bluuebunny/crossref_metadata_2025 huggingface dataset:
Calibration and the Expert Problem
Authors: French S.
Published: November 2008

A decision maker needs to give his subjective probability for a single event of interest, A. Being aware that he has little substantive knowledge of the factors affecting A, the decision maker asks an expert for advice. The expert gives his subjective probability for A. In the light of this information, how should the decision maker form his subjective probability? In particular, does it matter to the decision maker whether the expert is a well-calibrated probability assessor? In this paper these questions are explored and it is suggested that concepts such as calibration and refinement cannot usefully be defined independently of the decision maker.
Preemptive Scheduling of Uniform Machines by Ordinary Network Flow Techniques
Authors: Federgruen A. , Groenevelt H.
Published: November 2008

We consider the problem of scheduling n jobs, each with a specific processing requirement, release time and due date on m uniform parallel machines. It is shown that a feasible schedule can be obtained by determining the maximum flow in a network, thus permitting the use of standard network flow codes. Using a specialized maximum flow procedure, the complexity reduces to O(tn3) operations when t is the number of distinct machine types. Previous algorithms solve the feasibility problem in O((m + log n)(m2n3 + n4)) operations. In addition to the feasibility problem, we describe algorithms for the maximum lateness criterion. Here we develop a bound which compares even more favorably to the best previous bound. We also show how other criteria with respect to the amount of work completed on each job prior to its due date or the amount of work scheduled in each of a sequence of periods can be optimized by similar path augmenting techniques.
Safety Stocks in MRP—Systems with Emergency Setups for Components
Authors: Carlson Robert C. , Yano Candace A.
Published: November 2008

Material Requirements Planning or Manufacturing Resource Planning (MRP) systems originally were designed for a deterministic environment. Often, however, demand for finished products is uncertain and some type of buffering mechanism is necessary to provide desired levels of service. When the schedule is replanned each period, as typically is done, variability of demand may manifest itself in the form of early or “emergency” production runs. Safety stock may serve to avert some or most of these emergency production runs. We have developed a heuristic algorithm which is shown to provide extremely good guidelines for setting safety stock levels.
A Cost-Based Methodology for Stochastic Line Balancing with Intermittent Line Stoppages
Authors: Silverman Fred N. , Carter John C.
Published: November 2008

This paper examines the effect of stochastic task times on the total operating costs of a continuously paced assembly line under the assumption that the line is stopped whenever at least one work station requires more time than allotted. A comprehensive stochastic cost function is integrated into an efficient balancing algorithm to enable an approximately minimum cost balance to be obtained. An experiment was conducted to determine the cost savings resulting from using the stochastic method as compared to two deterministic methods. The stochastic method of this paper produced lower cost balances in most cases studied.
Determining Organizational Effectiveness: Another Look, and an Agenda for Research
Authors: Lewin Arie Y. , Minton John W.
Published: November 2008

Concern with the effectiveness, productivity, efficiency or excellence of organizations is a subject that has motivated the writings of economists, organization theorists, management philosophers, financial analysts, management scientists, consultants, and practitioners. It has served as a unifying theme for over a century of research on the management and design of organizations, yet the empirical research has not contributed to the development of a universal theory of organizational effectiveness. In this paper we review the extent to which the components of a contingent behavioral theory of organizational effectiveness already exist, one that incorporates the paradoxes and tradeoffs inherent in real life organizations. We consider the problem of effectiveness measurement, and we propose a research approach utilizing a strategy of engineering organizational effectiveness which could lead to an inductive, applied, empirically-based theory of contingent organization design. In this context the engineering of organizational effectiveness has a dual purpose. For the organizations and their managers participating in the research, it refers to understanding, constructing and managing organizational activities in given contexts so as to achieve and maintain improved performance as measured by one or more situationally-determined criteria. In addition, to provide the empirical basis from which induction can proceed, the engineered events must be structured and implemented in such a way so as to facilitate theory construction and testing.
Organizational Information Requirements, Media Richness and Structural Design
Authors: Daft Richard L. , Lengel Robert H.
Published: November 2008

This paper answers the question, “Why do organizations process information?” Uncertainty and equivocality are defined as two forces that influence information processing in organizations. Organization structure and internal systems determine both the amount and richness of information provided to managers. Models are proposed that show how organizations can be designed to meet the information needs of technology, interdepartmental relations, and the environment. One implication for managers is that a major problem is lack of clarity, not lack of data. The models indicate how organizations can be designed to provide information mechanisms to both reduce uncertainty and resolve equivocality.
The Decision-Making Paradigm of Organizational Design
Authors: Huber George P. , McDaniel Reuben R.
Published: November 2008

This paper introduces and explicates the decision-making paradigm of organizational design. We argue that the domains of existing design paradigms are declining in scope, and that the nature of current and future organizational environments requires use of a design paradigm that responds to the increasing frequency and criticality of the decision-making process. In particular, we argue that the decision-making paradigm is applicable when the organizational environments are hostile, complex, and turbulent.

The focal concept of the decision-making paradigm is that organizations should be designed primarily to facilitate the making of organizational decisions. The paper sets forth the paradigm's six major concepts and discusses the principal domains of its application. The paper also examines the relationships between the decision-making paradigm and the literatures on (1) organizational decision making, (2) the information processing view of organizations, and (3) the need for compatibility between the organization's design and the design of its technologically supported information systems. The paper concludes by identifying ten organizational design guidelines that follow from the decision-making paradigm.
On the Minimum Violations Ranking of a Tournament
Authors: Ali Iqbal , Cook Wade D. , Kress Moshe
Published: November 2008

This paper examines the problem of rank ordering a set of players or objects on the basis of a set of pairwise comparisons arising from a tournament. The criterion for deriving this ranking is to have as few cases as possible where player i is ranked above j while i was actually defeated by j in the tournament. Such a situation is referred to as a violation. The objective, therefore, is to determine the Minimum Violations Ranking (MVR). While there are situations where this ranking would be allowed to contain ties among subsets of objects, we will concern ourselves herein with linear ordering (no ties). A series of examples are given where this requirement would seem to be appropriate. In order to put the MVR problem into proper perspective we introduce the concept of a distance on the set of tournaments. A set of natural axioms is presented which any such distance measure should obey, and it is proven that in the presence of these axioms a unique such measure exists. It is then shown that the MVR problem is equivalent to the minimum distance problem, which can be represented in several forms—in particular as a problem of determining the minimum feedback edge set in a graph and as a mixed integer generalized network problem. This opens up a wide scope of possible solution procedures for the MVR problem. An optimal algorithm is presented along with computational results. In addition, various heuristics are discussed including an improved heuristic referred to as the Iterated Kendall method.
A Stochastic Inventory Model Incorporating Intra-Year Purchases and Accounting Tax Incentives
Authors: Biddle Gary C. , Martin R. Kipp
Published: November 2008

It has been observed that firms alter year-end inventory policies in response to accounting tax incentives. This study proposes a stochastic ordering policy model which quantifies these effects. An innovative feature is its use of two decision variables: an initial order-up-to-level at the beginning of each year and a desired year-end inventory level. The ability to place a second order after demand has been assessed allows for an explicit consideration of the effects of tax incentives on order quantity decisions. Separate formulations are developed for the two most widely-used inventory accounting methods, LIFO and FIFO. The model provides new implications for choices between LIFO and FIFO, the forms of optimal ordering policies under each and for year-end inventory levels. A procedure is given for calculating the optimal FIFO policy. Calculating optimal LIFO policies is very difficult so myopic approximate policies are given which bound the optimal policy.
Axiomatic Foundation of the Analytic Hierarchy Process
Authors: Saaty Thomas L.
Published: November 2008

This paper contains an axiomatic treatment of the Analytic Hierarchy Process (AHP). The set of axioms corresponding to hierarchic structures are a special case of axioms for priority setting in systems with feedback which allow for a wide class of dependencies. The axioms highlight: (1) the reciprocal property that is basic in making paired comparisons; (2) homogeneity that is characteristic of people's ability for making comparisons among things that are not too dissimilar with respect to a common property and, hence, the need for arranging them within an order preserving hierarchy; (3) dependence of a lower level on the adjacent higher level; (4) the idea that an outcome can only reflect expectations when the latter are well represented in the hierarchy. The AHP neither assumes transitivity (or the stronger condition of consistency) nor does it include strong assumptions of the usual notions of rationality. A number of facts are derived from these axioms providing an operational basis for the AHP.
An Adaptive Filter for Estimating Spatially-Varying Parameters: Application to Modeling Police Hours Spent in Response to Calls for Service
Authors: Foster Stuart A. , Gorr Wilpen L.
Published: November 2008

The Spatial Adaptive Filter (SAF), introduced in this paper, uses generalized damped negative feedback to estimate spatially-varying parameters for multivariate models. Previous adaptive filters have been designed to estimate time-varying parameters and process data recursively in time sequence. SAF processes all data simultaneously in an iterative algorithm. Monte Carlo studies show that SAF is successful in automatically identifying and estimating step-jump and continuous spatial variation in the parameters of causal variables. A case study on census-tract data from Columbus, Ohio, relating police-vehicle hours spent in responding to calls to socio-economic indicators, has systematic spatial variation in estimated parameters. Independent variables that are significant in inner-city areas of Columbus become progressively less significant in moving to outlying areas.
Flexible Manufacturing Systems: A Review of Analytical Models
Authors: Buzacott J. A. , Yao David D.
Published: November 2008

This paper reviews recent work on the development of analytical models of Flexible Manufacturing Systems (FMSs). The contributions of each of the groups concerned with model development are summarized and an assessment is made of the strengths and weaknesses of its modelling approach. A number of directions in which models require extension are outlined, in particular the representation of such aspects of FMS operation as the tool delivery systems, the blocking phenomenon, the transient behavior and the differences between flexible machining systems and flexible assembly systems. Further work is also required on the structure of FMS control and the integration with plant production planning and control.
Game Theory and Cost Allocation Problems
Authors: Tijs S. H. , Driessen T. S. H.
Published: November 2008

Problems of allocating joint costs in a reasonable way arise in many practical situations where people decide to work together to save costs. Cost allocation methods based on game theoretical concepts take into account the strategic aspects of cost allocation situations. We give a survey of cost allocation methods based on the nucleolus and the Shapley value, and introduce also a new one, the so-called cost gap allocation method which is based on the τ-value. It is shown that for some large subclasses of cost allocation problems this new cost allocation method coincides with old separable cost methods proposed in the thirties by the Tennessee Valley Authority and also with the separable costs-remaining benefits (SCRB) method. Properties of this cost gap allocation method are also treated.
Searching for Positive Returns at the Track: A Multinomial Logit Model for Handicapping Horse Races
Authors: Bolton Ruth N. , Chapman Randall G.
Published: November 2008

This paper investigates fundamental investment strategies to detect and exploit the public's systematic errors in horse race wager markets. A handicapping model is developed and applied to win-betting in the pari-mutuel system. A multinomial logit model of the horse racing process is posited and estimated on a data base of 200 races. A recently developed procedure for exploiting the information content of rank ordered choice sets is employed to obtain more efficient parameter estimates. The variables in this discrete choice probability model include horse and jockey characteristics, plus several race-specific features. Hold-out sampling procedures are employed to evaluate wagering strategies. A wagering strategy that involves unobtrusive bets, with a side constraint eliminating long-shot betting, appears to offer the promise of positive expected returns, even in the presence of the typically large track take encountered at Thoroughbred racing events.
Search Theory and the Manufacturing Progress Function
Authors: Muth John F.
Published: November 2008

A theory based upon random search within a fixed population of technological possibilities is used to explain the manufacturing progress function. The theory is consistent with the power function relation between unit costs and cumulative output that has frequently been observed. It is also consistent with initial rates of improvement smaller than those predicted later by the power function relation, the eventual cessation of cost reduction, and an irregularity of improvements. Existing theories in the literature either fail to agree with the main empirical phenomena or else assume precisely what they attempt to explain.
Arbitrating a Dispute: A Decision Analytic Approach
Authors: Eliashberg Jehoshua
Published: November 2008

Many collective decision-making and bargaining situations can be described through the set of the feasible joint evaluations of all conceivable settlements. Attention should then be restricted to that subset (Pareto-optimal frontier) from which no joint gains are possible. Hence, the focal issue becomes which element of the Pareto-optimal subset should be chosen as a solution to the dispute. This paper proposes an arbitration procedure to address this issue. The proposed approach, decision-analytic in its nature, is inspired by LaValle’s (LaValle, I. H. 1978. Fundamentals of Decision Analysis. Holt, Rinehart and Winston, New York.) allocation-function approach (which is not specific on how to obtain an allocation function) and by Eliashberg and Winkler's (Eliashberg, J., R. L. Winkler. 1981. Risk sharing and group decision making. Management Sci. 27 (November) 1221–1235.) work (which does not accommodate probability differences within the group). After the new approach is presented, its implications are examined for some likely scenarios and examples are considered.
A Multiplier Adjustment Method for the Generalized Assignment Problem
Authors: Fisher Marshall L. , Jaikumar R. , Van Wassenhove Luk N.
Published: November 2008

We describe a branch and bound algorithm for the generalized assignment problem in which bounds are obtained from a Lagrangian relaxation with the multipliers set by a heuristic adjustment method. The algorithm was tested on a large sample of small random problems and a number of large problems derived from a vehicle routing application. Computation times were reasonable in all cases and the branch and bound trees generated had nearly two orders of magnitude fewer nodes than for competing algorithms. Although comparison of running times on different machines is difficult, the multiplier adjustment method appears to be about one order of magnitude faster than the best previously existing algorithms for this problem.
The Multiregion Dynamic Capacity Expansion Problem: An Improved Heuristic
Authors: Fong C. O. , Srinivasan V.
Published: November 2008

We consider the problem of determining a schedule of capacity expansions for m producing regions and a schedule of shipments from the regions to n markets so as to meet market demands over a T-period planning horizon at minimum discounted capacity expansion and shipment costs. The proposed algorithm permits capacity expansion costs to be arbitrary nonnegative increasing functions of the expansion amounts, but the shipment (and production) costs are restricted to be proportional to the amounts shipped. The algorithm does not require market demands to be increasing over time. The cost functions are allowed to be nonstationary and the possibility of imports is considered. The proposed heuristic algorithm improves on feasible solutions by simultaneously reassigning several capacity expansions to different regions and/or time periods. A look-ahead feature prevents the algorithm from becoming myopic and a self-learning feature dynamically updates computational parameters. The heuristic algorithm was tested on both randomly generated and real-life based problems with m ≤ 15, and n ≤ 15 and T ≤ 25. The test problems had increasing market demands, capacity expansion costs specified in the form of a concave power function or a fixed charge plus linear function, stationary costs (aside from a constant discount factor), and no imports. Results indicate that for the class of problems tested, the heuristic algorithm is computationally efficient and provides solutions that are closer to optimum than those obtained by previous algorithms.
Optimal Capacity Expansion Planning When There are Learning Effects
Authors: Hiller Randall S. , Shapiro Jeremy F.
Published: November 2008

Production and capacity expansion decisions are difficult to analyze when there is learning. Later production is less costly, and maybe more profitable, but the company must endure high initial production costs. Mixed integer programming models are presented for optimizing coordinated production and capacity expansion plans in the face of such learning effects. An illustrative model is developed, optimized, and the types of strategies it selects are discussed.
A Generalized Quantity Discount Pricing Model to Increase Supplier's Profits
Authors: Lee Hau L. , Rosenblatt Meir J.
Published: November 2008

In this paper, the joint problem of ordering and offering price discount by a supplier to his sole/major buyer is analyzed. The objective is to induce the buyer to alter his order schedule and size so that the supplier can benefit from lower set up, ordering, and inventory holding costs. We generalize the quantity discount pricing model of Monahan (Monahan, J. P. 1984. A quantity discount pricing model to increase vendor profits. Management Sci. 30 (6) 720–726.) to: (1) explicitly incorporate constraints imposed on the amount of discount that can be offered; and (2) relax the implicit assumption of a lot-for-lot (or order-for-order) policy adopted by the supplier. An algorithm is developed to solve the supplier's joint ordering and price discount problem.
Forecasting Error Evaluation in Material Requirements Planning (MRP) Production-Inventory Systems
Authors: Lee T. S. , Adam Everett E.
Published: November 2008

The impact of forecasted demand and forecast error, introduced in the Master Production Schedule, upon Material Requirements Planning (MRP) Systems is investigated. A computerized simulation was built to examine several questions. Results indicate that forecasting error, especially the mean error, does impact MRP system inventory costs and shortages; the greater the forecast error the greater the shortages. An exception to this general relationship was that a slight forecast BIAS may improve MRP system performance, which was the case for systems studied herein. Lot-sizing rules and product structure (bill of material structure) were also found to impact total MRP system inventory costs and shortages. The more complicated the MRP structure, the greater the differentiation among lot-sizing rules and the greater the cost impact of forecast errors. A good lot-sizing rule appears to be the period order quantity rule. However, as the forecast error level gets higher, it becomes difficult to select the better lot-sizing rule. Based on this study, suggestions are presented for the production manager's consideration, especially the inventory-production control manager.
Counting Your Customers: Who-Are They and What Will They Do Next?
Authors: Schmittlein David C. , Morrison Donald G. , Colombo Richard
Published: November 2008

This article is concerned with counting and identifying those customers who are still active. The issue is important in at least three settings: monitoring the size and growth rate of a firm's ongoing customer base, evaluating a new product's success based on the pattern of trial and repeat purchases, and targeting a subgroup of customers for advertising and promotions. We develop a model based on the number and timing of the customers' previous transactions. This approach allows computation of the probability that any particular customer is still active. Several numerical examples are used to illustrate applications of the model.
Kanban, MRP, and Shaping the Manufacturing Environment
Authors: Krajewski Lee J. , King Barry E. , Ritzman Larry P. , Wong Danny S.
Published: November 2008

There has been a great deal of interest recently in the Japanese approach to manufacturing, growing out of a concern for finding ways to reduce inventories and increase productivity. At this project's inception, its objective was to assess whether the kanban system could perform well in the manufacturing environments found in this country. Based on observations from managers visiting Japan, the project was enlarged to also assess which factors in a production environment have the biggest impact on performance—regardless of the system in use.

Guided by a panel of production and inventory managers from diverse plant environments, a comprehensive list of factors thought most important to manufacturing effectiveness was constructed. The panel established low and high values for each one. These settings were considered representative of the range experienced in U.S. plant environments. The factor settings allowed a variety of representative plants to be tested with a large scale simulator. Results show that kanban, when implemented in certain environmental settings, does indeed perform exceptionally well. However, so do the more traditional systems used in the United States. Conversely, there are other plant environments in which all systems perform much worse. This suggests that the factors themselves are the keys to major improvement. Simultaneously reducing setup times and lot sizes is found to be the single most effective way to cut inventory levels and improve customer service. Shop factors of particular importance are yield rates and worker flexibility. Degree of product standardization and the product structure are also high impact factors. Less crucial than earlier believed, at least over the factor settings simulated, are inventory record inaccuracy, equipment failures, and vendor reliability. Such results suggest that the selection of a production/inventory system can be of less importance than the improvement of the manufacturing environment itself.
An Algorithm for Technology Choice in Local Area Network Design
Authors: Marucheck Ann S. , Sulek Joanne M.
Published: November 2008

Technological advances in both the manufacturing and office sectors have emphasized the need to link processors and communications equipment into Local Area Networks (LANs) to facilitate communication and promote resource sharing. Interviews with designers and users of LANs revealed that a primary problem in the acquisition of a LAN is making technology choices in a cost effective manner when the available technologies and their costs are constantly changing. Since no standards for technology choice currently exist and user demand is expected to increase, system flexibility is also an important concern. The problem of technology choice is formulated as a dynamic integer program. Because of the numerous combinations of technology and network configuration pairings, the Sweeney-Tatham reduction method is utilized to reduce the problem to a computationally tractable size. Finally, the formation is applied to the actual case of an institutional user seeking to network 29 buildings. The resulting reduced problem can be solved on a microcomputer as a shortest path problem.
A Methodology for Determining a Hospital's Expected Costs for Changes in Patient Load and Service Mix
Authors: Duchessi Peter
Published: November 2008

This paper describes a methodology that demonstrates how specific types of patient/cost data can be used to construct a model that predicts the expected increase or decrease in costs associated with a change in patient load, expansion of an existing patient service department, closure of an existing patient service department, or installation of a specific patient service department. Data from a group of New York State hospitals are used to illustrate the development of the model's components that produce cost estimates. A computer-based model is used to demonstrate the methodology's application to a specific hospital. Additionally, a number of program runs that simulate the cost impact of patient load and/or service mix changes are presented. Finally, the methodology's potential management and regulatory applications are discussed.
The Multilocation Multiperiod Inventory Problem: Bounds and Approximations
Authors: Karmarkar Uday S.
Published: November 2008

The multilocation inventory problem can be thought of naturally as an extension of the single location “newsboy” problem to multiple locations with transshipment possible between locations. Previous work has established the form of optimal policies; however, computational results have been limited to the one-period case or to special structures. This paper develops lower- and upper-bounds for the general multiperiod problem. These also suggest approximations to the optimal solution. Computational methods are discussed and tested on small problems.
Setting Planned Leadtimes in Serial Production Systems with Tardiness Costs
Authors: Yano Candace Arai
Published: November 2008

We investigate the problem of determining optimal planned leadtimes in serial production systems in which the actual procurement and processing times may be stochastic. The objective is to minimize the sum of inventory holding costs and job tardiness costs given a customer specified due-date. We present a general solution procedure for two stage serial systems, which for most cost structures and leadtime distributions is a single-pass algorithm. We also indicate how the procedure can be extended to N-stage systems. We present computational results which provide some insight into the characteristics of optimal safety time policies.
Lottery Dependent Utility
Authors: Becker Joao L. , Sarin Rakesh K.
Published: November 2008

In this paper we propose a model for decision making under risk that is capable of predicting empirically observed preference patterns that have been found to be incompatible with the expected utility model. The model departs from the classical expected utility model by allowing utilities to depend on the lottery. The dependence of utilities on the lottery being evaluated is achieved by restricting the utility measure to a convenient parametric family of functions. The idea then is to use each lottery to determine a specific parameter value thus characterizing the utility function for each particular lottery. The expected value of this lottery dependent utility function provides the overall measure of preference. The model retains the properties of transitivity, stochastic dominance, and continuity. It also permits types of analyses, such as exploitation of basic attitudes toward risk through risk aversion properties, that have been found useful in decision theory.

The primary use of our model is in descriptive or predictive research and applications. For some decision makers who wish to retain the preference patterns that are incompatible with the substitution principle, even after the implications of their choices are made transparent, our model could be of prescriptive use as well.
The Theory of Ratio Scale Estimation: Saaty's Analytic Hierarchy Process
Authors: Harker Patrick T. , Vargas Luis G.
Published: November 2008

The Analytic Hierarchy Process developed by Saaty (Saaty, T. L. 1980. The Analytic Hierarchy Process. McGraw-Hill, New York.) has proven to be an extremely useful method for decision making and planning. However, some researchers in these areas have raised concerns over the theoretical basis underlying this process. This paper addresses currently debated issues concerning the theoretical foundations of the Analytic Hierarchy Process. We also illustrate through proof and through examples the validity or fallaciousness of these criticisms.
Optimal Group Maintenance Policies with Continuous and Periodic Inspections
Authors: Assaf David , Shanthikumar J. George
Published: November 2008

Optimum group maintenance policies for a set of N machines subjected to stochastic failures under continuous and periodic inspections are considered. Under very general conditions it is shown that a control limit policy minimizes the expected cost per unit time over an infinite horizon, when costs are incurred due to loss of production and repair only. It is also shown how to explicitly compute this control limit. When additional costs are incurred due to inspection, a characterization of an optimal periodic inspection/repair policy that minimizes the expected cost per unit time over an infinite horizon is given.
Design and Operation of a Multicommodity Production/Distribution System Using Primal Goal Decomposition
Authors: Brown Gerald G. , Graves Glenn W. , Honczarenko Maria D.
Published: November 2008

An optimization-based decision support system has been developed and used by NABISCO to manage complex problems involving facility selection, equipment location and utilization, and manufacture and distribution of products such as the familiar Ritz Crackers, Oreo Cookies, Fig Newtons, etc. (all product names trademarks of NABISCO). A mixed-integer, multi-commodity model is presented for the problems at hand, and a new class of goal decompositions is introduced to yield pure network subproblems for each commodity; the associated master problems have several notable properties which contribute to the effectiveness of the algorithm. Excellent quality solutions for problems with more than 40,000 variables (including several hundred binary variables with fixed charges) and in excess of 20,000 constraints require only 0.6 megabytes region and less than one compute minute on a time-shared IBM 3033 computer; average problems (with fewer binary variables) require only a second or two. The solution method has more to recommend it than sheer efficiency: new insights are given for the fundamental convergence properties of formal decomposition techniques. Several applications of this powerful interactive tool are discussed.
A Heuristic Approach to Product Design
Authors: Kohli Rajeev , Krishnamurti Ramesh
Published: November 2008

A dynamic-programming heuristic is described to find approximate solutions to the problem of identifying a new, multi-attribute product profile associated with the highest share-of-choices in a competitive market. The input data consist of idiosyncratic multi-attribute preference functions estimated using conjoint or hybrid-conjoint analysis. An individual is assumed to choose a new product profile if he/she associates a higher utility with it than with a status-quo alternative. Importance weights are assigned to individuals to account for differences in their purchase and/or usage rates and the performance of a new product profile is evaluated after taking into account its cannibalization of a seller's existing brands. In a simulation with real-sized problems, the proposed heuristic strictly dominates an alternative lagrangian-relaxation heuristic in terms of both computational time and approximation of the optimal solution. Across 192 simulated problems, the dynamic-programming heuristic identifies product profiles whose share-of-choices, on average, are 98.2% of the share-of-choices of the optimal product profile, suggesting that it closely approximates the optimal solution.
Dynamic Patent Races with Risky Choices
Authors: Park Jaesun
Published: November 2008

This paper investigates equilibrium R&D investment strategies of firms endowed with different innovation potentials. To address this issue, this paper permits two stages of innovation and develops a simple stochastic game model involving two firms. It is shown that in equilibrium, a leader in the multiple stage innovation game invests more than a follower; firms compete more vigorously in the later stages of innovation than in the earlier stages; and a follower is more likely to choose a riskier innovation path than one requiring, on average, equivalent effort. It provides an explanation of how the expected benefits, the cost of R&D, and interactions between competing firms combine to determine dynamic R&D strategies over time.
The Optimal Treatment Strategy—A Patient's Perspective
Authors: Mehrez A. , Gafni A.
Published: November 2008

In this paper we present a general model that enables us to better understand the decision of a patient whether or not to participate in a treatment, and, if so, the optimal timing for the treatment, from his point of view. The model takes into account both “objective information” which represents medical technology as well as “subjective information” which represents the patient's preference. By doing so it is attuned to the school of thought that medical care is not required for its own sake but for the sake of its effect on health as perceived by the patient himself. The framework presented is used to analyze the optimal decision for the individual for several different cases: One disease-one treatment; one disease-several alternative treatments; many diseases-many treatments; direct payment vs. full insurance; and the effect of the possible future introduction of a better treatment. The optimal decision of treatment for the individual is also analyzed under different assumptions in relation to the parameters. For example, both quality of life in a state of disease and the probability of success of the treatment are constant versus the case where both decrease over time; the comparison between the use of population and individual mortality rates by individuals for decision making; and treatment affecting only quality of life vs. treatment which also affects the individual's life span. The most common decision that results from our model (especially when treatment affects only quality of life) is a bang-bang solution. That is, the optimal timing of a treatment is now or never.
Note—Comment on: A Generalized Quantity Discount Pricing Model to Increase Supplier's Profits
Authors: Goyal S. K.
Published: November 2008

Lee and Rosenblatt (Lee, H. L., M. J. Rosenblatt. 1986. A generalized quantity discount pricing model to increase supplier's profits. Management Sci. 32 (9) 1177–1185.) considered the joint problem of ordering and offering discount by a supplier to his sole buyer, the objective of the supplier being to induce the buyer to alter his order quantities in order to increase the supplier's yearly profit. They determined the optimal ordering and pricing policy for the supplier under the constraint on the amount of discount offered to the purchaser. This restriction on the amount of price discount seems unreasonable when the objective of the supplier, in all likelihood, is to increase his own profits. It is possible that higher discounts in purchase price may lead to greater economies for the supplier. In this note, a much simpler approach is being offered for determining the optimal ordering and pricing policy for the supplier.
Cognitive Process as a Basis for MIS and DSS Design
Authors: Ramaprasad Arkalgud
Published: November 2008

Cognitive process research can provide specific, operational guidelines for MIS/DSS design by delineating the specific influences on managers' cognitive processes in sensing, formulating, and solving problems. The paper integrates some of the considerable body of literature on these processes in the framework of Piaget's model to illustrate the type of guidelines cognitive process research can provide. It also delineates three topical areas for future research: (a) Choice of Logico-Mathematical-Structures (LMSs), (b) Development of LMSs, and (c) Application/Attribution of LMSs to sense, formulate and solve problems, and describes how research in these areas can help improve the effectiveness of MIS/DSS.
Uncertainty, Competition, and the Adoption of New Technology
Authors: Mamer John W. , McCardle Kevin F.
Published: November 2008

Faced with the decision of whether or not to adopt a new technology whose economic value cannot be gauged with certainty, the manager of the firm may elect to decrease the uncertainty by sequentially gathering information (at a unit cost of c > 0), updating his prior beliefs in a Bayesian manner. Uncertainty regarding the actions of a competitor, however, cannot be reduced. Our model allows a manager to account for potential competition, either substitute or complementary, by inclusion of strategic considerations modelled in a game theoretic setting. We show that the firm's best response mapping satisfies a dynamic programming recursion (even when the one period reward function is unbounded) providing management with a familiar tool to solve its problem. Best response behavior is characterized by a monotone sequence of pairs of threshold numbers which give rise to a “cone-shaped” continuation region. The continuation region is shown to shift up (down) with increases in the expected level of substitute (complementary) competition making the firm less (more) likely to adopt the innovation. Finally, the existence of a Nash equilibrium in cone-shaped strategies is established.
Analysis of a Two-Echelon Inventory Control System with Complete Redistribution
Authors: Jönsson H. , Silver E. A.
Published: November 2008

This paper examines a two-level distribution system consisting of a central warehouse (CW) supplying several branch warehouses (BW's), which, in turn, supply normally-distributed customer demands in a periodic-review environment. The CW replenishes system inventory using a base-stock replenishment policy and a predetermined order cycle of H time periods; i.e., every H periods, the CW orders enough from an outside supplier to bring the systemwide inventory position to a certain level (to be determined) based on a given minimum level of customer service. Upon receipt of this order, the CW allocates it entirely to the BW's so as to minimize the expected total units short at the BW's. This simple allocation scheme, may, of course, lead to out-of-balance BW inventories towards the end of the CW's order cycle. Hence, redistribution during the cycle should be considered. The redistribution treated here is a complete redistribution of all BW inventories one period before the end of the order cycle. Approximate formulas are derived which allow for a comparison of the system-wide inventories appropriate to each of two allocation schemes: (1) the simple allocation scheme only; and (2) the simple allocation scheme with total redistribution one period before the end of the order cycle. Limited computational tests indicate the magnitude of the improvements possible with total redistribution, and the sensitivities of these improvements to model parameters.
Institutionalization of a Management Science Innovation in Police Departments
Authors: Lawless Michael W.
Published: November 2008

The adoption of management science models has typically been studied in time frames of less than two years. Recommendations of government decisionmakers for improving the likelihood of successful model development, diffusion, and adoption have been based on these studies. Yet some factors important to the use of models do not emerge in the short term. This study examines model use over a longer time frame, and draws some policy implications. A survey was taken of 17 police departments live years after they implemented PCAM, the Patrol Car Allocation Model. Utilization (extent of use) and institutionalization (extent of organizational adaptation) were evaluated. Overall, there were few signs that use of PCAM had a major impact on the state of police patrol allocation. PCAM was found to be operational in six departments, and fully institutionalized in two. Based on patterns of use and nonuse, recommendations are made to enhance the long-term impact of future modeling projects. Among them are to survey user needs and give them a larger role in model development, to design models capable of an expanded range of tasks and of running on personal computers, and to include performance evaluation and feedback in all model-building projects. A structured approach to development is suggested to anticipate implementation and institutionalization problems, and to produce integrated solutions.
Scheduling Ocean Transportation of Crude Oil
Authors: Brown Gerald G. , Graves Glenn W. , Ronen David
Published: November 2008

A crude oil tanker scheduling problem faced by a major oil company is presented and solved using an elastic set partitioning model. The model takes into account all fleet cost components, including the opportunity cost of ship time, port and canal charges, and demurrage and bunker fuel. The model determines optimal speeds for the ships and the best routing of ballast (empty) legs, as well as which cargos to load on controlled ships and which to spot charter. All feasible schedules are generated, the cost of each is accurately determined and the best set of schedules is selected. For the problems encountered, optimal integer solutions to set partitioning problems with thousands of binary variables have been achieved in less than a minute.
On the Evaluation of Compound Options
Authors: Selby Michael J. P. , Hodges Stewart D.
Published: November 2008

Compound option valuation formulae give rise to the summation of a series of multinormal distribution functions. This paper presents an identity on sums of nested multinormal distributions of arbitrary dimension. We show that this identity generalizes some well-known low order identities for the multinormal distribution. We present three applications of the new identity to contingent claims valuation problems. The first and second applications show that by reducing significantly the number of integrals to be evaluated, faster and more accurate algorithms can be developed for implementing the Geske-Johnson American put valuation formula and the Roll-Geske-Whaley American call formula; the third gives new economic insights into the valuation of disaggregated coupon bonds.
Combining Overlapping Information
Authors: Clemen Robert T.
Published: November 2008

A decision maker trying to learn about an uncertain quantity may obtain divergent information from a number of sources (e.g., experts). In this paper we study the decision maker's problem of aggregating this information to form his posterior distribution when he believes that the experts' opinions are dependent due to shared information. Examples in both normal and Bernoulli frameworks lead to some surprising general insights regarding the impact of the dependence on the posterior distribution. The study has implications for practitioners who face real-world information-aggregation problems and for groups of experts who seek a consensus.
Analyzing Tenant Assignment Policies
Authors: Kaplan Edward H.
Published: November 2008

This paper discusses two popular policies used by housing authorities to assign applicants to housing projects: first available unit and priority assignment policies. The policies are compared according to their abilities to integrate housing projects, applicant assignment probabilities, and mean waiting times. Our results show that priority policies can successfully integrate public housing projects while first available unit policies can exacerbate segregation. These results support the reported empirical performance of these policies. We briefly consider the time necessary to reach steady state for these policies; this is one point of departure for further research.
Lot Sizes, Lead Times and In-Process Inventories
Authors: Karmarkar Uday S.
Published: November 2008

In many manufacturing problems, the total lead time taken to manufacture a product is an important consideration. Long lead times impose costs due to higher work-in-process inventory, increased uncertainty about requirements, larger safety stocks and poorer performance to due dates. Traditional lot sizing models ignore lead time related costs, although there are systematic relationships between lot sizes and lead times. This paper examines these relationships and their implications for lot sizing and work-in-process inventories, for batch manufacturing shops with queues.