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

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.