Some numerical experiments on multi-criterion tabu programming for finding Pareto-optimal solutions
WSEAS TRANSACTIONS on SYSTEMS
ICCOMP'09 Proceedings of the WSEAES 13th international conference on Computers
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Designing of the general complex systems like the semantic Web, computer networks, production scheduling or robot path planning require some extremely efficient optimization techniques that support decision making process [7]. Decision making for complex systems is based on multicriterion-optimisation. We use several criteria to identification the sensitive preferences of a decision maker. For instance, a task assignment in a distributed computer system may reduce bath the total cast af a program run and aworklaad of the bottleneck computer [2]. The probability that all computers remain fault-free during the execution of the modules assigned to computers is another criterion of evaluation task assignments. Same crucial multicriterion evolutionary algorithms have been described in [3]. However, multi-criteria evolutionary algorithms consume a lot of time to calculate the set of efficient solutions. To avoid this disadvantage, we introduce some quantum-based algorithms Because there are not accessible quantum computers we simulate the quantum computers on classical ones. In such a way quantum-inspired algorithms can be used for a computer decision aid, too.