Tabu-based evolutionary algorithm with negative selection for pareto-opfimization in distributed systems

被引：0
|
作者：
Balicki, Jerzy [1 ]
机构：
[1] Naval Univ Gdynia, Ul Smidowicza 69, PL-81103 Gdynia, Poland
来源：
ADVANCES ON ARTIFICIAL INTELLIGENCE, KNOWLEDGE ENGINEERING AND DATA BASES, PROCEEDINGS | 2008年
关键词：
evolutionary algorithm; multi-criterion optimization; Internet bank systems;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Reliability and the load balancing are crucial factors for a quality evaluation of distributed systems. Load balancing of the Web servers can be implemented by reduction of the workload of the bottleneck computer what improves both a performance of the system and the safety of the bottleneck computers. An evolutionary algorithm based on a tabu search procedure is discussed for multi-criteria optimization of distributed systems A tabu mutation is applied for minimization the workload of the bottleneck computer. It can be obtained by task assignment as well as selection of suitable computer sorts. Moreover, a negative selection procedure is developed for improving non-admissible solutions. Some numerical results are submitted.
引用
收藏
页码：327 / +
页数：2
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