Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1135520 | Computers & Industrial Engineering | 2009 | 7 Pages |
Abstract
In this paper, we proposed a genetic algorithm for the one-commodity pickup-and-delivery traveling salesman problem. In the proposed algorithm, we designed a new tour constructing heuristic to generate the initial population, and proposed a novel pheromone-based crossover operator that utilizes both local and global information to construct offspring. In addition, a local search procedure was embedded into the genetic algorithm to accelerate convergence. The proposed genetic algorithm was tested on benchmark instances with up to 500 customers, and the computational results show that it gives a faster and better convergence than existing heuristics.
Related Topics
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Authors
Fanggeng Zhao, Sujian Li, Jiangsheng Sun, Dong Mei,