关键词: 蚁群算法, 克隆选择, 混沌, 变异, 模拟退火

Abstract: Ant Colony Algorithm（ACA） is a stochastic optimization algorithm inspired by the behavior of ant looking for food.However，the standard ACA has some shortcomings，such as premature convergence，searching precision lowness and so forth.Based on the simulation of natural death process of 5% B-cell in biology clone selection，this paper proposes 8 kinds of updating algorithms according to intergeneration differential，theory of chaos，principle of mutation respectively，and selects the updated ants in terms of simulated annealing method.Numerical experiments show that the updating algorithm by using intergeneration differential and chaotic mutation is a good selection.Simultaneously，the updating effect is perfect when the updated ants are about 20%.This algorithm can effectively overcome the premature problem and speed up the convergence.

Key words: ant colony algorithm, clone selection, chaos, mutation, simulated annealing