bluuebunny/crossref_metadata_2025 huggingface dataset:
Arc Reduction and Path Preference in Stochastic Acyclic Networks
Authors: Bard Jonathan F. , Bennett James E.
Published: November 2008

The paper presents a heuristic for determining the path that maximizes the expected utility of a stochastic acyclic network. The focus is on shortest route problems where a general, nonlinear utility function is used to measure outcomes. For such problems, enumerating all feasible paths is the only way to guarantee that the global optimum has been found. Alternatively, we develop a reduction algorithm based on stochastic dominance to speed up the computations. Monte Carlo simulation is used to evaluate the approach. In all, 70 test problems comprising 20 to 60 nodes are randomly generated and analyzed. The results indicate that the heuristic produces significant computational saving as the size of the network grows, and that the quality of the reduced network solutions are better than those obtained from the original formulation.
Behind the Learning Curve: A Sketch of the Learning Process
Authors: Adler Paul S. , Clark Kim B.
Published: November 2008

This exploratory paper sketches some of the behavioral processes that give rise to the learning curve. Using data from two manufacturing departments in an electronic equipment company, we construct a model of productivity improvement as a function of cumulative output and two managerial variables—engineering changes and workforce training. Exploration of this model highlights the complex relationship between first-order and second-order learning.
On the Independence of Irrelevant Assets: McEntire's Conjecture
Authors: Deb Raj , Hadar Josef , Seo Tae Kun
Published: November 2008

In his 1984 paper in Management Science, McEntire conjectured that all concave utility functions satisfy his independence-from-irrelevant-assets (IIA) property. This paper shows that this conjecture is false. The paper provides several families of utility functions, all of whose members violate the IIA property; moreover, it is shown that the set of utility functions violating the IIA property is quite large, and that it is widespread throughout the entire space of utility functions.
The Pointwise Stationary Approximation for Mt/Mt/s Queues Is Asymptotically Correct As the Rates Increase
Authors: Whitt Ward
Published: November 2008

Green, Kolesar and Svoronos (in press) and Green and Kolesar (in press) use numerical methods to investigate the behavior of multiserver Markov queues with a Poisson arrival process having a sinusoidal arrival rate. For this model they propose an approximation for long-run average performance measures called the pointwise stationary approximation (PSA), which consists of an appropriate weighted average of the performance measure that would result at each point in time if the system were stationary with the arrival rate that applies at that point in time. In this paper we verify their conjecture that PSA is asymptotically correct as the service and arrival rates increase with the instantaneous traffic intensity held fixed (corresponding to long arrival rate cycles). We actually establish both pointwise and average versions of this result for general time-dependent birth-and-death processes.
Theoretical Foundation for a Learning Rate Budget
Authors: Kantor Paul B. , Zangwill Willard I.
Published: November 2008

A conceptualization of production learning is proposed, which resolves costs into groups characterized by the rate at which the costs can be reduced. These groups may correspond to learning in process, materials or technology. This approach suggests a new budget methodology, the Learning Rate Budget (LRB), which combines activities with similar learning rates to facilitate planning, forecasting, bidding, accountability, and management control. This new conceptualization of cost progress rests on three postulates concerning the budget, the technology and a finite basis for the learning curve. This paper explores these postulates, presents the LRB, and summarizes the empirical study that led to this concept.
A Balance Model for Evaluating Firms for Acquisition
Authors: Rao Vithala R. , Mahajan Vijay , Varaiya Nikhil P.
Published: November 2008

In recent years, the U.S. corporate world has been dominated by a spectacular spate of mergers and acquisitions. Firms are seeking out partners that will provide them the necessary leverage to achieve their various growth and diversification goals. Based on the balance model developed by Farquhar and Rao, this paper suggests a multi-attribute approach for evaluating acquisition partners. The appropriateness of this approach in the decision of one firm to acquire another firm is investigated using experimental methods. The context of the cosmetic industry is used in this empirical application. Results indicate that the balance model is quite suitable in describing the acquisition decision.
The Allocation of Consumer Incentives to Meet Simultaneous Sales Quotas: An Application to U.S. Army Recruiting
Authors: Lovell C. A. Knox , Morey Richard C.
Published: November 2008

Consumer incentives often have a dual role: to expand the market and to redistribute the market so as to meet sales targets for a range of products. The proper allocation of incentives must recognize and deal with the competitive and “cannibalizing” effects operating among product classes. The presence of environmental factors, scale economies, and cost per unit for each of the candidate incentive types also must be accounted for. This paper develops and illustrates an analytical approach designed to improve the allocation of consumer incentives where sales targets are exogenously set. The model generates a system of simultaneous behavioral equations, a portion of which is included to reflect attempted cost minimizing behavior. The model is applied to FY81-FY86 data from the U.S. Army Recruiting Command, which allocated over $1 billion for special incentives to selected recruits. The incentives consist of enlistment bonuses and educational benefits offered to quality recruits who select critical occupational specialties. The sales targets are enlistment quotas for each of the occupational specialties that must be simultaneously satisfied. The Army's goal is to meet these quotas, in a postulated recruiting environment, at minimum total incentive expenditure. Results suggest that the Army could improve the cost-effectiveness of its recruiting effort through a reallocation of the incentives it offers to recruits. Misallocation during the FY81-FY86 period is estimated to have cost the Army approximately 3.5% of its total incentives expended in infantry recruiting recruiting.
Resource Allocation Models with Risk Aversion and Probabilistic Dependence: Offshore Oil and Gas Bidding
Authors: Keefer Donald L.
Published: November 2008

Bidding for offshore U.S. oil and gas leases is a major corporate resource allocation problem involving enormous uncertainties and very high stakes. This paper presents two new, operationally useful decision analysis models to aid in bidding for oil and gas leases. They are unique in that they consider risk aversion and probabilistic dependence among the values of the leases, with both bid levels and partnership shares as (continuous) decision variables. They are suitable for use in evaluating proposed bidding policies or as objective functions in optimization formulations. Practicality of their data requirements is evidenced by use of one of the models for several years in a major oil company. Comparison of optimal solutions to these models on a small example, using actual oil-company data, demonstrates the importance of taking risk aversion and probabilistic dependence into account, and provides insight into the adequacy of independence and conditional dependence as approximations for dependence. These results are pertinent to other real-world allocation problems that share many of the characteristics of bidding problems, such as R&D funds allocation.
Mean-Absolute Deviation Portfolio Optimization Model and Its Applications to Tokyo Stock Market
Authors: Konno Hiroshi , Yamazaki Hiroaki
Published: November 2008

The purpose of this paper is to demonstrate that a portfolio optimization model using the L1 risk (mean absolute deviation risk) function can remove most of the difficulties associated with the classical Markowitz's model while maintaining its advantages over equilibrium models. In particular, the L1 risk model leads to a linear program instead of a quadratic program, so that a large-scale optimization problem consisting of more than 1,000 stocks may be solved on a real time basis. Numerical experiments using the historical data of NIKKEI 225 stocks show that the L1 risk model generates a portfolio quite similar to that of the Markowitz's model within a fraction of time required to solve the latter.
Accounting Implications of Corporate Diversification
Authors: Amit Raphael , Livnat Joshua , Zarowin Paul
Published: November 2008

This study investigates the direct effects of corporate diversification on accounting reports, and the implications of these effects for accounting research. The study shows that firms which diversify into unrelated areas of business devote a larger proportion of their capital investments to acquisitions and are, therefore, characterized by smaller differences between replacement-cost and historical-cost values of assets than undiversified firms. The implications of these findings, as well as other operating characteristics of diversified firms, for the following areas of accounting research are subsequently examined.

(1) Inflation-adjusted data. Inflation-adjusted data of diversified firms have less incremental information content (beyond historical-cost) than those of undiversified firms.

(2) Earnings Response Coefficients. Diversified firms have stronger market associations with earnings changes, and their earnings are more persistent.

(3) Selection of accounting methods. Diversified firms select, ceteris paribus, more liberal accounting methods than their undiversified counterparts.
Strategic Interpolative Design of Dynamic Manufacturing Systems Layouts
Authors: Montreuil Benoit , Venkatadri Uday
Published: November 2008

This paper presents a proactive strategic methodology for designing dynamic layouts for the expansion (or decline) phase of manufacturing systems. The methodology first estimates probable scenarios of the system requirements at its maturity level, strategically designs mature layouts given the set of scenarios, then tactically interpolates intermediate layouts, backward to the initial facilities plan.

For manufacturing systems with rigid facilities, the paper provides a linear programming model sustaining this proactive strategic methodology. The model efficiently generates optimal layouts for all intermediate expansion phases given a goal layout for the final mature phase of the expansion plan, the phased cell sets, the phased flow and relationships sets, and various design constraints, for an array of objectives.
Algorithms for the Multi-Resource Generalized Assignment Problem
Authors: Gavish Bezalel , Pirkul Hasan
Published: November 2008

The multi-resource generalized assignment problem is encountered when a set of tasks have to be assigned to a set of agents in a way that permits assignment of multiple tasks to an agent subject to the availability of a set of multiple resources consumed by that agent. This problem differs from the generalized assignment problem in that an agent consumes not just one but a variety of resources in performing the tasks assigned to him.

This paper develops effective solution procedures for the multi-resource generalized assignment problem. Various relaxations of the problem are studied and theoretical relations among these relaxations are pointed out. Rules for reducing problem size are discussed and are shown to be effective through computational experiments. Heuristic solution procedures and an efficient branch and bound procedure are developed. Results of computational experiments testing these procedures are reported.
Strict vs. Weak Ordinal Relations for Multipliers in Data Envelopment Analysis
Authors: Ali Agha Iqbal , Cook Wade D. , Seiford Lawrence M.
Published: November 2008

In a recent paper, Golany (1988) proposes an interesting extension of Data Envelopment Analysis to the situation where ordinal relations among weights corresponding to certain dimensions exist. However, the development of the extended model contains mathematical errors and the proposed equivalence is incorrect.

We establish the correct model equivalence and prove that weak ordinal relations require a nonstandard DEA model. We also show that the case of strict ordinal relations can be handled with the standard DEA model. These results hold for the CCR, BCC, additive, and multiplicative models and for relations involving both input and output multipliers.
Decision Making Over Time and Under Uncertainty: A Common Approach
Authors: Prelec Drazen , Loewenstein George
Published: November 2008

This paper considers a number of parallels between risky and intertemporal choice. We begin by demonstrating a one-to-one correspondence between the behavioral violations of the respective normative theories for the two domains (i.e., expected utility and discounted utility models). We argue that such violations (or preference reversals) are broadly consistent with three propositions about the weight that an attribute receives in both types of multiattribute choice. Specifically, it appears that: (1) if we add a constant to all values of an attribute, then that attribute becomes less important; (2) if we proportionately increase all values of an attribute, or if we change the sign of an attribute, from positive to negative, then that attribute becomes more important. The generality of these propositions, as well as the constraints they would impose on separable representations of multiattribute preferences, is discussed.
Robust Capacity Planning Under Uncertainty
Authors: Paraskevopoulos Dimitris , Karakitsos Elias , Rustem Berc
Published: November 2008

The existence of uncertainty influences the investment, production and pricing decision of firms. Therefore, capacity expansion models need to take into account uncertainty. This uncertainty, may arise because of errors in the specification, statistical estimation of relationships and in the assumptions of exogenous variables. One such example is demand uncertainty. In this paper, a cautious capacity planning approach is described for solving problems in which robustness to likely errors is needed. The aim is to cast the problem in a deterministic framework and thereby avoid the complexities inherent in nonlinear stochastic formulations. We adopt a robust approach and minimize an augmented objective function that penalises the sensitivity of the objective function to various types of uncertainty. The robust or sensitivity approach is compared with Friedenfelds' equivalent deterministic demand method. Using numerical results from a large nonlinear programming capacity planning model, it is shown that as caution against demand uncertainty increases, the variance of the total objective function (profit) decreases. The cost of such robustness is a deterioration in the deterministic risky performance. This method is also applied to an industry simulation model in order to assess the effect of uncertainty in market demand on optimal capacity expansion and capacity utilisation.
Optimal Update Policies for Distributed Materialized Views
Authors: Segev Arie , Fang Weiping
Published: November 2008

In this paper we present an analysis of the problem of determining optimal policies for updating distributed materialized views. We demonstrate the general application of materialized views, and define the concept of materialized view currency and allow a query to specify its currency requirement. We also allow a materialized view to be updated from either a base relation or another materialized view. This flexibility provides an opportunity for further reduction in the cost of maintaining distributed materialized views. We model the problem of optimal update policies to capture currency and policy constraints, replicated data, and various view update policies. The optimization incorporates a minimum-cost objective function as well as user's response time constraints.
Note—Sequencing JIT Mixed-Model Assembly Lines
Authors: Inman Robert R. , Bulfin Robert L.
Published: November 2008

We provide a new formulation and solution procedure to sequence a mixed model just-in-time (JIT) assembly system. Mixed model JIT assembly systems are a fundamental part of the well-known “Toyota Production System.” The underlying idea in sequencing these systems is to maintain a constant usage rate of all parts on the line. We give a polynomial algorithm to determine the optimal sequence for an objective function that is mathematically different, but intuitively similar to the objective functions of previous researchers. Furthermore, a computational study indicates that the new algorithm is robust in that its sequences are as good as those generated by other algorithms when evaluated with respect to traditional objectives, but are found 200 times faster.
Models of Tradeoffs in a Hierarchical Structure of Objectives
Authors: Harvey Charles M.
Published: November 2008

Multiattribute utility models and cost-benefit models often arrange the objectives into a hierarchical structure in order to identify appropriate subobjectives and to select appropriate attributes to measure the subobjectives. This paper discusses nonadditive models that use the hierarchical structure in order to examine issues of tradeoffs that models in present use are not able to include. The models are sufficiently structured so that they can be applied by procedures that are similar to those available for other prescriptive models of preferences.
Sources of Superior Performance: Market Share Versus Industry Effects in the U.S. Brewing Industry
Authors: Montgomery Cynthia A. , Wernerfelt Birger
Published: November 2008

Using financial measures of performance we investigate the sources of value creation in the U.S. brewing industry between 1969 and 1979. We find that market share gains in this industry at this time are not correlated with changes in value and that the performance of individual leading firms is highly correlated. Our interpretation is that the success of market share building strategies depends critically on specific industry conditions. Specifically, in the absence of fundamental shifts in the relative resource positions of individual firms, share gains may come at too high a price. In addition, the research shows that intra-industry correlations in returns may result from excessive competition rather than collusion.
Sensitivity Analysis for Mean-Variance Portfolio Problems
Authors: Best Michael J. , Grauer Robert R.
Published: November 2008

This paper shows how to perform sensitivity analysis for Mean-Variance (MV) portfolio problems using a general form of parametric quadratic programming. The analysis allows an investor to examine how parametric changes in either the means or the right-hand side of the constraints affect the composition, mean, and variance of the optimal portfolio. The optimal portfolio and associated multipliers are piecewise linear functions of the changes in either the means or the right-hand side of the constraints. The parametric parts of the solution show the rates of substitution of securities in the optimal portfolio, while the parametric parts of the multipliers show the rates at which constraints are either tightening or loosening. Furthermore, the parametric parts of the solution and multipliers change in different intervals when constraints become active or inactive. The optimal MV paths for sensitivity analyses are piecewise parabolic, as in traditional MV analysis. However, the optimal paths may contain negatively sloping segments and are characterized by types of kinks, i.e., points of nondifferentiability, not found in MV analysis.
Simulating Health Expenditures Under Alternative Insurance Plans
Authors: Buchanan Joan L. , Keeler Emmett B. , Rolph John E. , Holmer Martin R.
Published: November 2008

A simulation model that estimates individual health care spending as a function of the structure of indemnity-type insurance plans is presented. The behavioral models that form the basis for this work were developed as part of RAND's Health Insurance Experiment, (HIE), a randomized clinical trial. The randomized design and statistical methods provided estimates of the effects of insurance on use, uncontaminated by sickness or selection effects. The demand for medical care was modelled using episodes of treatment. Within the simulation, episodes occur independently and randomly through time according to a Poisson process with rates depending on individual characteristics and insurance. Empirical results from the HIE indicate that insurance primarily affects individual decisions to seek treatment (episode frequency), but has only minimal effects on episode costs. The response to changes in price (insurance) is modelled as a Bernoulli censoring process on episode frequency. The model is used to address issues on the effective design of insurance plans.
Designing Telecommunications Networks for the Reseller Market
Authors: Bard Jonathan F. , Bejjani Wassim A.
Published: November 2008

This paper presents an algorithm for minimizing the monthly cost of telecommunications networks characterized by multichannel queues with forced balking and hierarchical routing plans. The problem is of major interest to resellers of long distance services and corporate network managers who lease their lines from AT&T and Other Common Carriers. The algorithm can be used to select the most economical combination of lines to meet a desired grade of service, set here to an average blockage rate of 1% during the busy hour.

Because of the nonlinearities involved, the problem is formulated as a dynamic program and solved with forward recursion. The Erlang loss formula is used to determine blockage in the case of Poisson arrivals, while Wilkinson's equivalent random theory is adopted when the input traffic is peaked. Model validation is achieved with a SLAM II simulation.

The algorithm is applied to the network of National Telecommunications of Austin, which consists of 5 hierarchical levels and 52 candidate nodes, and carries about 2.3 million minutes of monthly traffic. Current services range from FX connections to Specialized WATS. The results indicate that cost reductions of over 18%, or $30,000 per month, can be achieved by periodically adjusting trunk group sizes to match the forecast demand.
Soviet Multi-Objective Mathematical Programming Methods: An Overview
Authors: Lieberman Elliot R.
Published: November 2008

Over the past 20–30 years multi-objective mathematical programming (MOMP) has emerged as an increasingly active area of research in the fields of management science, operations research, applied mathematics, and engineering. Despite the intensity of interest, however, earlier surveys of MOMP methods have all but ignored Soviet work in this area. Published in unfamiliar journals and often available only in Russian, the Soviet research has remained virtually unknown outside of the USSR and Eastern Europe. This has been particularly unfortunate given the extent, importance, and originality of much of the Soviet research. The current article attempts to correct this situation by providing a comprehensive, yet nontechnical, overview of Soviet MOMP methods. Using a taxonomy similar to ones that have been applied to Western MOMP techniques, the article categorizes the Soviet methods based on when they involve a decision maker in the solution process—a priori, progressively, a posteriori, or never—and what kind of information the decision maker provides. In all, 17 methods are analyzed with particular attention given to their distinctive features and to the issues of computational feasibility and burden on the decision maker. The article concludes with observations on the overall character of Soviet MOMP research, comparing the general directions in Soviet and Western research.
Bootstrapped Insights into Empirical Applications of Stochastic Dominance
Authors: Nelson Ray D. , Pope Rulon D.
Published: November 2008

Bootstrapping, a very versatile statistical technique, significantly amplifies the understanding and success of empirical applications of stochastic dominance. Its ability to calculate the standard deviations of order statistics reveals the uncertainty of the critical estimates of the tails of cumulative density functions. Understanding this uncertainty reveals why a wide variety of tail shapes all cause a notable loss in power for stochastic dominance tests. Simulations show that the smoothing inherent in bootstrapping can significantly increase the power of the tests when dominance exists in the population.
Note—An Improved Discrete Dynamic Programming Algorithm for Allocating Resources Among Interdependent Projects
Authors: Carraway Robert L. , Schmidt Robert L.
Published: November 2008

Nemhauser and Ullmann (1969) proposed a discrete dynamic programming (DP) approach for several variations of the basic capital allocation model, including one in which the returns and resource consumption of projects are interdependent. For this case, we augment their DP approach with a branch-and-bound strategy as suggested in Morin and Marsten (1976). Computational results demonstrate that this enhancement significantly reduces required computation time and effectively removes any limit on the number of nonzero interaction terms allowed. We also demonstrate that our approach compares favorably to an alternative implicit enumeration approach proposed by Hansen (1972).
Note: An Improvement to the Dynamic Cycle Lengths Heuristic for Scheduling the Multi-Item, Single-Machine
Authors: Leachman Robert C. , Xiong Zhong K. , Gascon André , Park Kwangtae
Published: November 2008

A heuristic scheduling policy for multi-item, single-machine scheduling systems facing stochastic, time-varying demands was previously introduced by Leachman and Gascon. In this technical note we provide an improvement to the calculations of the policy. Simulation tests of the revised version of the policy indicate that the improvements maintain or enhance customer service while reducing total inventory and setup costs on the order of 1–7%.
Paradox or At Least Variance Found: A Comment on “Mean-Variance Approaches to Risk-Return Relationships in Strategy: Paradox Lost”
Authors: Bromiley Philip
Published: November 2008

In general, the problem is that the computed mean-variance relationship for a period of time cannot be identified in distinction to the effects of shifts in the relationship over time—without additional information or assumptions. Thus, using a mean-variance approach to risk-return relationships means that statements about the nature of the mean-variance association cannot be confirmed in a nontrivial fashion within the empirical system nor generalized to any other time period—including subperiods. (Ruefli 1990) (emphasis in original)
Eureka: A Hybrid System for Assembly Line Balancing
Authors: Hoffmann Thomas R.
Published: November 2008

Numerous methods have been proposed for solution of the simple assembly line balancing (SALB) problem. This paper describes a branch and bound algorithm which in many cases is faster than the well-known Hoffmann heuristic technique to which it is related. It introduces a simple bounding rule which uses the concept of the “theoretical” minimum slack time to achieve rapid solutions. It is combined with the Hoffmann heuristic to develop an even more effective system for solving SALB problems. Timing results are given for a standard set of problems found in the literature. Since that set was solved in such a very short time, more challenging as well as more typical problems are explored and timing results presented. Benchmarking of the procedure is easier since implementation is on an eight-megahertz IBM AT with a math coprocessor, using the standard IBM PC Professional FORTRAN compiler.
Multivariate Batch Means and Control Variates
Authors: Yang Wei-Ning , Nelson Barry L.
Published: November 2008

We consider applying the nonoverlapping batch means output analysis method in conjunction with the control-variate variance-reduction technique to estimate a steady-state multivariate mean vector. The effects of the number of batches and the number of control variates on the multivariate point and region estimators and the univariate point and interval estimators are considered. The results are experiment analysis guidelines in terms of an appropriate range of the number of batches to choose as a function of the number of responses and control variates. The results have implications for terminating simulations as well.
Optimal Cycle Times in Multistage Serial Systems with Set-Up and Inventory Costs
Authors: Karimi Iftekhar A.
Published: November 2008

Scheduling of multistage serial production systems under constant demand and infinite horizon is considered. The production stages operate with periodic shut-downs and startups. An integer nonlinear programming formulation is presented for determining a stationary, cyclic schedule with no stock-outs in any inventory and minimum sum of set-up and inventory costs. It allows a lot-sizing policy involving arbitrary, noninteger splitting/merging of lots. Three, almost optimal, heuristic algorithms and an exact branch and bound algorithm are developed using analytical results. Their evaluation using simulated problems shows the branch and bound algorithm to be the best, as it is fast even for systems with as many as 11 stages.
Growth Versus Security in Dynamic Investment Analysis
Authors: MacLean L. C. , Ziemba W. T. , Blazenko G.
Published: November 2008

This paper concerns the problem of optimal dynamic choice in discrete time for an investor. In each period the investor is faced with one or more risky investments. The maximization of the expected logarithm of the period by period wealth, referred to as the Kelly criterion, is a very desirable investment procedure. It has many attractive properties, such as maximizing the asymptotic rate of growth of the investor's fortune. On the other hand, instead of focusing on maximal growth, one can develop strategies based on maximum security. For example, one can minimize the ruin probability subject to making a positive return or compute a confidence level of increasing the investor's initial fortune to a given final wealth goal. This paper is concerned with methods to combine these two approaches. We derive computational formulas for a variety of growth and security measures. Utilizing fractional Kelly strategies, we can develop a complete tradeoff of growth versus security. The theory is applicable to favorable investment situations such as blackjack, horseracing, lotto games, index and commodity futures and options trading. The results provide insight into how one should properly invest in these situations.
An Emerging Distributed Work Arrangement: An Investigation of Computer-Based Supplemental Work at Home
Authors: Venkatesh Alladi , Vitalari Nicholas P.
Published: November 2008

Recent advances in information technology and changes in social and economic relationships have led individual workers and organizations to explore various types of distributed work arrangements. This paper examines a specific type of distributed work arrangement, supplemental work at home. This arrangement refers to full-time employees doing job-related work at home in the evenings and on weekends. Based on a theoretical analysis of supplemental work, data gathered from a 346 computer-owners and 104 nonowners are empirically examined. The results suggest that the amount of time spent on supplemental work is positively related to work self-determination variables (flexibility and control), portability of work tasks, the availability of a telecommunications link between the firm and the home, and household income, and negatively related to commuting time and the presence of children at home. The paper discusses the implications of supplemental work for organizational design and the employer-employee relationship, It concludes that compared to other types of work at home, supplemental work is one remote work arrangement that is likely to persist, especially for professionals and managers.
Minimizing Total Cost in Scheduling Outpatient Appointments
Authors: Ho Chrwan-Jyh , Lau Hon-Shiang
Published: November 2008

This paper considers various rules for scheduling appointments for medical clinic outpatients and investigates their ability to minimize a weighted sum of medical personnel's and patients' idle-time costs. It is shown that the idle times incurred by any given rule are affected by the following three “environmental factors” (in decreasing order of importance): the probability of no-show, the coefficient of variation of service times, and the number of patients per clinical session. Theoretically, an appropriate scheduling rule can be identified only if one knows the values of these parameters and the ratio between the medical personnel's and patients' idle-time costs.

Under environments characterized by 27 different combinations of the three environmental factors, the performance of nine scheduling rules are evaluated using simulation. Some of the rules evaluated are original to this study. The results are presented in the form of “efficient frontiers,” together with a simple procedure for identifying the best scheduling rule for given environmental-parameter values. This rule-identification procedure is shown to be easily adaptable for circumstances with limited knowledge about the environmental factors; it also reveals that the simple Bailey-Welch individual-appointment rules are surprisingly robust.
Simulation Designs for Quadratic Response Surface Models in the Presence of Model Misspecification
Authors: Donohue Joan M. , Houck Ernest C. , Myers Raymond H.
Published: November 2008

This article considers the selection of experimental designs for the estimation of second-order response surface metamodels in a simulation environment. Rather than construct designs based on the premise that the postulated model exactly represents the simulated response, as is the case in optimal design theory, we assume that the estimation process may be biased by the presence of unfitted third-order terms. We therefore seek to specify experimental plans that address the bias due to possible model misspecification as well as traditional variance considerations. The performance measure used for this “fit-protect” scenario is Box and Draper's design criterion of average mean squared error of predicted response. Four important classes of response surface experimental plans are examined: (1) central composite designs, (2) Box-Behnken plans, (3) three-level factorial experiments, and (4) small central composite designs. Each design class is studied in conjunction with three pseudorandom number assignment strategies: (1) the use of a unique set of streams at each design point; (2) the assignment of a common stream set to all experimental points: and (3) the simultaneous use of common and antithetic streams through design blocking. Comparisons of both design classes and assignment strategies are presented to assist the user in the selection of an appropriate experimental strategy.
A Branch-and-Bound Procedure for the Multiple Resource-Constrained Project Scheduling Problem
Authors: Demeulemeester Erik , Herroelen Willy
Published: November 2008

In this paper a branch-and-bound procedure is described for scheduling the activities of a project of the PERT/CPM variety subject to precedence and resource constraints where the objective is to minimize project duration. The procedure is based on a depth-first solution strategy in which nodes in the solution tree represent resource and precedence feasible partial schedules. Branches emanating from a parent node correspond to exhaustive and minimal combinations of activities, the delay of which resolves resource conflicts at each parent node. Precedence and resource-based bounds described in the paper are combined with new dominance pruning rules to rapidly fathom major portions of the solution tree. The procedure is programmed in the C language for use on both a mainframe and a personal computer. The procedure has been validated using a standard set of test problems with between 7 and 50 activities requiring up to three resource types each. Computational experience on a personal computer indicates that the procedure is 11.6 times faster than the most rapid solution procedure reported in the literature while requiring less computer storage. Moreover, problems requiring large amounts of computer time using existing approaches for solving this problem type are rapidly solved with our procedure using the dominance rules described, resulting in a significant reduction in the variability in solution times as well.
Profiles of Product Innovators Among Large U.S. Manufacturers
Authors: Capon Noel , Farley John U. , Lehmann Donald R. , Hulbert James M.
Published: November 2008

This paper identifies four groups among 113 Fortune 500 manufacturers that approach innovation quite differently. The groups are based on 27 measured elements of corporate environment, corporate strategy, and formal and informal organization. Both product innovation and financial performance differ significantly over the groups, and a group of 42 firms that invest heavily in innovation perform best financially. A smaller group of firms that are not innovative but which follow a strategy of acquisition perform nearly as well financially. Firms focusing research resources on process innovation perform poorly, although process research complements product research among the effective innovators. Particularly important for explaining both product innovation and financial performance of these firms are salient combinations of classic elements of good environment, good strategy and good organization—strong positions in growing markets, investment in research and development, open and creative organizational structures and supportive organizational climates.
Vector Computers, Monte Carlo Simulation and Regression Analysis: An Introduction
Authors: Kleijnen Jack P. C. , Annink Ben
Published: November 2008

Vector computers provide a new tool for management scientists. The application of that tool requires thinking in vector mode. This mode is examined in the context of Monte Carlo experiments with regression models; these regression models may serve as metamodels in simulation experiments. The vector mode needs to exploit a specific dimension of the Monte Carlo experiment, namely the replicates of that experiment. Taking advantage of the machine architecture gives a code that computes Ordinary Least Squares estimates on a Cyber 205 in only 2% of the time needed on a Vax 8700. For Generalized Least Squares estimates, however, the code runs slower on the Cyber 205 than on the VAX, if the regression model is small; for large models the CYBER 205 runs much faster.
The Role of Inventory in Delivery-Time Competition
Authors: Li Lode
Published: November 2008

The paper operationalizes the notion of shortage cost by considering the behavior of customers and competing firms and examines the role of inventory in response time competition. We start with a single-firm production control model in which customers are characterized by their preferences of price, quality and delivery time. The optimal production/inventory policy and the optimal choice between make-to-order and make-to-stock operations are determined in simple “newsboy”-like formulas. The basic model is then extended to an n-firm market game in which firms compete for orders from the aspect of early delivery. One could think of this setting as an oligopoly racing market. The analysis shows that competition can breed a demand for produce-to-stock, just as other economic phenomena such as economies of scale, uncertainty, or seasonality can induce make-to-stock, and that delivery-time competition increases the buyer's welfare while decreasing the producer's welfare.
Hierarchical Planning for Probabilistic Distribution Systems in Euclidean Spaces
Authors: Simchi-Levi David
Published: November 2008

We develop an analytical model to assist the design and control of probabilistic distribution systems. These distribution systems are characterized by the explicit inclusion of probabilistic elements. The probabilistic aspect considered is that only a subset of all potential customers needs service on any given working day. This subset of customers and their demand are determined according to some probability distribution. The cost of operating such systems is significantly affected by decisions on the number and locations of the distribution centers, the allocation of customers to each center, and the routing strategy. We propose a three-stage hierarchical approach in which decisions about the number of centers and their locations (first stage), customers allocations (second stage) and routing strategies (third stage) are combined to reduce total system cost.
Locally Rational Decision Making: The Distracting Effect of Information on Managerial Performance
Authors: Glazer Rashi , Steckel Joel H. , Winer Russell S.
Published: November 2008

This paper describes a phenomenon called “locally rational” decision-making, in which the mere presence of information may have dysfunctional consequences even if decision makers do not process the information incorrectly. Using the results from an experiment conducted with a strategic market simulation game, we find that the accessibility of information results in a disposition to focus on those components of decision-making most clearly addressed by the information. If these are not the components most closely tied to success, overall performance may in fact suffer. The decision-making process is thus “locally rational” since it may be optimal with respect to specific components of a larger plan, but globally suboptimal with regard to ultimate outcomes and for the organization as a whole. We describe the implications of the phenomenon for the use of market-related data in managerial decision-making.
Dynamic Pricing and Ordering Decisions by a Monopolist
Authors: Rajan Arvind , Rakesh  , Steinberg Richard
Published: November 2008

This paper considers the relationship between pricing and ordering decisions for a monopolistic retailer facing a known demand function where, over the inventory cycle, the product may exhibit: (i) physical decay or deterioration of inventory called wastage; and (ii) decrease in market value called value drop associated with each unit of inventory on hand. The retailer is allowed to continuously vary the selling price of the product over the cycle. We introduce a notion of instantaneous margin, and use it to derive profit maximizing conditions for the retailer.

The model explains the markdown of retail goods subject to decay. It also provides guidance in determining when price changes during the cycle are worthwhile due to product aging, how often such changes should be made, and how such changes affect ordering intervals and quantities.
Decomposition and Nondifferentiable Optimization with the Projective Algorithm
Authors: Goffin J. L. , Haurie A. , Vial J. P.
Published: November 2008

This paper deals with an application of a variant of Karmarkar's projective algorithm for linear programming to the solution of a generic nondifferentiable minimization problem. This problem is closely related to the Dantzig-Wolfe decomposition technique used in large-scale convex programming. The proposed method is based on a column generation technique defining a sequence of primal linear programming maximization problems. Associated with each problem one defines a weighted potential function which is minimized using a variant of the projective algorithm. When a point close to the minimum of the potential function is reached, a corresponding point in the dual space is constructed, which is close to the analytic center of a polytope containing the solution set of the nondifferentiable optimization problem. An admissible cut of the polytope, corresponding to a new supporting hyperplane of the epigraph of the function to minimize, is then generated at this approximate analytic center. In the primal space this new cut translates into a new column for the associated linear programming problem. The algorithm has performed well on a set of convex nondifferentiable programming problems.
Control Variate Models for Estimating Transient Performance Measures in Repairable Item Systems
Authors: Ahmed Mohamed A. , Gross Donald , Miller Douglas R.
Published: November 2008

We develop a new modeling idea for comparing infinite-source, ample-server models (∞/∞) and finite-source, finite-server models (f/f). The comparison provides an efficient estimate of the error when approximating an f/f system with an ∞/∞ system and allows the analytical solution of the ∞/∞ model to be used as a control variate. We show that using ∞/∞ models as control variates for f/f systems can be an effective variance reduction technique for system performance estimates. Using these estimates will allow us to determine more efficiently when ∞/∞ models are good approximations for f/f systems.
Experiments with Initial Transient Deletion for Parallel, Replicated Steady-State Simulations
Authors: Glynn Peter W. , Heidelberger Philip
Published: November 2008

A simple and effective way to exploit parallel processors in discrete event simulations is to run multiple independent replications, in parallel, on multiple processors and to average the results at the end of the runs. We call this the method of parallel replications. This paper is concerned with using the method of parallel replications for estimating steady-state performance measures. We report on the results of queueing network simulation experiments that compare the statistical properties of several possible estimators that can be formed using this method. The theoretical asymptotic properties of these estimators were determined in Glynn and Heidelberger (1989a, b). Both the theory and the experimental results reported here strongly indicate that a nonstandard (in the context of steady-state simulation), yet easy to apply, estimation procedure is required on highly parallel machines. This nonstandard estimator is a ratio estimator. The experiments also show that use of the ratio estimator is advantageous even on machines with only a moderate degree of parallelism.
A Nonlinear Heuristic Short-Term Model for Hydroelectric Energy Production: The Case of the Hazbani-Dan Water System
Authors: Rabinowitz Gad , Mehrez Abraham , Rabina Avi
Published: November 2008

A two-stage decision and control model for the operation of the power station in the Hazbani-Dan Water System (Israel) was developed and implemented. In this system, river water is stored and then either consumed by agricultural farms or released to a hydroelectric power station. Under management policy, agricultural consumption is taken as a constraint. The problem was solved via a two-stage procedure consisting of a long-term model (LTM) and a short-term model (STM). The LTM was presented by Rabinowitz et al. (1988). This paper reports on the development and analysis of the STM, in which operational flexibilities of the power station are taken into consideration, thereby improving the LTM solution.

Our main contributions are aimed at: (1) describing the (nontraditional) systematic thinking process which transformed the mathematically expressed problem into an efficiently solvable model; (2) presenting the analysis of the model; and (3) reporting on a practical application of the model in a unique system.