An estimation of distribution algorithm with diversity preservation

作者：Cheng Yu Hu^*; Wang Xue Song; Hao Ming Lin

来源：Acta Electronica Sinica, 2010, 38(3): 591-597.

• Bench-mark problems
• Convergence speed
• Diversity estimation
• Ergodicity
• Estimation of distribution algorithms
• Fitness values
• Initial values
• Mutation operators
• Optimal solutions
• Premature convergence

In order to solve the premature convergence problem existing in the traditional estimation of distribution algorithm (EDA), based on the analysis of methods for diversity preservation and reasons for premature convergence, an estimation of distribution algorithm with diversity preservation (EDA-DP) is proposed. A chaotic mutation operator is introduced into EDA by taking advantage of the randomness, ergodicity, initial value sensitivity and regularity of chaos. The EDA-DP is able to adjust its mutation radius in an adaptive way according to the fitness value and the distance between each individual. Moreover, the EDA-DP is able to generate its offspring population by making use of the concentration inside the population. The EDA-DP is evaluated on a set of benchmark problems and the experimental results show that the precision of the optimal solutions and the convergence speed are improved, thanks to the EDA-DP effectively overcomes the premature convergence problem.

• 出版日期2010
• 单位中国矿业大学（北京）