关键词: 狼群算法, 交互策略, 函数优化, 自适应, 搜索策略

Abstract:

Aiming at the shortcomings of Wolf Pack Algorithm (WPA), such as slow convergence, being easy to fall into local optimum and unsatisfactory artificial wolf interactivity, a wolf pack algorithm based on modified search strategy was proposed, which named Modified Wolf Pack Algorithm (MWPA). In order to promote the exchange of information between the artificial wolves, improve the wolves' grasp of the global information and enhance the exploring ability of wolves, the interactive strategy was introduced into scouting behaviors and summoning behaviors. An adaptive beleaguering strategy was proposed for beleaguering behaviors, which made the algorithm have a regulatory role. With the constant evolution of algorithm, the beleaguered range of wolves decreased constantly and the exploitation ability of algorithm strengthened constantly. Thus the convergence rate of algorithm was enhanced. The simulation results of six typical complex functions of optimization problems show that compared to the Wolf Colony search Algorithm based on the strategy of the Leader (LWCA), the proposed method obtains higher solving accuracy, faster convergence speed and is especially suitable for function optimization problems.

Key words: Wolf Pack Algorithm (WPA), interactive strategy, function optimization, adaptive, search strategy