| 计重收费政策下的货物权重车辆路径 |
| 投稿时间：2009-12-18 修订日期：2010-05-11 点此下载全文 |
| 引用本文：吴思,丁以中.计重收费政策下的货物权重车辆路径[J].上海海事大学学报,2010,31(3):22-26. |
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| 基金项目:国家高技术研究发展计划（“八六三”计划）（2007AA04Z105） |
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| 中文摘要:为提高物流效率、降低物流成本，在货物权重车辆路径问题（Weighted Vehicle Routeing Problem，WVRP）和计重收费问题研究的基础上，按照完全计重收费模式，建立以运输过程中总费用（包括固定费用、油耗费用和路桥费用)最小为目标函数的整数非线性规划优化模型.对实际算例，首先使用lingo软件求解精确解，然后利用粒子群优化（Particle Swarm Optimization,PSO）算法求解近似优化解，最后求解一般车辆路径问题模型并计算出相应的行驶总费用.3种结果的比较分析说明所提出的模型和用PSO算法求解的可行性和有效性.该模型可实现运输资源的优化配置，降低企业的物流成本.
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| 中文关键词:车辆路径问题 货物权重 计重收费 粒子群优化算法 |
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| Weighted vehicle routeing problem under toll by weight policy |
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| Abstract:To improve logistics efficiency and reduce logistics cost, based on the study of Weighted Vehi cle Routeing Problem (WVRP) and toll by weight problem, according to full toll by weight mode, an integer nonlinear programming optimization model is established in order to minimize the total cost (include fixed cost, fuel cost and roll cost) during the transport process. For the actual examples, the lingo software is firstly used to get the exact solutions, and then the Particle Swarm Optimization (PSO) algorithm is used to get the approximate optimal solution, finally the general vehicle routeing problem model is solved and the corresponding total cost of driving is calculated. Comparative analysis of the three kinds of results illustrates the feasibility and effectiveness of the proposed model and PSO algorithm. The method can realize the allocation optimization of transportation resources and reduce the enterprise’s logistics cost. |
| keywords:vehicle routeing problem cargo weight toll by weight particle swarm optimization algorithm |
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