A Improved Genetic Algorithms for TSP
Fei Yang · Jisuanji fangzhen · 2003
Genetic algorithms(GA) using ordinal strings must use special crossover operators such as PMX, CX and OX, which is very bother. A new improved GA algorithm is proposed for TSP problem: Partheno-evolution genetic algorithm(PEGA), PEGA that utilize effect limbic information from father-body use the way of preserving the least limbic to evolution. PEGA make up for their lacks and genetic operation of PEGA is much simper than traditional genetic algorithm. Numerical example based on the design is given. Simulation results show a better performance for solving TSP. Thus the effectiveness of the proposed design method is testified.