旅行商问题(TSP)的一种改进遗传算法

传统的序号编码遗传算法(GA)使用PMX、CX和OX等特殊的交叉算子，这些算子实施起来很麻烦。针对TSP问题的求解，提出了一种新的改进遗传算法：单亲进化遗传算法(PEGA)，PEGA是利用父体所提供的有效边的信息，使用保留最小边的方法进行个体的进化。与传统的遗传算法相比，PEGA算法弥补了它们的不足之处，简化了遗传算法。给出了PEGA算法的数值算例，仿真实验表明了该算法对于对称的TSP和非对称的TSP问题，都具有收敛速度快的特点，证明了该算法的有效性。

A Improved Genetic Algorithms for TSP

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.