A new geometric shape-based genetic clustering algorithm for the multi-depot vehicle routing problem
2011
In this paper, a new type of geometric shape based genetic clustering algorithm is proposed. A genetic algorithm based on this clustering technique is developed for the solution process of the multi-depot vehicle routing problem. A set of problems obtained from the literature is used to compare the efficiency of the proposed algorithm with the nearest neighbor algorithm so as to solve the multi-depot vehicle routing problem. The experimental results show that the proposed algorithm provides a better clustering performance in terms of the distance of each customer to each depot in clusters. This result in a considerably less computation time required, when compared with the nearest neighbor algorithm.
Keywords:
- Population-based incremental learning
- Suurballe's algorithm
- Machine learning
- Nearest-neighbor chain algorithm
- Best bin first
- Mathematical optimization
- Artificial intelligence
- Correlation clustering
- k-medians clustering
- CURE data clustering algorithm
- Computer science
- Canopy clustering algorithm
- Pattern recognition
- Cluster analysis
- Determining the number of clusters in a data set
- Data stream clustering
- Correction
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