Biogeography migration algorithm for traveling salesman problem

Abstract

Purpose

Biogeography‐based optimization algorithm is a new kind of optimization algorithm based on biogeography. It is designed based on the migration strategy of animals to solve the problem of optimization. The purpose of this paper is to present a new algorithm – biogeography migration algorithm for traveling salesman problem (TSPBMA). A new special migration operator is designed for producing new solutions.

Design/methodology/approach

The paper gives the definition of TSP and models of TSPBMA; introduces the algorithm of TSPBMA in detail and gives the proof of convergence in theory; provides simulation results of TSPBMA compared with other optimization algorithms for TSP and presents some concluding remarks and suggestions for further work.

Findings

The TSPBMA is tested on some classical TSP problems. The comparison results with the other nature‐inspired optimization algorithms show that TSPBMA is useful for TSP combination optimization. Especially, the designed migration operator is very effective for TSP solving. Although the proposed TSPBMA is not better than ant colony algorithm in the respect of convergence speed and accuracy, it provides a new way for this kind of problem.

Originality/value

The migration operator is a new strategy for solving TSPs. It has never been used by any other evolutionary algorithm or swarm intelligence before TSPBMA.

Citation

Mo, H. and Xu, L. (2011), "Biogeography migration algorithm for traveling salesman problem", International Journal of Intelligent Computing and Cybernetics, Vol. 4 No. 3, pp. 311-330. https://doi.org/10.1108/17563781111160002