A dynamic,nonstationary inventory problem for a price/quantity setting firm

A dynamic and nonstationary model is formulated for a firm which attempts to minimize total expected costs over a finite planning horizon. The control variables are price and production. The price p and the demand ζ are linked through the relationship ζ = g(p) + η, where g(p) is the riskless demand curve and η is a random variable. The general model allows for proportional ordering costs, convex holding and stockout costs, downward sloping riskless demand curve, backlogging, partial backlogging, lost sales, partial spoilage of inventory, and two modes of collecting revenue. Sufficient conditions are developed for this problem to have an optimal policy which resembles the single critical number policy known from stochastic inventory theory. It is also shown what set of parameters will satisfy these sufficiency conditions.     

An empirical bayes estimator for the scale parameter of the two-parameter weibull distribution

An empirical Bayes estimator is given for the scale parameter in the two-parameter Weibull distribution. The scale parameter is assumed to vary randomly throughout a sequence of experiments according to a common, but unknown, prior distribution. The shape parameter is assumed to be known, however, it may be different in each experiment. The estimator is obtained by means of a continuous approximation to the unknown prior density function. Results from Monte Carlo simulation are reported which show that the estimator has smaller mean-squared errors than the usual maximum-likelihood estimator.     

A mathematical model for generating the area of a drainage basin

This paper presents a mathematical model that yields the area drained by a naturally-occurring network of streams. The model is based on empirically derived relationships in the field of quantitative geomorphology and an assumption concerning the probabilistic nature of stream system formation. A wide range of model solutions is indicated, and the model is validated by comparing the results to statistics from actual stream systems.     

Minimax inspection strategies for single unit systems

A model for proper scheduling of inspections is considered, if system failures can be detected only by checking. Two cases are analyzed: replacement and no replacement of a failed system. On condition that no or only partial information on the lifetime distribution of the system is available, minimax inspection strategies are obtained with respect to cost criterions.     

On a generalized bin-packing problem

In this paper we address a bin-packing problem which possesses a variety of modifications of the classic theme. Among these are bin-dependent chip weights, bin costs, and bin-dependent penalties for unused capacity. Lagrangian relaxations are employed in the context of a branch-and-bound framework in order to solve the problem after which substantial computational experience is provided.     

Analysis of data from life-test experiments under an exponential model

This paper discusses situations in which the distribution of a lifetime response variable T is taken to depend upon a vector x of regressor variables. We specifically consider the case in which T, given x , has an exponential distribution, and in which x represents levels of fixed factors in an experimental design. Methods of analyzing data under this type of model are discussed, with maximum likelihood and least squares methods being presented and compared.     

Computing equilibria via nonconvex programming

The problem of determining a vector that places a system in a state of equilibrium is studied with the aid of mathematical programming. The approach derives from the logical equivalence between the general equilibrium problem and the complementarity problem, the latter being explicitly concerned with finding a point in the set S = {x: < x, g(x)> = 0, g(x) ≦ 0, x ≧ 0}. An associated nonconvex program, min{? < x, g(x) > : g(x) ≦ 0, x ≧ 0}, is proposed whose solution set coincides with S. When the excess demand function g(x) meets certain separability conditions, equilibrium solutions are obtained by using an established branch and bound algorithm. Because the best upper bound is known at the outset, an independent check for convergence can be made at each iteration of the algorithm, thereby greatly increasing its efficiency. A number of examples drawn from economic and network theory are presented in order to demonstrate the computational aspects of the approach. The results appear promising for a wide range of problem sizes and types, with solutions occurring in a relatively small number of iterations.