关键词: 路径规划, 小生境, 免疫克隆, 最优保存策略, 免疫算法

Abstract: In solving path planning，standard genetic algorithm exists the problem of non-convergence with probability one and inevitable degeneration.Faced with this problem，a new algorithm named Adaptive Pseudo-Parallel Immune Algorithm（APPIA） is presented and realized.A niche pseudo-parallel cooperation evolution strategy is given based on evolution of several filial-population and niche technique.A new symbol encoding and decoding style is presented，the design of immune clone，immune dominance of immune operator are given.The clone scale can be regulated automatically by affinity between antibody and antigen，and between antibodies during evolution.By use of elitist strategy，the algorithm can be convergent with probability one.The feasibility and validity of the algorithm are validated by the calculation instance.Compared with standard genetic algorithm，the algorithm has improved the speed of convergence and has achieved higher capacity of global optimization.The instance shows that it is a high speed and fidelity method and provides a new approach for solving the problem of optimal path planning.

Key words: path planning, niche, immune clone, elitist strategy, immune algorithm