Capacity and production planning for a hybrid system with manufacturing and remanufacturing facilities
- Authors
- Lee, Chul-Won; Doh, Hyoung-Ho; Lee, Dong-Ho
- Issue Date
- Sep-2015
- Publisher
- Professional Engineering Publishing Ltd.
- Keywords
- Remanufacturing; capacity and production planning; mixed integer programming; heuristics
- Citation
- Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, v.229, no.9, pp 1645 - 1653
- Pages
- 9
- Indexed
- SCI
SCIE
SCOPUS
- Journal Title
- Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture
- Volume
- 229
- Number
- 9
- Start Page
- 1645
- End Page
- 1653
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/17391
- DOI
- 10.1177/0954405414539485
- ISSN
- 0954-4054
2041-1975
- Abstract
- This study proposes an integrated model for capacity and production planning in a hybrid production system with manufacturing and remanufacturing facilities. The manufacturing facility produces new products from raw materials, while the remanufacturing facility produces remanufactured products by disassembling, reprocessing and reassembling end-of-use/life products. The problem is to determine capacity requirements and production quantities at manufacturing and remanufacturing facilities, together with subcontracting quantities, to satisfy the demands over a given planning horizon. The objective is to minimize the sum of shutdown, production, inventory holding and subcontracting costs. In particular, this study considers the budget constraint that restricts the cost required to change manufacturing and remanufacturing capacities. An integer programming model is developed to represent the integrated problem mathematically, and then, due to the problem complexity, two linear programming relaxation-based heuristics, each of which fixes the binary variables using a systematic method, are suggested. Computational experiments were done on a number of test instances, and the test results show that the heuristics give near-optimal solutions.
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