Univariate Marginal Distribution Algorithm in Combination with Extremal Optimization (EO, GEO)
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- 作者：Mitra Hashemi (1) Mitra.hash@yahoo.com
Mohammad Reza Meybodi (2) mmeybodi@aut.ac.ir - 关键词：Univariate Marginal Distribution Algorithm – ; Extremal Optimization – ; Generalized Extremal Optimization – ; Estimation of Distribution Algorithm
- 刊名：Lecture Notes in Computer Science
- 出版时间：2011
- 出版年：2011
- 期刊代码：99_0302-9743
- 类别：cp
- 卷：7063
- 期：1
- 页码：220-227
- 数据来源：sp
摘要
The UMDA algorithm is a type of Estimation of Distribution Algorithms. This algorithm has better performance compared to others such as genetic algorithm in terms of speed, memory consumption and accuracy of solutions. It can explore unknown parts of search space well. It uses a probability vector and individuals of the population are created through the sampling. Furthermore, EO algorithm is suitable for local search of near global best solution in search space, and it dose not stuck in local optimum. Hence, combining these two algorithms is able to create interaction between two fundamental concepts in evolutionary algorithms, exploration and exploitation, and achieve better results of this paper represent the performance of the proposed algorithm on two NP-hard problems, multi processor scheduling problem and graph bi-partitioning problem.