Research on Optimal Path Planning Problem Based on an Adaptive Immune Algorithm
YU Zhen-hu · Microcomputer Information · 2009
In solving path planning ,standard genetic algorithm exists the problem of nonconvergence with probability one and inevitable degeneration including prematurity and decrease of diversity. Faced with this problem, A new algorithm named adaptive immune algorithm is presented and realized. 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 improved the speed of convergence and 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.