免疫算法与其他随机优化算法的比较分析

Comparative Analysis between Immune Algorithm and Other Random Searching Algorithms

详细描述了免疫算法的基本原理、步骤和寻优机理,以及抗体的抑制和促进、记忆单元更新、亲和性计算等特点。阐述了免疫算法抗原、抗体与实际问题的映射关系。用其他随机优化算法(模拟退火算法、遗传算法、进化规划等)与免疫算法进行了比较研究,给出了他们的异同点、免疫算法的优点等。利用旅行商问题(TSP)、随机优化算法测试函数对免疫算法及其他算法进行了测试分析。实例分析表明,免疫算法是一种收敛速度快、收敛性好的算法。

This paper describes detailedly the basic principles and processes of immune algorithm(IA). The optimizing mechanism, promotion and suppression of antibodyproduction, memory education and the calculation of affinity of IA are analyzed. This paper explains the properties of IA , the mapping relationship between antibody/antigen of IA and actual problem, and the difference between IA and other heuristic algorithms(genetic algorithm, evolutionary programming, evolutionary strategies and genetic programming, simulated annealing algorithm etc.). The convergent character of IA is tested using TSP problem and some test functions. From the results, IA is a remarkable algorithm with good convergence.