多策略集成的改进技能优化算法及应用

Improved Skill Optimization Algorithm Based on Multi-strategy Integration and Its Application

关键词:  技能优化算法  佳点集  自适应权重  t-分布扰动  函数优化问题  负荷分配  工程优化

Key words:  skill optimization algorithm  good point set  adaptive weight  t-distribution perturbation  function optimization problem  load allocation  engineering optimization

摘要:

针对技能优化算法(Skill Optimization Algorithm,SOA)寻优精度不高、收敛速度慢等缺点，本研究提出一种多策略集成的改进技能优化算法(Multi Strategy integrated Skill Optimization Algorithm,MSSOA)。MSSOA采用佳点集策略初始化种群，提高初始种群在解空间内的分布质量；根据算法特点在全局搜索阶段采用自适应权重，改进个体行进的步长；根据不同个体采用不同的t-分布扰动方式，平衡全局搜索和局部搜寻的关系，增强算法后期局部搜寻能力。通过12个测试函数、2个工程应用问题对其性能进行测试，测试结果表明MSSOA有着理想的寻优精度和收敛速度，能够解决复杂的工程问题。

Abstract:

Aiming at the shortcomings of Skill Optimization Algorithm (SOA),such as low optimization accuracy and slow convergence speed,a Multi Strategy Integrated Skill Optimization Algorithm (MSSOA) was proposed.MSSOA uses the good point set strategy to initialize the population and improve the distribution quality of the initial population in the solution space.According to the characteristics of the algorithm,the adaptive weight was used in the global search stage to improve the step size of the individual.According to different individuals,different t-distribution perturbation methods are used to balance the relationship between global search and local search,and enhance the local search ability of the algorithm in the later stage.The performance of MSSOA was tested by 12 test functions and 2 engineering application problems.The test results show that MSSOA has ideal optimization accuracy and convergence speed,and can solve complex engineering problems.