Abstract
The application of Particle Swarm Optimization (PSO) on combinatorial optimization problems is limited, and it is due to the continuous nature of PSO. In order to solve the Multiobjective Permutation Flowshop Sequencing Problem (MPFSP), a Discrete Particle Swarm Optimization (DPSO) algorithm is proposed. To obtain a well approximation of true Pareto front, the phenotype sharing function of the objective space is applied in the definition of fitness function. The effectiveness of the proposed DPSO has been analyzed using 5 problems with the objectives of minimizing the makespan and the total tardiness, and 20 benchmarks problems with the objectives of minimizing the makespan and the total flowtime. The result shows that the proposed DPSO can reach a good approximation of true Pareto front.KeywordsMultiobjective Permutation Flow Shop SequencingDiscrete Particle SwarmMakespanTotal TardinessTotal Flowtime
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