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This paper proposes a novel optimization method in order to real time implementation based on standard particle swarm optimization idea and characteristics of chaotic maps which is named as individual particle optimization (IPO). Three typical benchmark functions are used to validate the proposed algorithm performance and runtime and then compare with that of the other algorithms known as modified...
This paper proposes a new fuzzy tuned inertia weight particle swarm optimization (FIPSO) which remarkably outperforms the standard PSO, previous fuzzy as well as adaptive based PSO methods. Two benchmark functions with asymmetric initial range settings are used to validate the proposed algorithm and compare its performance with those of the other tuned parameter PSO algorithms. Numerical results indicate...
This paper proposes a local optima avoidable particle swarm optimization (LOAPSO) which remarkably outperforms the standard PSO in the sense that it can avoid entrapment in local optimum. Three benchmark functions are used to validate the proposed algorithm and compare its performance with that of the other algorithms known as hybrid PSOs and six functions reported in SIS2005 are used to better verification...
This paper proposes a new fuzzy tuned parameter particle swarm optimization (FPPSO) which remarkably outperforms the standard PSO as well as the previous fuzzy based approaches. Two benchmark functions with asymmetric initial range settings are used to validate the proposed algorithm and compare its performance with that of the other algorithms known as fuzzy based PSO. Numerical results indicate...
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