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

Price negotiation for capacity sharing in a two-factory environment using genetic algorithm
Price negotiation for capacity sharing in a two-factory environment using genetic algorithm
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.
0020-7343
1847-1868
Chen, J.-C.
27867a5a-9288-4ccc-abe6-7f4c5211edb1
Wang, K.-J.
80013d6b-7ea5-4c50-993e-d5fc2899354d
Wang, S.-M.
c226028d-1bbc-45a4-a41c-44ffb6567d91
Yang, S.-J.
defa92ea-044b-4b03-983b-322a30a47286
Chen, J.-C.
27867a5a-9288-4ccc-abe6-7f4c5211edb1
Wang, K.-J.
80013d6b-7ea5-4c50-993e-d5fc2899354d
Wang, S.-M.
c226028d-1bbc-45a4-a41c-44ffb6567d91
Yang, S.-J.
defa92ea-044b-4b03-983b-322a30a47286

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), pp. 1847-1868. (doi:10.1080/00207540601008440).

Record type: Article

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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Published date: February 2008
Organisations: Southampton Business School

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Local EPrints ID: 396307
URI: http://eprints.soton.ac.uk/id/eprint/396307
ISSN: 0020-7343
PURE UUID: 9fc24a5b-1990-4cbb-9e64-7cb08f0dc52c

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Date deposited: 18 Jul 2016 14:22
Last modified: 17 Jul 2017 18:50

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Contributors

Author: J.-C. Chen
Author: K.-J. Wang
Author: S.-M. Wang
Author: S.-J. Yang

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