盖文妹, 蒋仲安, 邓云峰, 李竞, 杜焱. 应急救援物资车辆运输路线多目标优化[J]. 工程科学学报, 2014, 36(10): 1384-1393. DOI: 10.13374/j.issn1001-053x.2014.10.016
引用本文: 盖文妹, 蒋仲安, 邓云峰, 李竞, 杜焱. 应急救援物资车辆运输路线多目标优化[J]. 工程科学学报, 2014, 36(10): 1384-1393. DOI: 10.13374/j.issn1001-053x.2014.10.016
GAI Wen-mei, JIANG Zhong-an, DENG Yun-feng, LI Jing, DU Yan. Multi-objective route optimization of transporting emergency goods and materials for rescue[J]. Chinese Journal of Engineering, 2014, 36(10): 1384-1393. DOI: 10.13374/j.issn1001-053x.2014.10.016
Citation: GAI Wen-mei, JIANG Zhong-an, DENG Yun-feng, LI Jing, DU Yan. Multi-objective route optimization of transporting emergency goods and materials for rescue[J]. Chinese Journal of Engineering, 2014, 36(10): 1384-1393. DOI: 10.13374/j.issn1001-053x.2014.10.016

应急救援物资车辆运输路线多目标优化

Multi-objective route optimization of transporting emergency goods and materials for rescue

  • 摘要: 运用运筹学中图论及多目标优化的理论和方法建立应急救援物资车辆最佳运输路线的选择模型,并基于启发式算法求解该模型.从静态网络应急物资车辆运输路线的双目标优化问题入手,设计适合本文模型的算法,并将之推广至含有三个及三个以上优化目标的路线选择问题.引入时间扩展图的概念,将动态网络中的最佳运输路线问题转化为静态网络中的路径选择问题.算法实质是通过构造辅助决策函数实现Dijstra算法的调用,并在辅助函数构成的搜索空间上寻找最优解,是一种快速的、近似的算法.利用随机路网和真实路网测试本文算法,测试结果与本文的理论分析一致,证明本文算法在应急救援物资车辆运输路线的多目标优化问题中可行且有较好的应用效果.

     

    Abstract: A mathematical model of the optimum route for transporting goods and materials during a disaster period was built by using the graph theory and multi-objective optimization method. For the simple case of a dual-objective optimization, an approximate and fast algorithm was proposed based on the heuristic algorithm and then we extended the promotion to other transportation route optimization problems, which contain 3 and more than 3 optimization goals. The dynamic network routing problem was transferred into a static network routing problem by introducing the time-expanded graph in dynamic network flow analysis, which can provide an appropriate method for selecting the optimum route of transporting emergency goods and materials. The purposes of the algorithm are to call Dijstra algorithm to calculate the model by constructing several decision support functions and to find the optimal solution in the search space constituted by the auxiliary functions, so the algorithm is a fast and approximate algorithm. The algorithm was tested in a random road network and a real road network, and the results are consistent with theoretical analysis in the text. The test results show that the algorithm has a better effect in solving the multi-objective route optimization problem of transporting emergency goods and materials and its solution efficiency is higher.

     

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