New Tabu Search Algorithm for Large-Scale Vehicle Routing Problem with Simultaneous Deliveries and Pickups
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摘要: 提出了一种新的禁忌搜索算法.该方法集成大量的邻域搜索方法,采用基于线路集合的分解策略,以及重起和扰动策略,将当前解分解成几个独立的路线子集合,用禁忌搜索法求解每个路线子集合,再将求得的子集合最好路线组成新的当前解.与记录更新法和传统禁忌搜索算法的最好目标值相比,在14组测试数据中,取得8个新的最好目标值,其余的误差值不超过2.41%,且有2组数据的车辆数减少了1辆.Abstract: A new tabu search algorithm that integrates many neighborhood search methods,and adopts route set-based decomposition,restart and perturbation strategies,was proposed.The current solution is divided into several subsets of routes,each of which is solved by the tabu search algorithm and the best solutions of the subsets are then merged to form a new current solution.Computational results show that compared with record-to-record travel and traditional tabu search algorithm,the new tabu search algorithm can improve on 8 out of 14 of the best known solutions and reduce the number of vehicles by one in 2 cases,with error less than 2.41% for the others.
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Key words:
- vehicle routing problem /
- multiple neighborhoods search /
- tabu search /
- restart /
- perturbation
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