Solving Capacitated Vehicle Routing Problem by an Improved Genetic Algorithm with Fuzzy C-Means Clustering

Aiming at solving the vehicle routing problem, an improved genetic algorithm based on fuzzy C-means clustering (FCM) is proposed to solve the vehicle routing problem with capacity constraints. On the basis of genetic algorithm, the FCM algorithm is used to decompose the large-scale vehicle routing o...

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Veröffentlicht in:Scientific programming Jg. 2022; S. 1 - 8
1. Verfasser: Zhu, Ji
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Hindawi 18.02.2022
John Wiley & Sons, Inc
Schlagworte:
Clustering
Genetic algorithms
Local optimization
Optimization algorithms
Population
Route planning
Search process
Vehicle routing
ISSN:1058-9244, 1875-919X
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Zusammenfassung:Aiming at solving the vehicle routing problem, an improved genetic algorithm based on fuzzy C-means clustering (FCM) is proposed to solve the vehicle routing problem with capacity constraints. On the basis of genetic algorithm, the FCM algorithm is used to decompose the large-scale vehicle routing optimization problem into small-scale subproblems, which can effectively improve the efficiency of the algorithm. At the same time, a generation method of the initial solution to CVRP problem is designed. The improved algorithm has good robustness and can also reduce the possibility of falling into local optimization in the search process. Finally, a simulation example is provided to verify the efficiency and superiority of the proposed algorithm.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1058-9244
1875-919X
DOI:10.1155/2022/8514660