A Novel Self-Adaptive Master-Slave Parallel Genetic Algorithm
In this paper, a new deterministic interpretation algorithm and its parallel implementation for interval nonlinear programming are proposed. The self-adaptive master-slave parallel genetic algorithm is proposed to solve the optimization problem with large and repeated computation load in the deterministic framework. The proposed ask-reply method can be used to solve the unbalance distribution problem of computation load among slave computers. The proposed algorithm and its parallel solution can sufficiently improve the computation performance and reliability of parallel system.
-nonlinear programming interval parameter parallel computation genetic algorithm
Zheng Jiang Bin Liu
Department of Automation, College of Information Science and Engineering, Wuhan University of Science and Technology, China
国际会议
2006现代科技国际研讨会(The International Workshop on Modern Science and Technology in 2006)
北京
英文
456-460
2006-04-01（万方平台首次上网日期，不代表论文的发表时间）