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.
| Original language | English |
|---|---|
| Pages (from-to) | 509-522 |
| Number of pages | 14 |
| Journal | Journal of Intelligent Manufacturing |
| Volume | 17 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2006 Aug |
Bibliographical note
Funding Information:Acknowledgements This work was in part supported by Korea Research Foundation Grant funded by the Korean government (MOEHRD, Basic Research Promotion Fund: KRF-2005-206-D00024) and by the fund from the Basic Research Program (Grant No.: R01-2002-000-00232-0) of the Korea Science and Engineering Foundation.
Keywords
- Adaptive genetic algorithm
- Advanced planning
- Manufacturing supply chain
- Scheduling
ASJC Scopus subject areas
- Software
- Industrial and Manufacturing Engineering
- Artificial Intelligence