Due to the non-linearity and large scale of the problem (considerable number of alternatives and different criteria), global powerful optimization techniques are needed. In this study, we have implemented a multi-objective particle swarm optimization algorithm, augmented with an additional fuzzy controller for tuning algorithm parameters in order to determine an effective approximation of the Pareto front. Computational results have shown that the algorithm is able to produce high-quality solutions for all tested instances. Moreover, the algorithm is very flexible and able to obtain non-dominated alternative solutions for different scenarios and alternatives in the design of virtual enterprises. |
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CITATIONS
Cited by 1 scholarly publication.
Particle swarm optimization
Fuzzy logic
Mathematical modeling
Optimization (mathematics)
Computer programming
Data modeling
Manufacturing