Negative selection with ranking procedure in tabu-based multi-criterion evolutionary algorithm for task assignment

In this paper, an improved negative selection procedure to handle constraints in a multi-criterion evolutionary algorithm has been proposed. The problem that is of interest to us is the complex task assignment for a distributed computer system. Both a workload of a bottleneck computer and the cost of system are minimized; in contrast, a reliability of the system is maximized. Moreover, constraints related to memory limits and computer locations are imposed. Finally, an evolutionary algorithm with tabu search procedure and the improved negative selection is proposed to provide effective solutions.