , Simchi-Levi David
Published: November 2008

In recent years new insights and algorithms have been obtained for the classical, deterministic vehicle routing problem as well as for natural stochastic and dynamic variations of it. These new developments are based on theoretical analysis, combine probabilistic and combinatorial modeling, and lead to new algorithms that produce near-optimal solutions, and a deeper understanding of uncertainty issues in vehicle routing. In this paper, we survey these new developments with an emphasis on the insights gained and on the algorithms proposed.
Integrated Variance Reduction Strategies for Simulation
Authors: Avramidis Athanassios N. , Wilson James R.
Published: November 2008

We develop strategies for integrated use of certain well-known variance reduction techniques to estimate a mean response in a finite-horizon simulation experiment. The building blocks for these integrated variance reduction strategies are the techniques of conditional expectation, correlation induction (including antithetic variates and Latin hypercube sampling), and control variates; all pairings of these techniques are examined. For each integrated strategy, we establish sufficient conditions under which that strategy will yield a smaller response variance than its constituent variance reduction techniques will yield individually. We also provide asymptotic variance comparisons between many of the methods discussed, with emphasis on integrated strategies that incorporate Latin hypercube sampling. An experimental performance evaluation reveals that in the simulation of stochastic activity networks, substantial variance reductions can be achieved with these integrated strategies. Both the theoretical and experimental results indicate that superior performance is obtained via joint application of the techniques of conditional expectation and Latin hypercube sampling.
Numerical Computation of the Moments of a Probability Distribution from its Transform
Authors: Choudhury Gagan L. , Lucantoni David M.
Published: November 2008

We present a simple, fast, and robust algorithm for numerically computing the first N moments (arbitrary N) of a nonnegative probability distribution from its Laplace-Stieltjes transform (continuous/mixed case) or z-transform (discrete case). The algorithm is based on numerically inverting an adaptively modified moment generating function. It only requires computation of the transform at several complex values of its argument. We also show that the high-order moments may be used in detecting the presence of exponential or geometric tails in distributions, and in case they are present the two parameters characterizing such a tail may be accurately computed. Several numerical examples of interest in the queueing literature illustrate the use of the algorithm. They include commonly used distributions as well as the waiting time, queue length, and busy period in queues with Poisson or more general Markovian arrival processes. Priority queues are also considered.
Strategic Arms Reduction Treaty (START) Drawdown Analyses
Authors: Owens Douglas W. , Parnell Gregory S. , Bivins Robert L.
Published: November 2008

This study investigated the feasibility and impacts of various U.S. and USSR time-phased strategic force structure reduction alternatives (commonly referred to as drawdowns) under the Strategic Arms Reduction Treaty (START). The study resulted from the Soviet Union's request for a U.S. position on the proposed Soviet drawdown limits. Treaty drawdown limits are time-phased numerical ceilings specified in the treaty, e.g., total weapons must be less than or equal to 8000 by January 1, 1996 and 6000 by January 1, 1998. Various modernized START force structures were evaluated under four drawdown limit alternatives. Two linear programming models (U.S. and USSR) were developed to rapidly assess each drawdown limit alternative. The models determined drawdown feasibility and identified the systems to dismantle each year to maximize force capability. For the U.S., the preferred drawdown limit alternatives were independent of the force structures considered, primarily because constraints on U.S. destruction rates drove the drawdown. For the USSR, significant differences occurred between each drawdown limit alternative, especially concerning multiple warhead systems like the SS-18. The results of this study were used to determine the U.S. START negotiation positions and assess the final START agreement.
Copula Models for Aggregating Expert Opinions
Authors: Jouini Mohamed N. , Clemen Robert T.
Published: November 2008

This paper discusses the use of multivariate distributions that are functions of their marginals for aggregating information from various sources. The function that links the marginals is called a copula. The information to be aggregated can be point estimates of an unknown quantity θ or, with suitable modeling assumptions, probability distributions for θ. This approach allows the Bayesian decision maker performing the aggregation to separate two difficult aspects of the model-construction procedure. Qualities of the individual sources, such as bias and precision, are incorporated into the marginal distributions. Dependence among sources is encoded into the copula, which serves as a dependence function and joins the marginal distributions into a single multivariate distribution. The procedure is designed to be suitable for situations in which the decision maker must use subjective judgments as a basis for constructing the aggregation model.

We review properties of copulas pertinent to the information-aggregation problem. A subjectively assessable measure of dependence is developed that allows the decision maker to choose from a one-parameter family of copulas a specific member that is appropriate for the level of dependence among the information sources. The discussion then focuses on the class of Archimedean copulas and Frank's family of copulas in particular, showing the specific relationship between the family and our measure of dependence. A realistic example demonstrates the approach.