求解资源约束下校车司机问题的混合变量邻域搜索

IF 0.3 Q4 COMPUTER SCIENCE, THEORY & METHODS
Ha-Bang Ban, Hong-Phuong Nguyen, Dang-Hai Pham
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引用次数: 0

摘要

具有资源约束的校车司机问题(SBDP-RC)是一个具有广泛实际应用的优化问题。在该问题中,车辆的数量准备选择若干小学生,其中所有车辆的总资源小于预定义值。这样做的目的是找到一条能最大限度减少学生等待时间的路线。这个问题在一般情况下是np困难的。在许多情况下,找到一个可行的解决方案就成了np困难问题。为了解决大规模的问题,元启发式方法是一种合适的方法。第一阶段采用基于插入启发式的构造启发式方法创建初始解。然后,后期采用随机邻域搜索与抖动技术相结合的通用变量邻域搜索(GVNS)对解进行改进。这种杂交保证了开采和勘探之间的平衡。因此,该算法可以摆脱局部最优解。在一个基准上对所提出的元启发式算法进行了测试,验证了算法的有效性。结果表明,该算法能快速得到较好的可行解。此外,在许多情况下,与之前的元启发式算法相比,可以找到更好的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hybrid Variable Neighborhood Search for Solving School Bus-Driver Problem with Resource Constraints
The School Bus-Driver Problem with Resource Constraints (SBDP-RC) is an optimization problem with many practical applications. In the problem, the number of vehicles is prepared to pick a number of pupils, in which the total resource of all vehicles is less than a predefined value. The aim is to find a tour minimizing the sum of pupils’ waiting times. The problem is NP-hard in the general case. In many cases, reaching a feasible solution becomes an NP-hard problem. To solve the large-sized problem, a metaheuristic approach is a suitable approach. The first phase creates an initial solution by the construction heuristic based on Insertion Heuristic. After that, the post phase improves the solution by the General Variable Neighborhood Search (GVNS) with Random Neighborhood Search combined with Shaking Technique. The hybridization ensures the balance between exploitation and exploration. Therefore, the proposed algorithm can escape from local optimal solutions. The proposed metaheuristic algorithm is tested on a benchmark to show the efficiency of the algorithm. The results show that the algorithm receives good feasible solutions fast. Additionally, in many cases, better solutions can be found in comparison with the previous metaheuristic algorithms.
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来源期刊
Computer Science-AGH
Computer Science-AGH COMPUTER SCIENCE, THEORY & METHODS-
CiteScore
1.40
自引率
0.00%
发文量
18
审稿时长
20 weeks
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