Chemical reaction optimization for solving a static bike repositioning problem
Chemical reaction optimization for solving a static bike repositioning problem
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解决静态自行车重新定位问题的化学反应优化
DOI：
10.1016/j.trd.2016.05.005
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发表时间：
2016-08
期刊：
影响因子：
--
通讯作者：
Sin C. Ho
中科院分区：
文献类型：
--
作者：
W.Y. Szeto;Ying Liu;Sin C. Ho
研究了单车静态重定位问题。重新定位的目标是使未满足的客户需求和车辆路线上的运营时间的加权和最小化。针对这一问题，提出了化学反应优化（CRO）方法来处理车辆路线，并设计了一个子程序来确定每个访问站点的装卸量。提出了一种改进的CRO算法，通过增加新的算子、规则和密集邻域搜索方法，提高了原CRO算法的解质量。提出了邻域节点集的概念来缩小解的搜索空间。为了说明增强型CRO的效率和准确性，设置了不同的测试场景，并将从IBM BLOG CPLEX、原始CRO和增强型CRO获得的结果进行了比较。计算结果表明，增强的CRO提供了高质量的解决方案，比IBM的CPLEX的计算时间更短，并提供了更好的解决方案比原来的CRO。结果还表明，将两个邻居节点集纳入增强型CRO提高了解的质量，并且在算法的主要阶段的最后部分，运行密集搜索的概率应随着迭代的增加而增加，以获得更好的解。
In this paper, the single-vehicle static repositioning problem is studied. The objective of repositioning is to minimize the weighted sum of unmet customer demand and operational time on the vehicle route. To solve this problem, chemical reaction optimization (CRO) is proposed to handle the vehicle routes, and a subroutine is proposed to determine the loading and unloading quantities at each visited station. An enhanced version of CRO is proposed to improve the solution quality of the original CRO by adding new operators, rules, and intensive neighbor solution search methods. The concept of a neighbor-node set is proposed to narrow the solution search space. To illustrate the efficiency and accuracy of the enhanced CRO, different test scenarios are set and the results obtained from IBM ILOG CPLEX, the original CRO, and the enhanced CRO are compared. The computational results indicate that the enhanced CRO provides high-quality solutions with shorter computing times than those of IBM ILOG CPLEX and provides better solutions than the original CRO. The results also demonstrate that incorporation of the two neighbor-node sets into the enhanced CRO improves the solution quality, and the probability of running the intensive search should increase with iteration in the final part of the main stage of the algorithm to obtain better solutions.
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DOI：
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发表时间：
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期刊：
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影响因子：
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作者：
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通讯作者：
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DOI：
10.1609/aaai.v29i1.9251
发表时间：
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期刊：
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