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- W2549919612 abstract "This paper addresses the unrelated parallel machine scheduling problem with sequence-dependant setup times for minimizing total tardiness and workload imbalance. The mixed integer linear programming is proposed to model the studied problem. This problem is shown to be NP-hard in the strong sense. Thus, we propose a hybrid algorithm that combines differential evolution with particle swarm optimization, namely HDEPSO, in order to solve the given problem. Our objective is to achieve faster convergence rate and obtain better pareto optimal solutions. In order to demonstrate the efficiency and reliability of the proposed algorithm, a number of test problems are solved. The HDEPSO results are compared with two well-known multi- objective genetic algorithms in the literature, i.e. NSGA-II and SPEA-II based on some comparison metrics. Computational experiments indicate the superiority of the HDEPSO compared to these two genetic algorithms." @default.
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- W2549919612 date "2012-01-01" @default.
- W2549919612 modified "2023-09-27" @default.
- W2549919612 title "A Hybrid Differential Particle Swarm Optimization Approach to Solve a Multi-objective Parallel Machine Scheduling Problem" @default.
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