Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/172566 
Erscheinungsjahr: 
2017
Quellenangabe: 
[Journal:] Journal of Industrial Engineering International [ISSN:] 2251-712X [Volume:] 13 [Issue:] 3 [Publisher:] Springer [Place:] Heidelberg [Year:] 2017 [Pages:] 323-330
Verlag: 
Springer, Heidelberg
Zusammenfassung: 
The vehicle routing problem with the capacity constraints was considered in this paper. It is quite difficult to achieve an optimal solution with traditional optimization methods by reason of the high computational complexity for large-scale problems. Consequently, new heuristic or metaheuristic approaches have been developed to solve this problem. In this paper, we constructed a new heuristic algorithm based on the tabu search and adaptive large neighborhood search (ALNS) with several specifically designed operators and features to solve the capacitated vehicle routing problem (CVRP). The effectiveness of the proposed algorithm was illustrated on the benchmark problems. The algorithm provides a better performance on large-scaled instances and gained advantage in terms of CPU time. In addition, we solved a real-life CVRP using the proposed algorithm and found the encouraging results by comparison with the current situation that the company is in.
Schlagwörter: 
Capacitated vehicle routing problem (CVRP)
Tabu search
Adaptive large neighborhood search (ALNS)
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