Bee Colony Optimization with Local Search for Traveling Salesman Problem

Many real world industrial applications involve finding a Hamiltonian path with minimum cost. Some instances that belong to this category are transportation routing problem, scan chain optimization and drilling problem in integrated circuit testing and production. This paper presents a Bee Colony Optimization (BCO) algorithm for Traveling Salesman Problem (TSP). The BCO model is constructed algorithmically based on the collective intelligence shown in bee foraging behaviour. The model is integrated with 2-opt heuristic to further improve prior solutions generated by the BCO model. Experimental results comparing the proposed BCO model with existing approaches on a set of benchmark problems are presented.

• Type: Journal
• Year: 2010
• Where: IJAIT
• Authors: Li-Pei Wong, Malcolm Yoke-Hean Low, Chin Soon Chong
• Keywords: BCO Model, Bee Colony Optimization, IJAIT 2010, Many Real World