Models for the Single Product Disassembly Lot Sizing Problem with Disposal. Issue 13 (2019)

• Record Type: Journal Article
• Authors: Massahian Tafti, M. Pour; Godichaud, M.; Amodeo, L.
• Is Part Of: IFAC-PapersOnLine. Volume 52:Issue 13(2019)
• Page Start: 547
• Page End: 552
• Publication Date: 2019
• Subjects: Reverse logistics -- Disassembly lot sizing -- Inventory -- Disposal -- Mixed-Integer Programming (MIP); Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2019.11.215
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: This paper considers a single product disassembly lot sizing problem with disposal decision (DLSPD) in order to reduce the costs as well as environmental impacts related to returned products. This is the problem of determining the quantity and time of the returned products to be disassembled while satisfying the demand of their parts or components over a planning horizon. Due to the existence of yield (in a disassembly system) and demand, which are not well balanced during planning horizon, surplus inventory of leaf items will be conducted. The integer programming (IP) can be used to arrive at optimal solution, with the disadvantage that the computational time explodes with increasingly complex product structure and larger size of problem. In this case, LP relaxation approach can be useful. Two integer programming models (aggregate formulation (AGG) and disaggregate formulation (FAL)) with considering disposal decision are developed to cope with the unnecessary surplus inventory. This paper focus on the problem with no capacity restriction on disassembly resource, and single product type with two-level product structure. The computation experiments are conducted to evaluate the performance of proposed models using CPLEX solver for different generated instance sizes. For large-sized problem, LP relaxation approach is suggested and compared with integer/optimal solution to show its effectiveness. The LP relaxation gives a strong lower bound (LB) for the proposed mixed-integer programming models.