The problem of scheduling groups of jobs on a single machine under the group technology assumption is studied. Jobs of the same group are processed contiguously and a sequence independent setup time precedes the processing of each group. All jobs have a common fixed due date, which can be either unrestrictively large or restrictively small. The objective is to minimize the total weighted earlin...

We propose a heuristic procedure that constructs a schedule for N jobs with stochastic processing times and a common due date on M parallel, identical machines. The criterion is the minimization of the total expected incompletion cost. A worst-case analysis for the ratio of the heuristic and optimal solutions is presented and a bound on the ratio is derived. The experimental results presented i...

The Due-Date Bargainer is a useful tool to support negotiation on due-dates between a manufacturer and its customers. To improve the computational performance of an earlier version of the Due-Date Bargainer, we present a new soft computing approach. It uses a genetic algorithm to nd the best priority sequence of customer orders for resource allocation and fuzzy logic operations to allocate the ...

This paper proposes an iterative bidding framework for integrated due date management decision making. We focus on a type of make-to-order environment, in which a firm needs to quote due dates and prices and to schedule the production of a variety of job orders required by a large group of customers. In most cases, customers prefer shorter due dates. However, given limited production capacity a...

When firms operate in a make-to-order environment, they must set due dates (or lead times) which are both relatively soon in the future and can be met reliably in order to compete effectively. This can be a difficult task, since there is clearly an inherent tradeoff between short due dates, and due dates that can be easily met. Nevertheless, the vast majority of due date scheduling research ass...