The improved hybrid genetic algorithm for solving TSP based on Handel-C
Yi Yang, Qiansheng Fang · 2010
Traveling Salesman Problem (TSP) is a kind of classical combinatorial optimization problem that is easy to be described but difficult to be solved. It belongs to NP-hard problem and is applied broadly in practice. Thus rapid and effective solving TSP is very important application value in practice. Genetic Algorithm (GA) is a kind of heuristic global optimization search algorithm that simulates the biology evolutionary system. GA is applied quite broadly to the combinatorial optimization domain. The paper adopts Handel-C language to program for the simple and improved hybrid genetic algorithms that solve TSP. The experiment results show that the performance of the improved algorithm enhances greatly.