Adaptive genetic algorithm for advanced planning in manufacturing supply chain |
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| Authors: | Chiung Moon Yoonho Seo Youngsu Yun Mitsuo Gen |
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| Affiliation: | (1) Department of Information & Industrial Engineering, Hanyang University, Ansan, 425-791, Korea;(2) Department of Industrial Systems & Information Engineering, Korea University, #1 Anamdong 5-ga, Sungbukku, Seoul, 136-713, Korea;(3) School of Business Administration, Chosun University, Gwangju, 501-759, Korea;(4) Graduate School of Information, Production & Systems, Waseda University, Kitakyushu, Japan |
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| Abstract: | A main function for supporting global objectives in a manufacturing supply chain is planning and scheduling. This is considered such an important function because it is involved in the assignment of factory resources to production tasks. In this paper, an advanced planning model that simultaneously decides process plans and schedules was proposed for the manufacturing supply chain (MSC). The model was formulated with mixed integer programming, which considered alternative resources and sequences, a sequence-dependent setup and transportation times.The objective of the model was to analyze alternative resources and sequences to determine the schedules and operation sequences that minimize makespan. A new adaptive genetic algorithm approach was developed to solve the model. Numerical experiments were carried out to demonstrate the efficiency of the developed approach. Received: June 2005 / Accepted: December 2005 |
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| Keywords: | Advanced planning Manufacturing supply chain Scheduling Adaptive genetic algorithm |
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