Scheduling the cyclic replenishment for decentralized supermarkets with electric vehicles: a branch-price-and-cut algorithm
研究了电动汽车在时间窗和换电需求下的循环补货调度问题，提出分支定价切割算法最小化车辆数，帮助汽车装配厂降低物流成本并实现绿色生产。
Facing the growing complexity of in-plant logistics, modern automobile manufacturers have widely employed the supermarket-based material-feeding strategy to ensure the smooth running of assembling production. To keep the supermarkets well supplied and implement sustainable scheduling, this paper investigates a cyclic replenishment electric vehicle scheduling problem with time windows and battery swap needs. A mixed integer linear programming model is consequently established, with the objective of minimizing the number of electric vehicles deployed. To solve the model, a novel branch-price-and-cut algorithm (BPCA) based on a set-partitioning model is proposed. In particular, an exact pulse algorithm, combined with a metaheuristic iterated randomized variable neighborhood descent algorithm, is developed to expedite the column generation process. Meanwhile, a memorization path join technique and an improved bounding scheme, are designed to accelerate the convergence of the pulse algorithm. Furthermore, valid inequalities are used to tighten the lower bound. Extensive computational experiments along with a case study verify the effectiveness and superiority of BPCA in dealing with the proposed problem. This paper assists assembly industries in efficiently controlling in-plant logistics, and implementing green production while reducing logistics costs.