Adaptive large neighborhood search heuristic for pollution-routing problem with simultaneous pickup and delivery
Adaptive large neighborhood search heuristic for pollution-routing problem with simultaneous pickup and delivery
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DOI：
10.1007/s00500-017-2535-5
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发表时间：
2017-03
期刊：
影响因子：
4.1
通讯作者：
S. Majidi;Seyyed-Mahdi Hosseini-Motlagh;Joshua Ignatius
中科院分区：
文献类型：
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作者：
S. Majidi;Seyyed-Mahdi Hosseini-Motlagh;Joshua Ignatius
本文研究了同时取货和送货的污染路径问题，目标是通过调度和路由客户来最小化燃料消耗和排放。建立了该问题的非线性混合整数规划模型，并提出了一种自适应大邻域搜索启发式算法，包括新的删除和插入算子。并提出了一种构造初始解的启发式算法。在两类基准实例上进行了计算实验，验证了该方法的有效性.实验结果进一步表明，我们提出的启发式算法优于相关的启发式算法，并改善了现有文献的结果。
This paper deals with the pollution-routing problem with simultaneous pickup and delivery, where the goal is to minimize fuel consumption and emissions by scheduling and routing customers. A nonlinear mix integer programing model is presented for this problem, and an adaptive large neighborhood search heuristic is proposed for the solution method including new removal and insertion operators. Also a heuristic algorithm is proposed to construct the initial solution. The proposed method is validated by computational experiments conducted on two classes of benchmark instances. The experiments further show that our proposed heuristic outperforms related heuristics and improved the results of existing literature.