Genetic algorithm for the one-commodity pickup-and-delivery traveling salesman problem

Authors:
Fanggeng Zhao;Sujian Li;Jiangsheng Sun;Dong Mei
Affiliations:
Institute of Vehicle Management, Bengbu 233011, China and Department of Logistics Engineering, University of Science and Technology Beijing, Beijing 100083, China;Department of Logistics Engineering, University of Science and Technology Beijing, Beijing 100083, China;Ordnance Technology Research Institute, Shijiazhuang 050003, China;Institute of Vehicle Management, Bengbu 233011, China
Venue:
Computers and Industrial Engineering
Year:
2009

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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.