An artificial fish swarm algorithm for solving a bi-objective capacitated vehicle routing problem

Jinling Li^{1, 2}, Haixiang Guo^{1, 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.