New mixed integer approach to solve a multi-level capacitated disassembly lot-sizing problem with defective items and backlogging

Abstract The disassembly process has attracted mounting interest due to growing green concerns. This paper addresses the capacitated dynamic lot-sizing problem with external procurement, defective and backordered items, setup times, and extra capacity. The problem is to determine how many end-of-life products to disassemble during each period. We propose a new mixed-integer programming (MIP) approach to formulate the problem under study in order to maximize the disassembly-process gain, which is obtained as the difference between the revenue achieved by resale of the items recovered after disassembly and the costs tied to operating the disassembly tasks. Several numerical tests using the well-known CPLEX solver proved that this new model can find the optimal disassembly schedule for most test instances within an acceptable computational time. Furthermore, we led sensitivity studies on disassembly capacity, setup time and procurement cost. Test results validate the power of the suggested model and provide helpful insights for industry practitioners.