An Improved Heuristic Crossover Operator for TSP

Abstract

TSP(Traveling Salesman Problem) is one of the typical NP-hard problem in combination optimization. For salving the problem, genetic algorithm is better than traditional ones obviously, and there are also many crossover operators used to get hypo-optimization route. Base on heuristic crossover by Lixin Tang, a new crossover operator is conducted. The crossover preservers the segment of effective genes, then mobile window operator and neighborhood identification operator are used to fasten the algorithm convergence.The example shows that the new crossover operator is useful.

Hybrid crossover operator based on pattern

“…The advantages of GA include its excellent robustness self-organization, self-adapting, which make it been applied to a widely field of the optimization problems, such as travelling sales man problem [5] , generating new individuals and numerical optimization [6] et al In spite of those advantage of GA, prematurely and slow convergence are two obvious problems influence the performance of genetic algorithm, so lots of researcher pay close attention to those problems and make improvement to the genetic operator [7][8][9] .…”