Multiobjective Differential Evolution Algorithm Balancing Multiple Stakeholders for Low-Carbon Order Scheduling in E-Waste Recycling

Abstract

Order scheduling is an important part of the e-waste recycling process, which can influence the quantity and efficiency of the recycling. With the sustainable development of e-waste recycling, low-carbon order scheduling becomes a significant and challenging reverse logistics scheduling problem. However, it is difficult to obtain an effective low-carbon order schedule considering the conflicting interests of the multiple stakeholders, including enterprises, drivers, customers, and governments. To address this issue, a multi-objective order scheduling model (MOOSM) and a multi-objective differential evolution algorithm balancing multiple stakeholders (MODE-MS) are proposed in this paper. First, to embody the interests of different stakeholders, three time-dependent key variables are calculated by the road congestion and vehicle load, including the velocity, travelling time and carbon emission. Second, with the above key variables, a five-objective order scheduling model is formulated to describe the low-carbon order scheduling problem in e-waste recycling. Third, for solving the MOOSM, a multi-objective differential evolution algorithm based on an adaptive evolutionary search strategy is developed to obtain the low-carbon and stakeholders satisfied scheduling schemes. The experimental results validate the feasibility of MOOSM and the effectiveness of MODE-MS. By comparing with four state-to-art algorithms, the advantages of the proposed MODE-MS are further demonstrated in solving the low-carbon order scheduling.