Integrated stochastic disassembly line balancing and planning problem with machine specificity

The disassembly is a fundamental basis in converting End-of-Life (EOL) products into useful components. Related research becomes popular recently due to the increasing awareness of environmental protection and energy conservation. Yet, there are many opening questions needed be investigated, especially efficient coordination different-level decisions under uncertainty big challenge. In this paper, novel integrated stochastic line balancing planning problem studied minimise system cost, where component yield ratios demands assumed uncertain. work, machine specificities considered for task processing, such as price, ability, capacity. For problem, two-stage non-linear programming model first constructed. Then, it further transformed linear formulation. Based on property analysis, valid inequality proposed reduce search space optimal solutions. Finally, sample average approximation (SAA) an L-shaped algorithm adopted solve problem. Numerical experiments randomly generated instances demonstrate that can save around 11% computation time, 64% time compared with SAA without sacrifice solution quality.