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机构地区:[1]福州大学经济与管理学院,福建福州350116
出 处:《江苏科技大学学报(自然科学版)》2016年第3期286-292,共7页Journal of Jiangsu University of Science and Technology:Natural Science Edition
基 金:国家自然科学基金资助项目(70871024;61300104)
摘 要:能源是世界的推动力.能源的消耗一方面需要消耗自然资源,另一方面又会污染环境.因此能源问题是全球持续关注的问题,而作为能源消耗大户的物流也成为业界与学术界关注的焦点.文中以提高客户满意度、降低能耗为目标,建立了带有软时间约束的单车型三维装箱绿色车辆路径优化模型,研究单车型车辆调度中载重量、需求的时间窗、三维装箱等多约束的处理方法,并且采用多目标粒子群算法进行仿真实验,获取Pareto最优解.研究结论对于企业提高客户满意度和降低能源消耗具有借鉴意义.Energy is the driving force of the world. On one hand the energy consumption needs to consume natural resources,and on the other hand it will pollute the environment. Therefore the world pays continuous attention to the energy problem,and the logistics which consumes a large amount of energy has become the focus of the logistics industry and the academic. In order to improve customer satisfaction and reduce the energy consumption,this paper sets up a model with soft time constraints of single type three-dimensional packing green vehicle routing,and studies the method that deal with vehicle scheduling of vehicle load,demands time window,three dimensional packing constraint and so on. Through the multi-objective particle swarm algorithm simulation,the Pareto optimal solution is proposed. The conclusion of this paper is of great significance for the enterprises to improve customer satisfaction and to reduce energy consumption.
关 键 词:绿色车辆路径 三维装箱 客户满意度 粒子群算法 PARETO最优
分 类 号:U661.336[交通运输工程—船舶及航道工程]
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