Price negotiation for capacity sharing in a two-factory environment using genetic algorithm

Chen, J.-C., Wang, K.-J., Wang, S.-M. and Yang, S.-J. (2008) Price negotiation for capacity sharing in a two-factory environment using genetic algorithm. International Journal of Production Research, 46 (7), 1847-1868. (doi:10.1080/00207540601008440).

Abstract

Uncertain and lumpy demand forces capacity planners to maximize the profit of individual factory by simultaneously taking advantage of outsourcing to and/or being outsourced from its supply chain and even competitors. This study develops a resource-planning model of a large manufacturer with two profit-centered factories. The proposed model enables a collaborative integration for resource and demand sharing which is highly attractive to the high-tech industries against the challenges of short product life cycle, intensive capital investment and decreasing marginal profit. Each of the individual factories applies an economic resource-planning model and a genetic algorithm to improve its objective while purchasing extra capacity requirement from its peer factory or selling extra capacity of resources to the others through a negotiation algorithm. This study makes a contribution in successfully building a mutual negotiation model for a set of customer tasks to be realized by the negotiating parties, each with private information regarding company objectives, cost and price. Experimental results reveal that near-optimal solutions for both of the isolated (a single factory) and negotiation-based (between two factories) environments are obtained.

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