Entropy-based genetic algorithm for solving TSP

Abstract

The traveling salesman problem (TSP) is used as a paradigm for a wide class of problems having complexity due to the combinatorial explosion. The TSP has become a target for the genetic algorithm (GA) community, because it is probably the central problem in combinatorial optimization and many new ideas in combinatorial optimization have been tested on the TSP. However, by using GA for solving TSPs, we obtain a local optimal solution rather than a best approximate solution frequently. The goal of the paper is to solve the above mentioned problem about local optimal solutions by introducing a measure of diversity of populations using the concept of information entropy. Thus, we can obtain a best approximate solution of the TSP by using this entropy-based GA.