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- W2964453452 abstract "Particle swarm optimization (PSO) is a population-based stochastic algorithm designed to solve complex optimization problems such as the Flexible Job Shop Scheduling Problem (FJSP). As a metaheuristic, the performance of the PSO is heavily affected by two elements: the size of the search-space and the way of its exploration. In this paper, we present a specific PSO algorithm for the FJSP that use Lower-bounds to bypass regions not containing optimal solutions. The proposed algorithm is a two-level PSO. The upper-level handles the mapping of operations to machines while the lower-level handles the ordering of operations. The performance gain in terms of solution optimality and CPU time, obtained by our method, has been validated by external FJSP benchmarks." @default.
- W2964453452 created "2019-08-13" @default.
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- W2964453452 date "2019-01-01" @default.
- W2964453452 modified "2023-09-26" @default.
- W2964453452 title "Toward a Two-Level PSO for FJS Problem" @default.
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- W2964453452 doi "https://doi.org/10.1109/sami.2019.8782738" @default.
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