A heuristic master planning algorithm for recycling supply chain management

This study focuses on solving a multi-objective master planning (MP) problem for a recycling supply chain, including collectors, disassemblers, shredders, reconditioners and garbage handlers. An MP problem for a recycling supply chain is solved to determine the optimal transporting and processing operations, while considering multiple product structures, multiple discrete planning periods, and multiple demands, stocking and garbage handling quantities. To solve the MP problem, we propose a multiple-goal mixed integer programming model with two objectives: minimize the total delay cost and minimize the sum of processing cost, transportation cost, holding cost, setup cost and garbage handling cost. To improve the effectiveness and efficiency of the solution process, we propose a heuristic algorithm, RPMPA, which consists of three phases: preliminary works, demand grouping and sorting algorithm, and the Recycling Process Path Selection Algorithm. We built a prototype based on RPMPA, and constructed a scenario analysis to show the effectiveness and efficiency of RPMPA.