Due to increasing awareness on the treatment of end-of-use/life products, disassembly has been a fast-growing research area of interest for many researchers over recent decades. This paper introduces a novel lot-sizing problem that has not been studied in the literature, which is the service-parts lot-sizing with disassembly option. The disassembly option implies that the demands of service parts can be fulfilled by newly manufactured parts, but also by disassembled parts. The disassembled parts are the ones recovered after the disassembly of end-of-use/life products. The objective of the considered problem is to maximize the total profit, i.e., the revenue of selling the service parts minus the total cost of the fixed setup, production, disassembly, inventory holding, and disposal over a planning horizon. This paper proves that the single-period version of the considered problem is NP-hard and suggests a heuristic by combining a simulated annealing algorithm and a linear-programming relaxation. Computational experiment results show that the heuristic generates near-optimal solutions within reasonable computation time, which implies that the heuristic is a viable optimization tool for the service parts inventory management. In addition, sensitivity analyses indicate that deciding an appropriate price of disassembled parts and an appropriate collection amount of EOLs are very important for sustainable service parts systems.

1. Introduction
2. Problem description
3. NP-Hardness and Heuristic Algorithm
    3.1 Overview of the SA Algorithm
    3.2 Initial Solution Generation
    3.3 Neighborhood Solution Generation
4. Computational Experiment
5. Concluding Remarks
References

• Jin-Myeong Jang(인하대학교 물류전문대학원) | 장진명
• Hwa-Joong Kim(인하대학교 물류전문대학원) | 김화중 Corresponding Author
• Dong-Hoon Son(홍콩과학기술대학교 토목환경공학과) | 손동훈
• Dong-Ho Lee(한양대학교 산업공학과) | 이동호