This paper extends a previously accepted model, used to estimate the warranty reserves required for nonrepayable products, by discounting future warranty costs to their present value, and by adjusting for expected changes in the general price level. The estimation equations are derived and their implications are discussed.
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.
Response to “A Note on ‘The Formulation of the M-Salesman Traveling Salesman Problem’” (Gavish, Bezalel. 1976. A Note on “The Formulation of the M-Salesman Traveling Salesman Problem”. Management Sci. 22 (6) 704–705).
This paper deals with the optimal issuing sequence of units, say batteries, from storage to the field when field lives are stochastic. Several appealing forms of the field life survival probability F̄(y∣x) are given when the battery has been on the shelf a length of time x. These forms are used to investigate the optimally of LIFO (issue youngest) or FIFO (issue oldest) policies in two basic models. These models correspond to issuing batteries either according to a possibly random schedule (the independent case) or one after another as the successive batteries fail (the dependent case).
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.
A recently proposed goal programming approach to aggregate planning of production rates and work force levels is reviewed and it is pointed out that there is very little difference between the “new approach” and the earlier Hansemann and Hess linear programming formulation. It is noted that the HMMS model used as a test vehicle in the original article can also be viewed as a goal programming formulation. Some more general opinions on the role of modelling in decision making are also included.
This paper centers on issues of equity which are related to least cost air pollution abatement strategies. Motivation is provided by a hypothetical example based on Knox County, Tennessee data. In this example substantial loss in economic efficiency occurs when all polluters are required to reduce emissions by the same rate, which is a popular kind of equity notion termed a “benchmark” solution. This notion of equity is shown to be equivalent to another which is related to the requirement that each polluter reduce by the proportion that he contributes to total controllable pollutant concentration at points in the region. A new air quality management strategy is suggested which is based on the requirement that polluters who choose to act independently of others must reduce emissions according to the benchmark solution. This strategy provides economic motivation for coalition formation.
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.
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.