An artificial fish swarm algorithm for solving a bi-objective capacitated vehicle routing problem
Jinling Li1, 2, Haixiang Guo1, 3, Yan Chen4, Deyun Wang1, Kejun Zhu1
COMPUTER MODELLING & NEW TECHNOLOGIES 2014 18(5) 181-190
1School of Economics and management, China University of Geosciences, Wuhan, 430074, P.R. China
2Jiangcheng College, China University of Geosciences, Wuhan, 430200, P.R. China
3Key Laboratory of Tectonics and Petroleum Resources, China University of Geosciences, Ministry of Education, Wuhan Hubei, 430074, P.R. China
4School of Distance and Continuing Education, China University of Geosciences, Wuhan, 430074, P.R. China
The paper focuses on a capacitated vehicle routing problem with two objectives: one is attainment of specific load factor and the other is minimization of total travel cost. Our approach is based on artificial fish swarm algorithm, a swarm-based heuristic, which mimics the foraging behaviour of a fish swarm. After initializing a school of artificial fish, whose validity is guaranteed by a designed repair operator, global optimal solution search is processed through random behaviour, prey behaviour, swarm behaviour, and follow behaviour. Experimental results for a practical distribution instance are reported and show that the artificial fish swarm algorithm performs better than sweep algorithm and genetic algorithm. This paper contributes to the solution methods of vehicle routing problem.