Abstract
We present in this paper a security-driven solution for scheduling of N independent jobs on M parallel machines that minimizes three different objectives simultaneously, namely the failure probability, the total completion time of the jobs and their respective tardiness. As this problem is NP-hard in the strong sense, a meta-heuristic method NSGA-II is proposed to solve it. This approach is based on the Pareto dominance relationship, providing no single optimal solution, but a set of solutions which are not dominated by each other. Thus, it was necessary to provide decision-making mechanisms selecting the best strategy from the Pareto frontier. The performance of the presented model and the applied GA is verified by a number of numerical experiments. The related results show the effectiveness of the proposed model and GA for small and medium-sized scheduling problems.
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Ga̧sior, J., Seredyński, F. (2013). Multi-objective Parallel Machines Scheduling for Fault-Tolerant Cloud Systems. In: Kołodziej, J., Di Martino, B., Talia, D., Xiong, K. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2013. Lecture Notes in Computer Science, vol 8285. Springer, Cham. https://doi.org/10.1007/978-3-319-03859-9_21
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DOI: https://doi.org/10.1007/978-3-319-03859-9_21
Publisher Name: Springer, Cham
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