Multi-criterion Tabu Programming for Pareto-optimal Task Assignment in Distributed Computer Systems

Multi-criterion tabu programming is a new approach for a decision making support and it can be applied to determine the Pareto solutions. Similarly to rules applied in the genetic programming, tabu programming solves problems by using a general solver that is based on a tabu algorithm. In the formulated task assignment problem as a multi-criterion question, both a workload of a bottleneck computer and the cost of system are minimized; in contrast, a reliability of the distributed system is maximized. Moreover, there are constraints for the performance of the distributed systems and the probability that all tasks meet their deadlines. In addition, constraints related to memory limits and computer locations are imposed on the feasible task assignment. Finally, results of some numerical experiments have been presented. Key-Words: Tabu search algorithm, multi-criterion optimization, genetic programming