询问 发表于 2025-3-25 05:24:52
http://reply.papertrans.cn/63/6246/624542/624542_21.pngPredigest 发表于 2025-3-25 07:33:08
http://reply.papertrans.cn/63/6246/624542/624542_22.pngCumbersome 发表于 2025-3-25 12:58:44
http://reply.papertrans.cn/63/6246/624542/624542_23.png背信 发表于 2025-3-25 16:07:13
Regine Kalkat. MA-BCRCD finds new best known solutions for all 20 instances. It also performs better on average for all instances in comparison to the performance of MATE. The results and analysis provided in this study suggest that further improvements on this problem set are possible both in terms of solutionMITE 发表于 2025-3-25 22:06:07
Regine Kalkat. MA-BCRCD finds new best known solutions for all 20 instances. It also performs better on average for all instances in comparison to the performance of MATE. The results and analysis provided in this study suggest that further improvements on this problem set are possible both in terms of solutionFEAS 发表于 2025-3-26 01:35:28
Regine Kalkads that has already been considered at an earlier iteration, thus accelerating the resolution. Results shown that our approach is competitive in terms of solution quality and execution time and can provide good solutions for the set of instances considered.仲裁者 发表于 2025-3-26 05:08:12
Regine Kalkae routing problem with time windows. The knowledge discovery mechanism extracts sequences of customers from solutions. The results show the benefit of using different strategies for the components of the knowledge discovery mechanism and the efficacy of extracting patterns from local optima for largImpugn 发表于 2025-3-26 10:43:32
http://reply.papertrans.cn/63/6246/624542/624542_28.pngIntractable 发表于 2025-3-26 14:47:01
Regine Kalkased by Glover, for the CMND. Computational results on a set of small and medium size benchmark instances show that while scatter search is not yet able to match the results of the best existing metaheuristics for the problem, all variants are successful in finding better solutions on some instances.LAITY 发表于 2025-3-26 20:16:48
d homes of the truck drivers. We applied the Unified Tabu Search method and modified it by an oscillating change of the neighborhood size in some selected iteration steps. Our heuristics are verified with extensive numerical studies. The Tabu Search based heuristics are able to solve real-life probl