Soft computing for multicustomer due-date bargaining

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 find the best priority sequence of customer orders for resource allocation and fuzzy logic operations to allocate the resources and determine the order-completion times, following the priority sequence of orders. To extend the due-date bargainer to accommodate bargaining with several customers at the same time, we propose a method to distribute the total penalty using marginal penalties for the individual bargainers. A demonstration software package implementing the improved due-date bargainer has been developed. It is targeted at apparel manufacturing enterprises. Experiments using realistic resource data and randomly generated orders have achieved satisfactory results.