Abstract: In order to improve the performance of Stud Genetic Algorithm(SGA) and accelerate the convergence speed, an improved stud genetic algorithm based on opposition is proposed. Conventional random method is replaced with opposition method in both population initialization and mutation, which can improve the quality of solutions. Based on benchmark functions, the optimization performance of the algorithm is compared with genetic algorithm, different evolutionary, particle swarm optimization and stud genetic algorithm, the results show that the new algorithm has better optimization performance.

Key words: opposition, Stud Genetic Algorithm(SGA), optimization

摘要： 为进一步提高螺栓遗传算法的优化效率，加速寻优过程，提出基于对立策略的螺栓遗传算法。该算法在种群初始化阶段和变异阶段均用对立取代随机方式，提高产生解的质量。利用测试函数对算法的效率进行检验，将其与差分算法、遗传算法、粒子群算法和螺栓遗传算法进行对比，结果表明，新算法具有更快的收敛速度和更高的求解精度。

关键词: 对立策略, 螺栓遗传算法, 优化

CLC Number: 

• TP181