bluuebunny/crossref_metadata_2025 huggingface dataset:
Queueing Models of Community Correctional Centers in the District of Columbia
Authors: Harris Carl M. , Thiagarajan T. R.
Published: November 2008

This paper describes the use of GI/M/c and heavy-traffic GI/G/c queues for modeling the utilization of community correctional centers or halfway houses in the District of Columbia. These models arise by considering each bed of a total of c in a facility as, a service channel providing random amounts of service to a constant stream of arrivals. The results have been used to provide decision-makers with means to evaluate facility use. The ultimate strategies are to be based on a subjectively chosen “optimal” balance between customer waiting time to get into the center and relative traffic intensity.
Group Decisions in the Face of Differences of Opinion
Authors: Bacharach Michael
Published: November 2008

Suppose a number of honest, intelligent individuals differ in their rankings of a set of possible actions. They may do so because they have difierent objectives, or they may do so solely because they disagree about what are the probable outcomes of the acts. The latter is the relevant case if they are acting disinterestedly as consultants. In this case how should the actions be ranked by the executive? Here the essential problem is that of “consensus theory”—to find a reasonable way of resolving the experts' differences of opinion about the facts (the circumstances determining the outcomes).

To tackle this problem we enlarge it. We pose the problem mathematically in an abstract form which encompasses a very wide range of hypothetical cases, allowing small and big differences over objectives (utilities) as well as over probability assessments (of the facts). We then look for general rules for generating a group ranking for the acts which would simultaneously satisfy axioms referring to varying extreme cases. On certain assumptions the group ranking of acts implies an underlying consensus about the facts.

The object of the paper is to show which axioms of group choice lead to which formulas for consensus. The paper arrives at both positive and negative results. Under two alternative sets of appealing axioms, the group's implicit consensus is given as a linear opinion pool; the consensual probabilities are weighted averages of the individuals' ones. On the other hand, under a third set of reasonable axioms, the group ranking cannot be arrived at by any rules for separately combining the probabilities and combining the utilities. However, this “impossibility” result depends on wanting the rule to work for cases of extreme differences over rankings of acts.
An Integrated Model for Accounts Receivable Management
Authors: Lieber Zvi , Orgler Yair E.
Published: November 2008

The purpose of this paper is to present an integrated model of accounts receivable. The model incorporates the major components of credit and collection policies such as the cash discount, credit period and charges for late payments. It considers the investment in accounts receivable, losses from bad debts and the impact of credit terms on sales. The objective is to maximize the present value of net earnings from accounts receivable. After deriving the general model, a simplified version is solved by classical optimization techniques under various sets of assumptions that are gradually relaxed.
Policy Making Under Discontinuous Change: The Situational Normativism Approach
Authors: Shakun Melvin F.
Published: November 2008

Policy making under conditions of discontinuous change is discussed in terms of situational normativism, a descriptive-normative approach to policy making systems. Under such conditions, norms and values play a key role in the adaptation of the system. The nature of norms and values within situational normativism is discussed, and implications for system adaptation are explored. Aspects of policy, strategy, planning and system design are considered. A behavioral model for purposeful search and adaptation under discontinuity is presented. At the policy level a referral process is described which allows for change with respect to the set of operational goal variables. This involves referral between operational goals and nonoperational goals (values) and norms. The use of the model in the situational normativism approach to planning under discontinuity is discussed.
Comparative Evaluation of Two Sets of Social Indicators
Authors: Malizia Emil E.
Published: November 2008

An earlier and a subsequent study which constructed two sets of social indicators for Charlotte, N.C. during the past two years are here examined and compared as part of an effort directed to the development of a general methodological approach for synthesizing and selecting between various indicators at local government levels. Five measurement tests are used to compare the two sets. The tests are based upon two criteria: correspondence and correctness. Four tests apply the former criterion; one test applies the latter. Although the results show the superiority of the more recent study, the more essential purpose is to illustrate a potentially useful approach to evaluating social indicators which is independent of the local public policy making process and is amenable to computerization. Although many of the tests employed cannot be brought to a completely satisfactory resolution at the present moment, the evaluation methodology can be regarded as a start toward a needed approach to assist systems analysts and local officials concerned with municipal information systems in constructing more reliable and accurate social indicators.
An Alternate Approach to Indicator Development
Authors: Flax Michael J.
Published: November 2008

In the previous paper Professor Malizia develops two tests (“correspondedness” and “correctness”) and uses them for comparing two sets of indicators. He seeks an “evaluation methodology which is ‘objective’ in that it does not depend upon the attitudes of managers or public officials.” Here, a different approach to the problem of evaluating or designing indicators is suggested. Rather than attempting to design multi-purpose indicators, one might deliberately seek to match indicator specifications systematically to the requirements of different managers and public officials. The crucial technical refinements of data definition and measurement precision can then be undertaken in the context of a knowledge of the eventual usage of the indicators being developed.
Regression Analysis for Multiplicative Phenomena and its Implication for the Measurement of Investment Risk
Authors: Schneller Meir I.
Published: November 2008

Beta—the systematic risk—is generally accepted as a measure for the risk involved in holding a portfolio of risky securities. It will be shown in this paper that, because beta is measured by regressing one multiplicative variable (the rate of return of a security or a portfolio) on another multiplicative variable (the market), in the long run, the systematic risk will approach either zero or infinity. It will also be shown that in the long run the unsystematic risk will dominate the systematic risk, and that, regardless of the value of this latter risk. This implies that for investors with long planning horizon the information conveyed in the systematic risk of an investment is rather limited.
On the Linear Complementarity Problem
Authors: Rao Arza K.
Published: November 2008

Consider the linear complementarity problem given in the system: [Formula: see text] where, W, Z and q are vectors of dimension n. M is a matrix of order n × n and ZT is the transpose of Z. Any (Z, W) satisfying (1), (2), and (3) is a complementary feasible solution to system (I).

In the literature, a class of matrices is defined such that if M belongs to this class, then existence of a feasible solution to system (I) implies the existence of a complementary feasible solution to system (I) with W = 0. In this paper, a new class of matrices 𝔐 is developed. It is shown that membership of a matrix M in 𝔐 is equivalent to the property; for any q existence of a feasible solution to system (I) implies the existence of complementary feasible solution to system (I) for that q with W = 0. This new class of matrices is not contained in any one of the known classes, namely, copositive plus, positive definite or semidefinite, P-matrices, P-matrices, Z-class, etc.
Explicit Solutions in Convex Goal Programming
Authors: Charnes A. , Cooper W. W. , Klingman D. , Niehaus R. J.
Published: November 2008

Goal programming has now become an important tool in areas such as public management science. There is therefore a need for examining ways of securing improved computational efficiency, as is done in this paper, instead of resting only on the linear programming equivalences that were set forth when the original goal programming article was published in Vol. 1, No. 2 of Management Science. Based on lemmata which permit reduction of various important classes of convex goal programming models to problems of full row rank-interval programming type, explicit solutions to convex goal programming problems are exhibited. Some of the equivalences herein established are also useful in their own right and for other classes of problems—e.g., interval programming—as well as advanced start procedures and other such computational matters.
A Note on Information Value Theory for Experiments Defined Extensive Form
Authors: Ponssard Jean-Pierre
Published: November 2008

An experiment is defined as a random variable which may take some posterior probability distributions according to a marginal probability. Elementary properties of this definition with respect to information value theory are derived as well as their practical implications.
Optimal Operation of Public Lotteries
Authors: Perry Arnon , Soland Richard M.
Published: November 2008

Public lotteries form an important source of revenue for many national and state governments, but little quantitative effort has been applied to their efficient operation. We here formulate a model in which the net revenue per unit time from the operation of a lottery depends upon the prizes offered, the price charged per ticket, and the time interval between successive drawings. The model is solved for the optimal values of these decision variables, and some illustrative numerical results are presented.
Stochastic Dominance Tests for Selecting Acceptable Debt Issuance Strategies
Authors: Brooks Leroy D.
Published: November 2008

The use of the Stochastic Dominance (SD) ordering rules in selecting a set of acceptable debt issuance strategies is examined. A procedure for selecting among alternative strategies on both the timing of issuance and maturity composition of a portfolio of liabilities is formulated. An application of the SD rules provides an effective analytical alternative to subjective judgment in determining debt timing policy when there are uncertain future costs. The SD approach enables a choice of strategies where there are specific stated assumptions on the nature of the underlying utility functions; the decisions are not based on subjective estimates of utility. An application of the ordering rules to the debt timing decision requires the use of a solution procedure applicable to a multi-period case having nonstationary probability functions over time. An application of the model to a small sample problem indicates the information requirements, SD test results, and the evaluation of the tests.
Note—A Comment on Blau's Dilemma in “Stochastic Programming” and Bayesian Decision Analysis
Authors: Charnes A. , Cooper W. W.
Published: November 2008

Using what he calls a “Basic Chance Constrained Programming Model,” BCCM, R. A. Blau proceeds in Blau [Blau, R. A. 1974. Stochastic programming and decision analysis: an apparent dilemma. Management Sci. 21 (3, November) 271–276.] to derive some results which he believes lead to a dilemma in which EPVI, the Expected Value of Perfect Information, is less than EVSI, the Expected Value of Sample Information. This is one part of Blau's dilemma. In addition, EPVI and EVSI are both negative. This is the other part of Blau's dilemma, from which he goes on to a variety of philosophic and other objections that he believes relate to contrasts between Bayesian decision theory and other, more classic, approaches in statistics. The latter are, in turn, related to chance constrained programming, and so on, but in ways that are only adumbrated rather than developed in detail by Blau.
An Application of Queueing Theory to Reservation Newtorks
Authors: Driscoll M. F. , Weiss N. A.
Published: November 2008

This paper discusses the modeling and solution of a reservation network problem. The model is presented in terms of motel reservations, but is applicable to reservation systems for airlines, automobile rental agencies, etc. The network studied employs three methods for delivery of reservation messages, two of which serve jointly as a control mechanism. The problem solved is that of finding minimum rates for the control mechanism which ensure that, with a given probability, messages are delivered within a specified period of time.
Input Policies for a Longitudinal Manpower Flow Model
Authors: Grinold Richard C.
Published: November 2008

This paper formulates a general longitudinal manpower flow model and poses the problem of scheduling the inflow of manpower for an infinite number of periods subject to constraints on the stocks and inflows of manpower and the size of the manpower system. The objective is to minimize the present value of the costs of system operation. A finite linear program is introduced which can calculate a lower bound on the optimal value of the infinite problem. The optimal solution of the finite linear program can be used to construct a sound and easily implemented policy for the infinite problem.
A Hybrid Algorithm for the Computation of Fixed Points
Authors: Garcia C. B.
Published: November 2008

Given a continuous mapping of a simplex to itself, an algorithm is shown that generates an infinite sequence of points converging to a fixed point of the mapping. Taking advantage of a generalization of Sperners lemma, the proposed method generalizes those of Scarf and Eaves in a manner such that both methods are given a unifying formulation.
Industrial Market Forecasting with Anticipations Data
Authors: Rippe Richard , Wilkinson Maurice , Morrison Donald
Published: November 2008

A forecasting model for industrial markets is developed and illustrated that utilizes publicly available data on anticipated future capital spending and sales. The model is based upon input demand functions derived from a fixed coefficient production function. Since the proposed forecasting method is easy to implement and offers the prospect of reasonably accurate forecasts, it may serve not only as a principal forecast technique but also as a standard of performance against which more elaborate and costly procedures are judged.
An Interactive Programming Method for Solving the Multiple Criteria Problem
Authors: Zionts Stanley , Wallenius Jyrki
Published: November 2008

In this paper a man-machine interactive mathematical programming method is presented for solving the multiple criteria problem involving a single decision maker. It is assumed that all decision-relevant criteria or objective functions are concave functions to be maximized, and that the constraint set is convex. The overall utility function is assumed to be unknown explicitly to the decision maker, but is assumed to be implicitly a linear function, and more generally a concave function of the objective functions. To solve a problem involving multiple objectives the decision maker is requested to provide answers to yes and no questions regarding certain trade offs that he likes or dislikes. Convergence of the method is proved; a numerical example is presented. Tests of the method as well as an extension of the method for solving integer linear programming problems are also described.
Production-Inventory Decisions under Order-Occurrence Risk: The Deterministic Order Quantity Case
Authors: Jesse Richard R.
Published: November 2008

This paper examines the problem of production-inventory decisions under order-occurrence risk. To characterize this problem briefly, let the number of periods which elapse between the receipt of orders n and n + 1 for an item be described by a probability mass function fn(s). If fn(∞) > 0, then order-occurrence risk is said to exist. That is, upon receiving order n for an item, there exists a positive probability that no future orders will occur. Assuming deterministic order quantities, the order-occurrence risk problem is formulated as a dynamic program. Optimal production-inventory disposal policies are characterized for the case of piecewise-linear production-disposal costs and concave increasing holding costs. The production cost is assumed to include a setup cost, and demand backlogging is not permitted. The production and disposal lead times are assumed to be zero.
Dynamic Correction in Marketing Planning Models
Authors: Weinberg Charles B.
Published: November 2008

Most marketing planning models have carry-over effects in which one period's decisions influence the results obtained in future periods. In this paper it is shown that failure to allow for the carry-over effect beyond the planning horizon can result in underallocation of resources and in biases in the timing pattern of resource expenditure. For a wide class of market planning models, a procedure is developed to take into account this long-term effect. The distortion and the procedure are illustrated in an example.
Some New Results on Compromise Solutions for Group Decision Problems
Authors: Freimer M. , Yu P. L.
Published: November 2008

We report some new results on compromise solutions studied by Yu [Yu, P. L. 1973. A class of decisions for group decision problems. Management Sci. 19 (8, April) 936–946]. The following article focuses on the relation between the compromise solution and its parameter. In particular, we show that, under some nice conditions, the compromise solution is a continuous function of its parameter. A fundamental monotonicity result (Theorem 3.1) concerning compromise solutions is derived. The result enables us to generate the bounds of all compromise solutions. When n = 2, two monotonicity results are derived. These yield a good interpretation of the parameter p. When p is small the “group utility” is emphasized; and when p increases the individual regrets receive more weight. Finally we construct an example to illustrate that the monotonicity results for n = 2 are almost impossible to be generated for n > 2.
Note—A Note on “The Formulation of the M-Salesman Traveling Salesman Problem”
Authors: Gavish Bezalel
Published: November 2008

A Note on “The Formulation of the M-Salesman Traveling Salesman Problem” (Svestka, J. A., V. E. Huckfeldt. 1973. Computational experience with an M-salesman traveling salesman algorithm. Management Sci. 19 (7, March) 790–799).
Reply to: “Notes on Hofshi and Korsh 1972”
Authors: Hofshi Rami , Korsh James
Published: November 2008

Reply to: “Notes on Hofshi and Korsh 1972” (Joglekar, Prafulla. Notes on Hofshi and Korsh 1972. Management Sci. 22 (6) 717–720).
A Comprehensive Planning Model for Long-Range Academic Strategies
Authors: Walters A. , Mangold J. , Haran E. G. P.
Published: November 2008

In this paper we describe a multiperiod linear programming model designed to aid the administrator of a school in planning and decision-making for a five-year horizon. The technique of goal programming is employed to accommodate the multiplicity of goals and the marginal trade-offs inherent in such a process. The model includes faculty staffing goals, career constraints, teaching and course loads, tenure constraints and budget constraints. A weighted sum of the deviations from the staffing goals make up the objective function of the prototype model considered. Several methods of estimating the various parameters of the model are discussed, and the results of a small example are also discussed.
On Risky Investments with Random Timing of Cash Returns and Fixed Planning Horizon
Authors: Perrakis Stylianos , Sahin Izzet
Published: November 2008

This paper provides a computational technique for the evaluation of the net present value (NPV) of an investment, in which the cash inflows occur at random time points and which terminates after a fixed time interval. The initial cash outlay is deterministic and the magnitudes of the cash inflows are nonnegative random variables with known distributions.

The lengths of the intervals between successive cash inflows are independently distributed and independent of the magnitude of the inflows. The Laplace transform of the distribution of the NPV is computed for both cases of mutual independence and perfect correlation of the inflows.

It is argued that these distributions are indispensable in determining the accuracy of the manager's estimates and in evaluating actual versus expected performance of a project.
Response to Remarks of M. Hofri
Authors: Crane Michael A. , Iglehart Donald L.
Published: November 2008

Response to Remarks of M. Hofri (Hofri, Micha. 1976. Note—Re: Michael A. Crane, Donald L. Iglehart, “Simulating stable stochastic systems, IV: Approximation techniques”. Management Sci. 22 (8) 913).
Note—Note on a Control Problem of Balachandran and Tijms
Authors: Boxma O. J.
Published: November 2008

In this note a conjecture of Balachandran and Tijms [Balachandran, K. R., H. C. Tijms. 1975. On the D-policy for the M/G/1 queue. Management Sci. 21 1073–1076.] concerning the optimality of the D-policy over the N-policy in an M/G/1 queueing system is proved, using an inequality for renewal functions. This inequality seems to have some importance of its own.
Note—A Note: Hidden Nonlinearities in the Application of Goal Programming
Authors: Awerbuch Shimon , Ecker Joseph G. , Wallace William A.
Published: November 2008

This note identifies instances where nonlinearities may occur in the application of goal programming. An illustration is presented and implications discussed.
Communication
Authors: Buffa Elwood S. , Scriabin Michael , Vergin Roger C.
Published: November 2008

(1) “On a Paper by Scriabin and Vergin” by Elwood S. Buffa, Graduate School of Management, University of California, Los Angeles. (Comments on Scriabin, M., R. C. Vergin. 1975. Comparison of computer algorithms and visual based methods for plant layout. Management Sci. 22 (2) 172–181)

(2) “Computer and Visual Methods for Plant Layout—A Rejoinder” by Michael Scriabin and Roger C. Vergin, Faculty of Management Sciences, Simon Fraser University, Burnaby, British Columbia, Canada. (Comments about details of Scriabin, M., R. C. Vergin. 1975. Comparison of computer algorithms and visual based methods for plant layout. Management Sci. 22 (2) 172–181 where Buffa [Scriabin, M., R. C. Vergin. 1976. Computer and visual methods for plant layout—a rejoinder. Management Sci. 23 (1) 104] felt were defects in research design)
The Attribute-Dynamic Attitude Model (Adam)
Authors: Zeleny Milan
Published: November 2008

The traditional compensatory multi-attribute model persists in being inconsistent with empirical findings. It is suggested here that the model is based on a number of significant conceptual simplifications. Although the individual choice behavior is partially characterized by randomness, the model attempts to reveal the underlying deterministic rationale of the choice behavior, abstracted from random fluctuations. If such a model is conceptually false then no stochastic refinement can validate it, although some statistical tests might be improved slightly. We need a different kind of deterministic choice rationale, a new paradigm, capable of explaining and predicting those changes, intransitivities and inconsistencies of the individual choice behavior for which we currently have only a stochastic explanation. Such a methodology can then be further refined via stochastic extension. The model presented here is designed to explain and predict changes in individual choice behavior under varying conditions of choice.
A Simple Perturbed Demand Inventory Model with Ordering Cost
Authors: Hill Thomas W.
Published: November 2008

The optimal order size and reorder point are obtained for a simple perturbed demand inventory model having ordering and holding costs.
An Easy Primal Method for Geometric Programming
Authors: Ecker J. G. , Zoracki M. J.
Published: November 2008

A simple primal solution method for geometric programming is proposed. The method exploits the proximity of geometric and linear programming and is easy to implement by anyone having a linear programming code. Some examples and computational experience are given.
Note—On Marketing Strategy and the Optimal Production Schedule—A Rejoinder
Authors: Leitch Robert Alan
Published: November 2008

Author's rejoinder to the discussion about his paper (Leitch, R. A. 1974. Marketing strategy and the optimal production schedule. Management Sci. 21 (3) 302–312.).
Simultaneous Investment and Allocation Decisions Applied to Water Planning
Authors: Armstrong Ronald D. , Willis Cleve E.
Published: November 2008

This paper develops models for water planning that simultaneously consider investment and allocation decisions. The framework is demonstrated for a region which includes the counties of San Luis Obispo and Santa Barbara in California. The quadratic discontinuous mathematical programming problems-resulting from such models are solved optimally by using generalized Benders decomposition. Benders decomposition is a method for breaking a larger problem into a series of manageable subproblems which yield feasible solutions to the overall system. In this case the decomposition is used to incorporate a quadratic programming allocation subproblem with an integer programming investment sequencing problem.
A Stochastic Model of Demand Forecasting for Technical Manpower Planning
Authors: Kwak N. K. , Garrett Walter A. , Barone Sam
Published: November 2008

This paper presents a stochastic technique for short-term demand forecasting of manpower requirements for a particular functional skin group. The demand model is adaptable to any organization in which the demand for services from a skill group is derived from several projects or activities. Working from these multi-project demands for skill group services, Bayesian decision analysis is used to produce a composite forecast of total skill group manpower demand. Options in the model provide for selectively varying the number and level of detail of the multi-project demand curves. The output of the model is useful for further manpower planning.
Policies for Reducing Blood Wastage in Hospital Blood Banks
Authors: Dumas M. Barry , Rabinowitz Manus
Published: November 2008

This paper presents new operational policies for reducing wastage (due to blood exceeding its transfusable age limit) without adversely affecting shortages (stockouts). One policy, called double-crossmatching, tests the same unit of blood for compatibility with two potential recipients (so that it is available for use by either) and also insures that blood is available for both. Another policy involves using Rh-negative blood for Rh-positive patients under certain blood-age conditions, when medically feasible. The simultaneous use of both policies is also investigated. The performance of these policies is measured by wastage-cost effectiveness over a range of demand levels and by blood type. Operational procedures for using these policies are also discussed.
An Evaluation of Flow Shop Sequencing Heuristics
Authors: Dannenbring David G.
Published: November 2008

This paper presents computational experience with eleven flow shop sequencing heuristics. Included in the study are three previously unreported heuristics, one of which turns out to be superior to the other ten heuristics tested. The comparisons were made on a variety of problem sizes, up to fifty jobs and fifty operations.
Optimizing Claims Fluctuation Reserves
Authors: Haehling von Lanzenauer Christoph , Wright Don D.
Published: November 2008

Many group insurance programs are characterized by experience rating features which imply that a surplus resulting from favorable experience belongs to the group, while the administering insurance company is to be reimbursed for a deficit resulting from unfavorable experience. Due to the volatile nature of claims, a claims fluctuation reserve is frequently established in order to reduce frequent rebates or premium adjustments resulting from surplus or deficit positions. A model is presented for resolving the rebate question and determining the design parameters of a claims fluctuation reserve. The model is formulated for non-stationary conditions and uses the first passage time concept as part of a chance constraint criterion. Results of an actual application are reported.
Note—A Note on the Dynamic Inventory Problem with Unknown Demand Distribution
Authors: Papachristos S.
Published: November 2008

We point out some errors in Iglehart's paper, “The Dynamic Inventory Problem with Unknown Demand Distribution,” published in Management Science in 1964.
Communication—Response to a “Comprehensive Model for Long Range Academic Strategies”
Authors: Walters Anthony S. , Burnstein Janet Mangold
Published: November 2008

Authors' answers to commentaries Gray, P. 1977. Communication—A comprehensive model for long range academic strategies. Management Sci. 23 (11) 1256–1257.
Procedures for Estimating Optimal Solution Values for Large Combinatorial Problems
Authors: Dannenbring David G.
Published: November 2008

This study focuses attention on methods for generating useful solution standards for large combinatorial problems. In particular, several procedures that provide point estimates of the value of the optimum solution are suggested and tested. These concepts are applied to a representative combinatorial problem: flow shop sequencing. Detailed computational results are presented.
Inventory Investment Analysis Using Biased Sampling Techniques
Authors: Berry William L. , Marcus Myles , Williams J. Greg
Published: November 2008

This paper describes the use of Biased Sampling to solve an inventory planning problem at a firm which produces plastic coated steel products. In this application, the Biased Sampling solutions provided an estimate of the inventory investment savings to be obtained from a major capital investment proposal. The problem structure, the development of biasing procedures to guide the solution process, and the computational results are presented.
Note—A Note on “Critical Ratio Scheduling: An Experimental Analysis”
Authors: Graves Stephen C.
Published: November 2008

A recent journal article [Berry, W. L., Rao, V. 1975. Critical ratio scheduling: an experimental analysis. Management Sci. 22 (2, October) 192–201.] by Berry and Rao on job shop scheduling reported some counterintuitive results concerning the use of dynamic operating information in making priority scheduling decisions. The results of the article, based on a simulation experiment, indicate that dynamic information on queue waiting time at individual machines and on the inventory status of individual items fails to improve the performance of the production system. In fact, the reported performance of the dynamic rule was inferior to the static rules in five out of six cases. The purpose of this note is to call attention to the possibility that it is Berry and Rao's construction and/or use of this information, and not the value of the information itself, which is in question.
Snow and Ice Removal in an Urban Environment
Authors: Cook Thomas M. , Alprin Bradley S.
Published: November 2008

Although important answers regarding the efficient removal of snow and ice reside in the domain of good planning and the behavioral sciences, the primary thesis of this paper is that cities can significantly improve their snow and ice removal operations by improving the routing of salt spreader trucks. A dynamic routing heuristic totally different from the static routing in general use was developed. The value of this heuristic was demonstrated to the satisfaction of city officials using a discrete simulation model of a large midwestern city. In addition, the simulator was used to answer questions of salt pile location and equipment configuration and location. Although applied to only one city, this routing heuristic, together with the simulation approach, is of potential value to all city governments that experience snow and ice emergencies.
A Dynamic Equilibrium Model for University Budget Planning
Authors: Massy William F.
Published: November 2008

A difference equation model of a university budget system is proposed and analyzed. The conditions for first and second-order dynamic equilibrium are determined, and it is shown that first-order equilibrium provides a useful criterion for financial health. Two sets of first-order solutions are examined: (1) those involving total expenditures, operating income, and the endowment payout rate; and (2) those involving tradeoffs between the net budget increase factor and tuition. The endowment payout rate emerges as a key policy variable that should be set on the basis of budget variables and total return on the endowment, rather than as the result of endowment yield. A region of instability in the solution space is defined; this region should be avoided. Stationary equilibrium, in which the fraction of the budget supported by endowment remains constant over time, simplifies the model and has other desirable properties.
Proximal Decision Analysis with Imperfect Information
Authors: Agnew Carson E.
Published: November 2008

In proximal decision analysis the value of a decision depends on a vector of state variables s and a vector of decision variables d in a quadratic fashion. Suppose some data, represented by a vector x, can be obtained. This paper describes a technique for using the data and develops an expression for the value of the information conveyed by the data. Because the value model is quadratic the data processing procedure uses a linear minimum-variance estimate of the conditional mean of s which depends only on the prior moments of the state vector and the noise associated with the measurement.
Management of Program Storage in Computers
Authors: Babad Jair M. , Balachandran V. , Stohr Edward A.
Published: November 2008

Computer systems play an increasingly important role in modern enterprises. Such systems represent a major investment, and their performance has major effects on profitability, utilization and user satisfaction. Much effort is therefore directed at the efficient management of these systems, and this paper is a step in this direction. Specifically, we consider the optimal allocation of programs and data to various storage devices in order to minimize the expected operational costs, subject to capacity and timing constraints. This problem is one of the many optimization problems that the system management faces, and its solution, though suboptimal for the whole system, might contribute considerably to the overall system's performance and costs. An effective procedure for the optimal (storage) allocation is presented, whose application to an actual large-scale operating system resulted in high (relative) savings. This procedure, with minor modifications, might be applied to many allocation problems which face users and management of computer systems.
Optimal System Allocations with Penalty Costs
Authors: Derman C. , Lieberman G. J. , Ross S. M.
Published: November 2008

We have N stages to sequentially construct I successful components. At each stage, we allocate a certain amount of money for the construction of a component. If y is the amount allocated, then the component constructed will be a success with probability P(y), where P is a continuous nondecreasing function satisfying P(0) = 0. After each component is constructed, we are informed as to whether or not it is successful. If, at the end of the N stages, we are i components short, then a final penalty cost C(i) is incurred. The problem is to determine at each stage how much money to allocate so as to minimize the total expected cost (construction cost plus penalty cost) incurred. The major result is that if C(i + 1) − C(i) ≤ C(i + 2) − C(i + 1), and if yn(i) denotes the optimal value to allocate when i components are needed with n stages remaining, then yn(i) is nondecreasing in i and nonincreasing in n.
Heuristic Scheduling of Activities under Resource and Precedence Restrictions
Authors: Thesen Arne
Published: November 2008

This paper extends the field of heuristic algorithms for resource constrained scheduling problems in three important areas. First, an algorithm is introduced where the role of the heuristic scheduling urgency factor is expanded from one of solely determining the order in which activities are considered for scheduling at a given instant, to one of determining the combination of activities to be scheduled at this instant. Second, a new hybrid scheduling urgency factor capitalizing on the fact that this algorithm is sensitive to the absolute value rather than relative sequence of the urgency factors is introduced. Finally, a systematic approach to the evaluation of such algorithms is introduced. This includes the identification of relevant problem attributes and the adoption of evaluative concepts such as computational efficiency and analytic and systems effectiveness.
Due-Dates and Instantaneous Load in the One-Machine Shop
Authors: Heard E. L.
Published: November 2008

The due-date assignment problem occurs when due-dates are assigned within, rather than outside, a job shop. This study explores the importance of instantaneous and future shop loads in setting due-dates in shops operating under due-date dependent queue discipline. The assignment of due-dates to arriving jobs in an m-machine shop is formulated as a stochastic dynamic programming problem in the first part of this study. A computational experiment using dynamic programming is performed in the second part and due-dates are developed for specific instantaneous load conditions in a simulated one-machine shop. The importance of instantaneous and future shop loads for assigning due-dates in a one-machine shop, with constant interarrivals and exponential service times, is shown.
A Markovian Model for a Perishable Product Inventory
Authors: Chazan Dan , Gal Shmuel
Published: November 2008

The rate of outdating of a perishable product (such as blood) and the age distribution of the inventory are analyzed. It is assumed that after each period's demand, the inventory is replenished with fresh product, up to a constant level. The age distribution is treated as a finite Markov chain. Expected outdating is shown to be convex in the inventory level. Upper and lower bounds for the expected outdating are obtained for the case of general demand distribution. Better and easily computable bounds and approximate distribution are found for the Poisson demand case.
A Row Generation Scheme for Finding a Multi-Commodity Minimum Disconnecting Set
Authors: Aneja Yash P. , Vemuganti R. R.
Published: November 2008

The multi-commodity minimum disconnecting set in a given network is of considerable interest in military operations. The present known methods of finding the multi-commodity minimum disconnecting set consist of implicit enumeration techniques or techniques which involve the solution of several specially structured linear integer programs known as set-covering problems. In this paper we present an efficient method of finding the multi-commodity minimum disconnecting set by solving a single set-covering problem. Extensions and computational experience are also discussed.
Note—A Note on Shwimer's Theorem A
Authors: Dinkelbach Werner , Rosenberg Otto
Published: November 2008

In 1972 Joel Shwimer published some interesting research “on the n-job, one-machine, sequence-independent scheduling problem with tardiness penalties … where the goal is to minimize the total penalty costs resulting from the tardiness of the jobs” (Shwimer, J. 1972. On the n-job, one-machine, sequence-independent scheduling problem with tardiness penalties: a branch-bound solution. Management Sci. 18 (6) B-301–B313.). The proposed algorithm is essentially based on his Theorem A. Unfortunately the given proof of Theorem A contains an inconsistency. In this note we present a different proof of the mentioned theorem.
Capacity Expansion with Imports and Inventories
Authors: Erlenkotter Donald
Published: November 2008

Models for planning capacity expansion typically have excluded the possibility of using inventories to delay expansion decisions. In this paper some properties are derived for an optimal expansion plan allowing inventories, and a dynamic programming model is formulated for determination of optimal expansion, inventory, and import decisions under an assumption of linearly growing demand. Some computational results for the capacity expansion of India's aluminum industry indicate the roles for inventory and import decisions in an expansion plan, and the sensitivity of these decisions to changes in relative costs.
A Time Series Approach to Queueing Systems with Applications for Modeling Job-Shop In-Process Inventories
Authors: Steudel Harold J. , Wu S. M.
Published: November 2008

The behavior of a uniformly sampled queueing system is characterized and interpreted using a time series approach. The advantages of employing time series to obtain a model of the queue's behavior are shown to be simplicity, flexibility and reliability. An analysis of actual queue data shows that the queue behavior of a uniformly sampled queueing system with a single server and Poisson-exponential activities is adequately described by a first order autoregressive model. The autocorrelation function is used to relate queueing theory and the time series model to obtain the commonly required parameters for a queueing system, in a manner independent of the mean level of the queue.
Kalman Filtering Applied to Statistical Forecasting
Authors: Morrison G. W. , Pike D. H.
Published: November 2008

This paper describes the use of the Kalman Filter in a certain ciass of forecasting problems. The time series is assumed to be modeled as a time varying mean with additive noise. The mean of the time series is assumed to be a linear combination of known functions. The coefficients appearing in the linear combination are unknown. Under such assumptions, the time series can be described as a linear system with the state vector of the system being the unknown parameters and present value of the mean of the process. The Kalman Filter can be used under these circumstances to obtain an “optimal” estimate of the state vector. One of the distinct advantages of the Kalman Filter is that time varying coefficients can be permitted in the model. Examples using the Kalman Filter in forecasting are presented.
Exceptional Paper—Location of Bank Accounts to Optimize Float: An Analytic Study of Exact and Approximate Algorithms
Authors: Cornuejols Gerard , Fisher Marshall L. , Nemhauser George L.
Published: November 2008

The number of days required to clear a check drawn on a bank in city j depends on the city i in which the check is cashed. Thus, to maximize its available funds, a company that pays bills to numerous clients in various locations may find it advantageous to maintain accounts in several strategically located banks. We will discuss the problem of optimally locating bank accounts to maximize clearing times. The importance of this problem depends in part on its mathematical equivalence to the well-known uncapacitated plant location problem. We present a Lagrangian dual for obtaining an upper bound and heuristics for obtaining a lower bound on the value of an optimal solution. Our main results are analytical worst-case analyses of these bounds. In particular we show that the relative error of the dual bound and a “greedy” heuristic never exceeds [(K − 1)/K]k < 1/e for a problem in which at most K locations are to be chosen. Two other heuristics are shown to have worst-case relative errors of at least (k − 1)/(2K − 1) < 1/2. Examples are given showing that all these bounds can be achieved. We present extensive computational results for these approximations.
Note—A Simplified Expression for the Efficient Frontier in Mean-Variance Portfolio Analysis
Authors: Buser Stephen A.
Published: November 2008

The identification of an important but previously overlooked technical property of minimum-variance portfolios greatly simplifies both the derivation of and the expression for the efficient frontier in mean-variance portfolio analysis. These simplifications permit a corresponding reduction in the analytics required to examine and to interpret essential properties of the model including comparative-static results and mutual-fund theorems.
On a Simultaneous Decision Model for Marketing, Production and Finance: A Rejoinder
Authors: Damon William W. , Schramm Richard
Published: November 2008

The primary focus of Welam's comment [Welam, Ulf Peter. 1977. On a simultaneous decision model for marketing, production and finance. Management Sci. 23 (9, May) 1005–1009.] is the criticism of the specific form of the demand function used to Damon and Schramm [Damon, William W., Richard Schramm. 1972. A simultaneous decision model for production, marketing and finance. Management Sci. 19 (October) 161–172, (13)]. His criterion for evaluating the model appears to be the degree to which individual equations faithfully represent the modelled phenomena for all possible values of the endogenous variables. This test of model validity would reject the quadratic approximations of production costs in the Holt, Modigliani, Muth and Simon study [Holt, Charles C. et al. 1960. Planning Production, Inventories, and Work Force. Prentice-Hall, Inc., Englewood Cliffs.], and would reject the use of quadratic utility functions, since at some level of income or wealth marginal utility becomes negative.
Note—Sequencing n Jobs on m Machines to Minimise Maximum Tardiness: A Branch-and-Bound Solution
Authors: Townsend W.
Published: November 2008

Each of n jobs is to be sequenced on m machines, with each job having a due date, and we wish to minimise the maximum tardiness of any job. The problem has been solved by Smith [Smith, W. E. 1956. Various optimizers for single-state production. Naval Research Logistics Quarterly 3 59–66] for the case of one machine. This note develops a branch-and-bound method for the general case.
Planning Electric Power Generation: A Nonlinear Mixed Integer Model Employing Benders Decomposition
Authors: Noonan F. , Giglio R. J.
Published: November 2008

This paper describes the development and application of an optimization program that is used to help electric utilities plan investments for power generation. For each year over a planning horizon the program determines what types and sizes of generating plants should be constructed, so as to minimize total discounted cost while meeting reliably the system's forecasted demands for electricity. The problem is formulated as a large-scale, chance constrained, mixed integer program. The solution algorithm employs Benders' Partitioning Principle, a mixed integer linear programming code, and a successive linearization procedure. Computation costs are low and, in the important area of sensitivity analysis, the program offers special economies which make it attractive to power system planners. Computational results are presented for a full sized generation planning problem for the six New England states where the algorithm is currently being used for planning generating facilities.
The Effect of Uncertainty in Input Quantities on the Optimal Expected Input Combination
Authors: Amihud Yakov
Published: November 2008

The problem faced here by a firm whose input quantities are fluctuating is to choose the optimal combination of average input quantities so as to maximize expected revenue under a cost constraint. We show that for the prevailing production functions, the firm might find it optimal to increase the average use of the stochastic factor (even when such an increase will further increase uncertainty) at the expense of other, possibly certain factors. This holds even when increased uncertainty in input reduces total expected revenue. The solution is shown to depend on characteristics of the production function which are generally ignored in the classical theory of the firm. The model may be used in general maximization problems with underlying stochastic variables.