This paper describes a problem in which the "cost" of satisfying the demand at a particular location is a weighted average of the travel times for the items that are supplied. The greatest weight is given to the first-arriving item, with decreasing weights given to each succeeding item. In the...

We describe a family of heuristics to solve combinatorial problems such as routing and partitioning. These heuristics exploit geometry but ignore specific distance measures. Consequently they are simple and fast, but nonetheless fairly accurate, and so seem well-suited to operational problems...

A new approximate algorithm for multidimensional zero-one knapsack problems with all positive coefficients is presented. The procedure is controlled by three parameters which affect the tradeoff between solution quality and computation time and whose values are set by the users. For 48 test...

“Landamatics” is a label given by American scholars to designate this algorithmic‐heuristic theory and method of performance, learning and instruction. Landamatics analyses and explains the mental processes which underlie expert performance, learning and decision making. It also defines...

This paper addresses a nonpreemptive single machine scheduling problem where all jobs have a common due date and have zero ready time. The scheduling objective is to minimize mean squared deviation (MSD) of job completion times about the due date. This nonregular measure of performance is...

In this paper we present a heuristic method, based on Lagrangian relaxation, for multilevel lot-sizing when there is a single bottleneck facility. A series of Lagrangian relaxations (one for each item in the product structure) is imbedded in a branch and bound procedure. The objective is to find...