The half-open refined oil secondary distribution problem is investigated,where trucks can choose any depot for replenishment or termination,and stations'demands can be split.In real transportation,fuel consumption costs are not only related to driving distance but also to cargo weight.This paper develops a mixed integer linear programming model to minimize both fixed utilization cost and fuel consumption cost.An adaptive large neighborhood search algorithm is proposed,incorporating multiple destroy/repair operators combing problem property,an improved greedy insertion algorithm used for initialization,a demand redistribu-tion strategy,and a depot adjustment strategy.Numerical experiments are conducted using SDVRP benchmark instances and actual data from a refined oil company.The performance of proposed algorithm is compared with variable neighborhood search,improved simulated annealing,and a hybrid genetic algorithm.Computational results show that the proposed algorithm is superior in both solution quality and efficiency.Moreover,it can significantly reduce the distribution cost of the company.
关键词
成品油二次配送/半开放式/需求可拆分/货物权重/自适应大规模邻域搜索
Key words
refined oil secondary distribution/half-open/split-delivery/weight-related cost/adaptive large neighborhood search
维普
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