bluuebunny/crossref_metadata_2025 huggingface dataset:
Fractional Programming. I, Duality
Authors: Schaible Siegfried
Published: November 2008

This paper, which is presented in two parts, is a contribution to the theory of fractional programming, i.e., maximization of quotients subject to constraints. In Part I a duality theory for linear and concave-convex fractional programs is developed and related to recent results by Bector, Craven-Mond, Jagannathan, Sharma-Swarup, et al. Basic duality theorems of linear, quadratic and convex programming are extended. In Part II Dinkelbach's algorithm solving fractional programs is considered. The rate of convergence as well as a priori and a posteriori error estimates are determined. In view of these results the stopping rule of the algorithm is changed. Also the starting rule is modified using duality as introduced in Part I. Furthermore a second algorithm is proposed. In contrast to Dinkelbach's procedure the rate of convergence is still controllable. Error estimates are obtained too.
Fractional Programming. II, On Dinkelbach's Algorithm
Authors: Schaible Siegfried
Published: November 2008

Dinkelbach's algorithm [Dinkelbach, W. 1967. On nonlinear fractional programming. Management Sci. 13 492–498.] solving the parametric equivalent of a fractional program is investigated. It is shown that the algorithm converges superlinearly and often (locally) quadratically. A priori and a posteriori error estimates are derived. Using those estimates and duality as introduced in Part I, a revised version of the algorithm is proposed. In addition, a similar algorithm is presented where, in contrast to Dinkelbach's procedure, the rate of convergence is still controllable. Error estimates are derived also for this algorithm.
Multi-Commodity Multi-Transformed Network Flows with an Application to Residuals Management
Authors: Panagiotakopoulos D.
Published: November 2008

This paper presents a network model for the analysis of waste management systems. In the “waste management network” that we develop waste-generating activities correspond to sources, each node corresponds to a specific flow (waste) form, and each arc to a flow transformation; a chain from a source to a destination represents in turn waste generation, treatment, and disposal, while a feasible flow pattern constitutes a possible waste management system. The model resembles the maximal multi-commodity flow model with positive gains (single transformation) along the arcs, but in addition it admits multi-transformations, interrelations among arc flows, and flow-dependent budget restrictions. The problem is formulated as a linear program where each column in the constraint matrix corresponds to a chain in the network. The solution procedure uses a column-generation scheme based on a shortest route algorithm adapted for multi-transformed flows. Recycling, discharge and effluent standards, charges, damage costs and various budgeting schemes can be handled. An illustrative hypothetical example is given.
Myopic Approximations for the Perishable Inventory Problem
Authors: Nahmias Steven
Published: November 2008

Recent work in describing optimal ordering policies for perishable inventory casts the problem as a multi-dimensional dynamic program, the dimensionality being one less than the useful lifetime of the product, m. As m becomes large the computational problem becomes severe so that developing approximations is a key problem. A bound on the perishing cost is obtained that is a function only of the total inventory on hand. Substituting this bound and an approximate transfer function, optimal policies can be computed myopically for the new problem. When the demand density possesses a monotone likelihood ratio, it is shown the function to be minimized is strictly pseudo-convex. Sample computations for special cases indicate that the approximation results in costs which are generally less than one percent higher than the optimal.
A Health Index for Patient Selection: A Value Function Approach with Application to Chronic Renal Failure Patients
Authors: Pliskin Joseph S. , Beck Clyde H.
Published: November 2008

Concrete criteria are needed for patient selection for scarce medical treatments and ranking of patient urgency for, or salvageability by, a given form of treatment. The mathematical theory of multi-attribute value functions is employed to rank order chronic renal failure patients with regard to therapeutic expectations. Order-2 mutual preferential independence was observed, thus an additive value function was justified. The paper demonstrates two different procedures for assessing a value function over a discrete attribute. The proposed approach yields a rank ordering (health status index) consistent with the physician's preferences and judgment. It can be employed for any medical decision process, even when only weaker preferential independence properties apply.
Approximate Solution to the (Q, r) Inventory Model for Gamma Lead Time Demand
Authors: Das Chandrasekhar
Published: November 2008

An approximate analytical method for solving the (Q, r) model when lead time demand is Gamma distributed is discussed. The method is quite accurate and requires less input than the familiar iterative method.
A Survey of Users of Corporate Planning Models
Authors: Naylor Thomas H. , Schauland Horst
Published: November 2008

Why are over 2,000 corporations either using, developing, or planning to develop some form of corporate simulation model? What types of companies are using corporate planning models? How are they being used? Which resources are required? These are among the questions which were raised in a recent survey of 346 companies whose results are summarized in this paper. The paper also examines the costs and benefits to be derived from using corporate simulation models. Finally, drawing on the survey results, the authors speculate on future developments in the field of corporate modeling.
Bayesian Point Estimation and the PERT Scheduling of Stochastic Activities
Authors: Britney Robert R.
Published: November 2008

Conventional PERT procedures frequently introduce undesirable and often indeterminant biases into the derived time statistics of large-scale complex projects. An alternative scheduling procedure BPERT is developed, employing an activity-based time estimation loss structure and a cost-minimization criterion. Bayesian point estimates are formulated for beta-distributed activity duration times minimizing the potential losses of misestimation. Viewed as certainty equivalents, these time estimates are then aggregated to yield a single project completion time. “Crashing” is introduced, and us implications for BPERT examined. An illustrative example contrasts PERT and BPERT.
A Branch and Bound Algorithm for Optimum Allocation of Float Nurses
Authors: Trivedi Vandankumar M. , Warner D. Michael
Published: November 2008

This paper discusses a methodology developed for allocation of float nurses in short-term general hospitals. The severity of need for nursing care on a unit is measured from the perceptions of head nurses of the unit. A multivariate regression model is used to predict head nurses perceptions at the beginning of a shift from certain auditable variables. The multivariate regressions are used as an objective function in a branch and bound allocation model designed to allocate float nurses before the start of a shift. The model is tested in five nursing units of a study hospital, and results are presented.
The GPSS Simulation of Scheduling Policies for Surgical Patients
Authors: Kwak N. K. , Kuzdrall P. J. , Schmitz Homer H.
Published: November 2008

The purpose of this study is to determine and evaluate utilization levels of the operating-room and recovery-room facilities of a hospital under different policy considerations governing patient flows. The utilization rates are examined under constraints that apply to the particular hospital from which the empirical data was obtained; however, the model and approach were designed with general applications in mind. The range of values for critical timing measurements is obtained from a model employing the Monte Carlo simulation technique. The model is programmed in GPSS and was run on an IBM 360/165. An optimal policy that satisfies the “real world” constraints of an active hospital is sought. The output from the model is interpreted. It is revealed that increases in facility utilization can be made while meeting the constraints dictated by normal hospital routine, thus offering the possibility of reducing costs.
Health Status Index Models: A Unified Mathematical View
Authors: Torrance George W.
Published: November 2008

A general mathematical formulation of the health status index model is developed. Equations are given for three types of population health indexes and for the determination of the amount of health improvement created by a health care program. Fourteen of the major health status index models from the literature are analyzed, and it is shown that each can be viewed as a special case of the general formulation. It is hoped that the paper will help to unify the health status index concept, will serve to standardize terminology and notation, and will facilitate comparisons of the various models.
An Efficient Algorithm for the 0-1 Knapsack Problem
Authors: Nauss Robert M.
Published: November 2008

In this note we present an efficient algorithm for the 0-1 knapsack problem and announce the availability of a callable FORTRAN subroutine which solves this problem. Computational results show that 50 variable problems can be solved in an average of 4 milliseconds and 200 variable problems in an average of 7 milliseconds on an IBM 360/91.
An Improved Heuristic Procedure for a Nonlinear Cutting Stock Problem
Authors: Coverdale I. , Wharton F.
Published: November 2008

Many industries acquire stocks of material in large standard sizes which are then reduced to required widths or lengths according to demand. Scheduling the cutting operations is a particularly difficult problem when a few cutting patterns must be chosen from a vast number of feasible patterns such that the total cost of the reduction process is minimised. Physical constraints and economic considerations restrict the number and type of pattern which can be used.

Haessler [Haessiler, R. W. An application of heuristic programming to a nonlinear cutting-stock problem occurring in the paper industry. Unpublished doctoral dissertation, The University of Michigan, Ann Arbor, 1968, available through University Microfilms, Ann Arbor, Dissertation No. 69–12, 119; Haessiler, R. W. 1971. A heuristic programming solution to a nonlinear cutting-stock problem. Management Sci. 17 (12, August) 793–802.] has described a typical problem in the paper industry and a heuristic procedure for obtaining satisfactory schedules. An improved procedure is proposed in which the type of pattern generated and accepted into the schedule is constrained to improve the likelihood that the residual scheduling problem has a feasible and economic solution. Results obtained by the proposed procedure are compared with those obtained manually and by Haessler for a set of eleven actual problems.
Note—A Test for Nonoptimal Actions in Undiscounted Finite Markov Decision Chains
Authors: Hastings N. A. J.
Published: November 2008

A test for nonoptimal actions in undiscounted Markov decision chains is proposed. The test eliminates actions for one or more stages after which they may re-enter the set of possibly optimal actions, but as convergence proceeds such re-entries cease.
An Empirical Analysis of the Optimal Advertising Policy
Authors: Horsky Dan
Published: November 2008

This paper determines an optimal policy for investment in advertising for a firm that wishes to maximize its discounted profits. To that end, an integrated approach consisting of model formulation, empirical investigation, and optimization is carried out. A model of market share response to advertising is formulated as a first-order Markov process, with nonstationary transition probabilities. These probabilities are assumed to be a function of the advertising goodwill accumulated by the firm and its competitors. The model as specified is nonlinear in its parameters, and nonlinear regression techniques are applied to estimate them. It is shown that this nonlinear form offers, via likelihood ratio tests, a unique opportunity for testing the model, and in a resulting empirical test, the model is found to be consistent with the data. Given these empirical findings, an optimal advertising policy is derived by the use of optimal control theory. The managerial implications of the recommended multi-period policy are examined, and the policy's sensitivity to managerial inputs and economic conditions is analyzed and illustrated.
Determination of the Product Mix and the Business Policy of an Insurance Company—A Portfolio Approach
Authors: Kahane Yehuda
Published: November 2008

This paper sets out a model which simultaneously determines the optimal composition of the insurance and investment portfolios of an insurance company using Sharpe's Single-Index Technique. This technique can be explained for management as follows: different product lines that a multi-product firm offers have different rates of return and different risks associated with those rates of return. Taking into account both risks and rates of return, what is the best mix of product lines for a firm to offer in the marketplace? This approach is especially suitable for insurance because of data limitations. This type of analysis can make a useful contribution in shaping the firm's product mix and marketing policy.
The Design of Problem-Solving Systems
Authors: Ulrich Werner
Published: November 2008

Problem solving, from a systems point of view, is to be considered as a complex, cognitive-affective process of formation and reorganization of conceptual systems. Conceptualization of problem-solving systems includes the development of a problem solver's possible points of view, their naming by explicitly introduced terms, and finally elaboration of ideal-typical formal design models. This paper suggests a taxonomic framework that elaborates and interconnects six design viewpoints, in order to give the problem solver (comprehended as a systems designer) better conceptual support than the “general” systems concept which is still mechanistically employed. These viewpoints furnish corresponding formal design ideals for the design and improvement of problem-solving processes. They must be completed by both normative premises and behavioral science concepts.
A Strategy Which Maximizes the Geometric Mean Return on Portfolio Investments
Authors: Vander Weide James H. , Peterson David W. , Maier Steven F.
Published: November 2008

A common formulation of the portfolio selection problem leads to the prescription of a strategy which maximizes the geometric mean return on investments. In this paper we examine conditions under which solutions exist for the case where the returns distribution is discrete. We establish necessary and sufficient conditions for a solution to exist and give a computationally convenient and exact method for finding a solution in circumstances where (i) a solution exists and (ii) the number of securities equals or exceeds the number of values in the returns distribution.
The m-Center Problem: Minimax Facility Location
Authors: Garfinkel R. S. , Neebe A. W. , Rao M. R.
Published: November 2008

The m-Center Problem is to locate a given number of (emergency) facilities anywhere along a road network so as to minimize the maximum distance between these facilities and fixed demand locations assigned to them. Fundamental properties of the m-Center Problem are examined. The problem is modeled using integer programming, and is successfully attacked using a binary search technique and a combination of exact tests and heuristics. Computational results are given.
Note—A Note on Multivariate Risk and Separable Utility Functions
Authors: Engelbrecht Richard
Published: November 2008

Richard [Richard, Scott F. 1975. Multivariate risk aversion utility independence and separable utility function. Management Sci. 22 (1) 12–21.] derived a number of results on multivariate risk for sufficiently regular utility functions. The results generalize to quite arbitrary utility functions.
Note—A Note on Single Machine Sequencing with Random Processing Times
Authors: Hodgson Thom J.
Published: November 2008

It is shown that Lawler's efficient (order n2) algorithm for the n-job, one-machine scheduling problem (where the objective is to minimize the maximum deferral cost subject to arbitrary precedence relationships) also applies when the processing times are random variables and the objective is to minimize the maximum expected deferral cost. Several special cases are explored.
How Often Will the Firemen Get their Sleep?
Authors: Finnerty John D.
Published: November 2008

We calculate the expected additional fire protection cost to a city implied by the 1974 amendments to the Fair Labor Standards Act. Under the amendments, if a city chooses not to pay its men who are on duty for more than 24 hours at a time for sleep and meal time, it may exclude up to eight hours of sleep time, but must compensate them at overtime rates for the entire sleep period if one or more alarms prevent them from obtaining at least five uninterrupted hours of sleep in that period. Interalarm times are modeled as a Poisson process, and both point and interval estimates of the additional annual overtime cost are computed for the city of Monterey by estimating the annual number of interrupted sleep periods. A model that permits the rate at which alarms are received and the length of die designated sleep period to be varied is developed for computing the proportion of nights in the year during which the firemen get five uninterrupted hours of sleep. A procedure for adjusting the model to allow for the time spent in response to an alarm is also described.
Multilocation Plant Sizing and Timing
Authors: Rao Ram C. , Rutenberg David P.
Published: November 2008

In this paper we solve a dynamic multilocation problem. Time is continuous, and demands can grow at varying rates in different markets and at different times. There are economies of scale in building plant capacity. To solve such a problem conditional on a prescribed sequence, we show how to use recent insights into the transportation problem to develop constructive algorithms that are computationally viable and attractive even for large problems. With plant sizes held constant, transportation cost is optimized through continuous time so as to set plant timings. We then treat the plant sizes (and some timings) as continuous variables in a feasible directions procedure to move towards a local optimum.
Incorporating Thresholds of Indifference in Probabilistic Choice Models
Authors: Krishnan K. S.
Published: November 2008

Probabilistic choice models are often based on utility concepts which call for assessments by decision makers of available alternatives. These models assume that distinct utilities can be derived from the decision maker's expressed preferences. Such an assumption is generally valid if the decision maker can recognize arbitrarily small utility differences. If the decision maker is indifferent between the alternatives the corresponding utilities are expected to be similar. In this paper, the concept of minimum perceivable difference is introduced into the conventional binary logit model. It is postulated that two alternatives are perceived as different only if the absolute difference in their utilities exceeds a positive constant. For estimating the parameters of the new model a maximum likelihood technique is employed, and an empirical test of the model is conducted using data on travelers' choice of mode for accessing commuter rail service from Lindenwold (New Jersey) to downtown Philadelphia. The model predicts individuals' choices in a holdout sample significantly better than the conventional logit model.
An Investment Strategy with Overshoot Rebates which Minimizes the Time to Attain a Specified Goal
Authors: Aucamp Donald C.
Published: November 2008

A strategy is developed which minimizes the expected time (or plays) to reach a given financial goal when “time rebates” are given if the goal is more than attained in the last investment period. It is shown that the optimal strategy is the one which maximizes the expected logarithm of the investment relative (for discrete distributions this is equivalent to maximizing the geometric mean). This strategy is optimal for all goals and levels of capital. When no time rebates are given, however, the proposed strategy will generally not be optimal. In this case the theory shows the strategy is uniformly good. Further, at least in a limited sense, the true optimal will generally differ significantly only in endgame play.
Managing the Incidence of Sickle Cell Anemia Through Genetic Counseling
Authors: Meredith Jack
Published: November 2008

Genetic counseling has long held promise as a means for controlling Tay-Sachs disease, thalassemia, sickle cell anemia, and a host of other untreatable genetic illnesses. This paper reports a study to investigate the long-term viability of genetic counseling as an alternative to searching for a cure for sickle cell anemia. The paper includes consideration of the relative lack of fitness of individuals with sickle cell anemia, the effect of mutation from normal to sickle hemoglobin, and the effect of interbreeding between the black and white races as well as the result of counseling specific proportions of the population with high risk rather than counseling everyone. The results project the theoretical rate of sickle cell anemia in the U.S. black population over the next 800 years, and are viewed qualitatively rather than as firm projections due to the preliminary nature of the counseling data and the simplifying assumptions of the model. They suggest that counseling programs can play a very large role in reducing the incidence of sickle cell anemia, even in the near future.
A Model of a Multi-Product Two-Stage Inventory System with Limited Intermediate Bulk Storage Capacity
Authors: Daellenbach Hans G.
Published: November 2008

A firm has a limited number of bulk storage tanks available for intermediate storage. A joint decision as to the assignment of products to tanks and the inventory stocking and replenishing policy for each product has to be made. It is shown that for a given inventory policy the minimization of the total cost expression can be transformed into a nested optimization problem involving three phases. These can be optimized sequentially starting with the innermost phase. The last phase turns out to be a transportation problem. The solution for an example involving 18 products and 10 tanks is presented and discussed.
Production Runs for Multiple Products: The Two-Product Heuristic
Authors: Saipe Alan L.
Published: November 2008

The optimal solution is presented for the problem of determining production run sizes for two products which must be produced on the same machine. This solution forms the basis for a heuristic solution to the N product problem. This heuristic provides uniformly better results than the complete-cycle heuristic for this problem. Numerical examples are presented to illustrate the method.
The Effects of Communication and Information Availability in an Experimental Study of a Three-Person Game
Authors: Murnighan J. Keith , Roth Alvin E.
Published: November 2008

This study investigated the effects of six communication/information conditions on the outcomes reached by three-person groups playing a characteristic function game. The game was played by a monopolist and two weaker players. The conditions consisted of six combinations which varied the amount of information available to the players and their ability to communicate with one another. The investigation focused on the effects of the independent variables and the relationship between the data and several game theoretic solution concepts. The results indicated that the monopolist's payoffs depended to a large extent on the communication/information conditions. Announcement of the payoff division and the availability of messages tended to reduce his payoffs. In conditions where no messages were allowed, the monopolist's payoffs increased over time. Although the data diverged significantly from the core, the situations which contributed to greater competition resulted in outcomes closer to the core. A comparison between von Neumann-Morgenstern solutions and the more general class of subsolutions indicated that subsolutions were more reflective of the behavior observed. In addition, the results over the entire set of conditions closely approximated the Shapley value, which has recently been shown to be a risk neutral player's expected utility for playing the game. Directions for future research were suggested.
Note—Author's Reply to Graves' Note on the Paper “Critical Ratio Scheduling: An Experimental Analysis”
Authors: Berry William L.
Published: November 2008

Author's Reply to Graves' Note on the Paper (Berry, W. L., V. Rao. 1975. Critical ratio scheduling: an experimental analysis. Management Sci. 22 (2, October) 192–201).
Optimization of Multitype Branching Processes
Authors: Pliska Stanley R.
Published: November 2008

We consider either a discrete time or an age-dependent branching process where the population consists of k types of individuals. Each time an individual is born, an action is chosen, for him which affects his lifetime, the number and types of his offspring, and the reward received. The problem of maximizing the expected reward is shown to be equivalent to a generalized Markov decision problem where the (k × k) transition, matrices are non-negative but not necessarily substochastic. It is shown that this branching process decision model can account for immigration, that it can be viewed as a controlled population process or infinite particle system, and that it has a number of applications including marketing and biology.
Linear Multiparametric Programming by Multicriteria Simplex Method
Authors: Yuf P. L. , Zeleny M.
Published: November 2008

A recently derived Multicriteria Simplex Method [Yu, P. L., M. Zeleny. 1975. The set of all nondominated solutions in linear cases and a multicriteria simplex method. J. Math. Anal. Appl. 49 (2, February) 430–468.] is used to study some basic properties in the decomposition of parametric space. A new type of parametric space, which arises naturally in its formulation, is used. Two computational methods are discussed. The first one is an indirect algebraic method which locates the corresponding set of all nondominated extreme points. The second one is a direct geometric decomposition method which is similar to that discussed by Gal and Nedoma [Gal, T., J. Nedoma. 1972 Multiparametric linear programming. Management Sci.. 18 406–421.]. The difficulties of such a geometric method are discussed through an example.
Aggregate Planning with Learning Curve Productivity
Authors: Ebert Ronald J.
Published: November 2008

Research reports of others indicate that many manufacturing organizations experience (a) the probiem of aggregate planning, and (b) experience systematic productivity changes throughout the “life” of a product. Methods for resolving (a) and for quantifying (b) have been developed and applied independently in the operations management literature. All current aggregate planning models are suitable only for constant productivity situations. The current research integrates (a) and (b) into a single computer-based model which permits the development of aggregate-output plans in the face of changing, productivity.

The model requires reformulation of traditional aggregate planning methods to incorporate changes in productivity and thereafter solves the reformulated planning problem using direct-computer search. The potential significance of the model is demonstrated by generating a series of aggregate plans for various learning rates. These plans are then used to develop manpower schedules, for cash flow analysis, and for making product pricing decisions.
An Application of Z-Matrices to a Class of Resource Allocation Problems
Authors: Tamir Arie
Published: November 2008

This study focuses on allocation problems that have some of their constraints defined in terms of Leontief input-output matrices, known as Z-matrices. A few properties of these matrices are discussed and then applied to achieve a possible reduction in the dimensionality of the resource allocation models. An allocation problem of the above nature is the subject of the recent work of Luss and Gupta [Luss, M., S. K. Gupta. 1974. Allocation of marketing effort among P substitutional products in N territories. Oper. Res. Quart. 25 77–88.], who were concerned about optimal allocation of marketing efforts among substitutional products distributed in different sales territories. The reduction procedure is then applied to their model to yield several extensions.
Economic Design of np Charts for Processes Subject to a Multiplicity of Assignable Causes
Authors: Chiu W. K.
Published: November 2008

A model is developed for production processes which have an in-control state and may jump to one of several out-of-control states in course of time, each such state being associated with an assignable cause. The quality characteristic is an attribute so that an np-chart control scheme is applied. Various cost and time elements are included in the derivation of the loss-cost function. By minimizing this function with respect to the three control variables, namely, the sampling interval, the sample size and the acceptance number, the economically optimal control plan can be obtained. A numerical example is given using a new prior distribution. The results compare favourably with those derived from a matched single cause model.
An Experimental Comparison of the Effectiveness of Three Planning Methods
Authors: Nutt Paul C.
Published: November 2008

Methods of planning based on systems ideas, behavioral science concepts, and heuristics were used to develop plans in a field setting, to contrast the merits of these planning approaches. Plans were evaluated by experts as well as decision makers and staff in the participating organization. Criteria such as quality, acceptance, and measures of innovation were used to contrast the plans. The perceptions of agency representatives that participated in the planning groups were also obtained.

The systems method used planning groups that were composed solely of experts. In the systems method, objectives were established in the first phase of the meeting, and used as a basis to structure the development of plans. For example, the intent of the service delivery plan was established before recommendations were developed. The behavioral approach used clients, the recipients of the service to be planned, as planning groups members. These groups developed a list of priority client problems which were used as a focus to formulate plans. The heuristic approach was applied to simulate trial and error planning. In this approach, no structure was used in the generation of plan components, the leader merely recorded the ideas that were stimulated by a statement of the problem. In the heuristic approach, half the planning groups had just clients as members and the rest were made up of experts.

The three methods of planning were applied to two problems—the development of plans for primary health care services, and home health care delivery mechanisms. In all, twelve distinct planning groups participated permitting a replication of each “problem-planning topic” contrast.

The results of the experiment indicated that the systems approach produced better quality plans while the behavioral approach produced more new ideas. This suggests that involving an organization's client in planning of services to define their problems provides a rich array of ideas for the planning process, but that systems approaches and experts are needed to formulate these ideas and consolidate them into a viable plan. However, the participants found their experiences to be significantly less satisfactory when a systems approach was used. Several other implications of these findings for planning practice are discussed.
Optimal Inventories for an (S − 1, S) System with No Backorders
Authors: Smith Stephen A.
Published: November 2008

This paper considers the problem of finding optimal stock levels for an inventory system with Poisson demands, arbitrary replacement time distribution, and emergency handling of shortages at a premium cost. The ordering policy is assumed to be of the (S − 1, S) type, i.e., a replacement item is ordered as soon as a unit of stock is used. A criterion for selecting the optimal stock level is formulated by minimizing the expected cost per unit time in steady state. Based on the fact that the probability of shortage for this model is given by the Erlang loss formula, it is possible to derive an approximate stocking level formula, which appears to be accurate over a wide range of parameter values. Comparisons with other related models and determination of achieved service levels are also discussed.
Minimising Waiting Time Variance in the Single Machine Problem
Authors: Eilon Samuel , Chowdhury I. G.
Published: November 2008

The paper considers the problem of n given jobs to be processed on a single machine where it is desirable to minimise the variance of job waiting times. A theorem is presented to the effect that the optimal sequence must be V-shaped (i.e., the jobs must be arranged in descending order of processing times if they are placed before the shortest job, but in ascending order of processing times if placed after it), and an algorithm for determining the optimal solution is given. A heuristic method is proposed for solving the problem where n is large; this method requires very little computing and was found to produce very good results for a sample of problems of varying size. The concept of the “efficient set” is examined and heuristic methods for generating this set are given.
Effectiveness of Nominal and Interacting Group Decision Processes for Integrating R&D and Marketing
Authors: Souder William E.
Published: November 2008

Because R&D and marketing are dependent upon each other for new product development, it is imperative that they achieve consensus and organizational integration (a team spirit of collaboration and joint commitment). But, consensus and integration are often inhibited by the differing viewpoints of R&D and marketing, which are a natural consequence of their specialized organizational roles and cultures. There is a need for a process that will bridge these dissonant viewpoints and cultures, while otherwise preserving the specialized orientations of the two parties. The bridging properties of three group decision making processes—nominal, interacting, and combined nominal-interacting—were tested by nine strategic planning teams, each composed of R&D and marketing personnel. The combined nominal-interacting process yielded very high levels of statistical consensus and group integration. The nominal process produced statistical consensus but it did not yield high levels of integration. The interacting process did not produce either consensus or integration. The results here and elsewhere indicate that consensus and collaboration problems between R&D and marketing may be alleviated by replacing the interacting decision making process, which is typically used by many organizations, with a combined nominal-interacting process.
A Flow Augmentation Approach to the Network with Gains Minimum Cost Flow Problem
Authors: Jensen P. A. , Bhaumik Gora
Published: November 2008

A network with gains has branches in which the ratio between the flow leaving a branch and the flow entering a branch is a positive constant called the gain. Branch gains may be greater or less than one. Such networks arise in water resources and electrical power planning problems, among others. This paper presents a dual method of finding the minimum cost flows in such a network. Computerized versions of the procedure have been tested on networks with up to 7,000 branches.
Optimal Engineering Design Under Uncertainty by Geometric Programming
Authors: Wiebking Rolf D.
Published: November 2008

This paper presents an application of stochastic (posynomial) geometric programming to an optimal engineering design problem. A theory developed by Avriel and Wilde for calculating and bounding the expected value of the objective function is summarized. Moreover, a method known as the statistical error propagation method is used to calculate approximate confidence intervals for the cost function. Stochastic geometric programming is applied to the design of a conventional “once-through” condensing system for a steam power plant in the presence of uncertainty (e.g., fuel costs can vary with market conditions). It is shown how the design engineer can extract a considerable amount of information from the solution of merely one small optimization problem. If tighter bounds on the expected cost value are desired, knowledge of discrete probability distributions for the individual random parameters is required and additional optimization problems must be solved.
Allocating Selling Effort Via Dynamic Programming
Authors: Beswick Charles A.
Published: November 2008

This article presents a model for allocating selling effort and setting sales force size which explicitly considers interactions with territorial design, forecasting, and performance evaluation. An extremely fast, dynamic programming algorithm for the allocation of selhng time to control units is presented, and a proof of the optimality of this solution under specified conditions is provided. This algorithm also generates the optimum sales force size and provides output which is a basis for designing sales territories. The allocation algorithm can accommodate a large class of multivariate response functions. The model also incorporates subjective judgment into the decision process. Interaction with sales management of a test firm has shown that the model is highly useful in pinpointing problem areas, in evaluating salesmen, and in designing territories which can, to a large degree, achieve the benefits of the optimum allocation generated by the model.
Combining Expert Judgments: A Bayesian Approach
Authors: Morris Peter A.
Published: November 2008

This paper presents a new approach to the problem of expert resolution. The proposed analytic structure provides a mechanism by which a decision maker can incorporate the possibly conflicting probability assessments of a group of experts. The approach is based upon the Bayesian inferential framework presented in [Morris, P. A. 1974. Decision analysis expert use. Management Sci. 20 (9, May)].

A number of specific results are derived from analysis of a generic model structure. In the single expert continuous variable case, we prove that the decision maker should process a calibrated expert's opinion by multiplying the expert's probability assessment by his own prior probability assessment and normalizing. A method for subjectively calibrating an expert is also presented.

In the multi-expert case, we obtain a simple multiplicative rule for combining the expert judgments. We also prove the existence of a composite probability function which measures the joint information contained in the probability assessments generated by a panel of experts. The interesting result is that composite prior should be processed as if it were the probability statement of a single calibrated expert.
The T-Policy for the M/G/1 Queue
Authors: Heyman Daniel P.
Published: November 2008

We consider situations where the server cannot continuously monitor its queue to sense customer arrivals. For this situation we introduce the T-policy which activates the server T time units after the end of the last busy period. We consider in detail an M/G/1 queue with linear customer holding costs and a fixed charge for activating the server. For the minimum cost-rate criterion we obtain the optimal value of T and the optimal cost rate. We show that the optimal cost rate is larger than the one achieved by the comparable optimal N-policy which activates the server when N customers are in the queue. We also show that under the optimal T-policy, the expected number of customers present when the server is activated is the optimal value of N.
Cognitive and Personality Tests for the Design of Management Information Systems
Authors: Bariff M. L. , Lusk E. J.
Published: November 2008

Presently observation and interviews are used in gathering information to facilitate organizational acceptance of MIS modifications. The authors propose that the measurement and evaluation of users' cognitive styles and related personality traits may provide an effective means for attaining successful MIS modifications. The authors suggest that two aspects of cognitive and personality traits are relevant to user adaptive behavior: (1) cognitive style and (2) implementation apprehension, e.g., resistance to change, defense mechanisms and stress tolerance. These design aspects are incorporated in a field study.
Time-Cost Tradeoffs: Elasticity Estimates and Determinants for International Technology Transfer Projects
Authors: Teece David
Published: November 2008

This paper postulates and tests for a time-cost tradeoff during the establishment of manufacturing plants abroad based on U.S. technology. Data on twenty international projects are used to estimate negatively sloped tradeoff functions for which time-cost elasticities are subsequently calculated. The determinants of these elasticities are then analyzed and shown to bear some similarities with the determinants of time-cost tradeoffs in technological innovation. The elasticity measurements were higher for projects where the technology had not been previously commercialized, for large-scale projects, and for projects carried out by the larger firms.
A Markov Quality Control Process Subject to Partial Observation
Authors: White Chelsea C.
Published: November 2008

This paper studies the problem of optimally controlling a discrete-time production process with countable state space which is subject to one of three control settings at each time interval: produce, inspect while producing, or repair (revise) the process. The cost of the item produced and the inspection and repair costs are assumed dependent on the state of the production process. It is assumed that the inspector-decisionmaker receives imperfect on-line observations of the production process at both times of production and inspection. Bounds on optimal cost are obtained. For the two-state case, several results associated with observation quality are determined which are sufficient for particularly simple characterizations of an optimal policy. Generalizations of several results due to Ross are also presented.
A Methodology for Assigning Minimum Cost Due-Dates
Authors: Weeks James K. , Fryer John S.
Published: November 2008

This paper presents and illustrates a methodology for estimating minimum cost due-dates in a job shop production system. Simulation of a hypothetical dual-constrained job shop is used to derive response measures of shop performance for various dispatching, labor assignment and due-date assignment rules. Multiple linear and nonlinear regression is used to estimate the relationship between the response measures and the value of K, the multiple of total processing time employed in assigning due-dates, for various dispatching-labor assignment operating policies. Five response measures are used as dependent variables for the regression models. They are mean job flow-time cost, mean job lateness cost, mean job earliness cost, mean job due-date cost, and mean labor transfer cost. The coefficients of the regression analysis are employed to predict shop performance in terms of the five component cost measures for varying levels of K given the dispatching-labor assignment operating policy. The estimated relationships between the component cost measures and the decision roles are combined to form a total cost function. The total cost function is then searched to find the minimum cost due-date multiple for each of the various dispatching-labor assignment policies. Graphical results indicate that the minimum cost multiple K employed to assign due-dates and the sensitivity of costs to deviations from this minimum cost multiple may depend on the cost structure and dispatching-labor assignment operating policy considered. Further, the results suggest that regression analysis of simulation results can be used to estimate due-dates and select dispatching and labor assignment rules for desired performance effects.
Scheduling a Project to Maximize Its Present Value: A Zero-One Programming Approach
Authors: Doersch Robert H. , Patterson James H.
Published: November 2008

A zero-one integer programming formulation of the project scheduling problem is reported which maximizes the discounted value of cash flows in a project when progress payments and cash outflows are made upon the completion of certain activities. While this problem has been treated previously, it has not been addressed in a manner which allows for the type of constraints treated in this paper. And while cash can be treated as any other resource in the noncash flow, resource-constrained version of this problem, the effects of cash inflows and outflows and the time sequencing alternatives for them allow for a different treatment of cash resources than has been previously reported.
Discounting, Ergodicity and Convergence for Markov Decision Processes
Authors: Morton Thomas E. , Wecker William E.
Published: November 2008

The rate at which Markov decision processes converge as the horizon length increases can be important for computations and judging the appropriateness of models. The convergence rate is commonly associated with the discount factor α. For example, the total value function for a broad set of problems is known to converge 0(αn), i.e., geometrically with the discount factor. But the rate at which the finite horizon optimal policies converge depends on the convergence of the relative value function. (Relative value at a given state is the difference between total value at that state and total value at some fixed reference state.) Relative value convergence in turn depends both on the discount factor and on ergodic properties of the underlying nonhomogeneous Markov chains. We show in particular that for the stationary finite state space compact action space Markov decision problem, the relative value function converges 0((αλ)n) for all λ > r(P), the argument of the subdominant eigenvalue of the optimal infinite horizon policy (assumed unique). Easily obtained bounds for r(P) are also given which are related to those of A. Brauer. Under additional restrictions, policy convergence is shown to be of the same order as relative value convergence, generalizing work of Shapiro, Schweitzer, and Odoni. The same result gives convergence properties for the undiscounted problem and for the case α > 1. If αr(P) > 1 the problem does not converge. As a by-product of the analysis, necessary conditions are given for the relative value function to converge 0((αλ)n), 0 < αλ < 1, for the nonstationary problem.
Note—A Comparison of Capacity Planning Techniques in a Job Shop Control System
Authors: Adam Nabil , Surkis Julius
Published: November 2008

A quantitative comparison between three types of capacity planning or shop loading techniques is presented. The results were obtained from simulation experiments.
Note—On the Validity of Marginal Analysis for Allocating Servers in M/M/c Queues
Authors: Dyer M. E. , Proll L. G.
Published: November 2008

In this note we prove a conjecture of Rolfe concerning the convexity of the expected queueing time formula for an M/M/c queue.