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Advisor(s)
Abstract(s)
This paper presents a comprehensive study of the Particle Swarm Optimization (PSO) algorithm, called complex-order PSO (CPSO). In the core of new set of algorithms, we employ the complex-order derivative and the conjugate order differential concepts in the position and velocity adaption mechanisms. To determine the influence of the control parameters on the quality of the results, a sensitivity analysis is conducted. A number of value- and rank-based tests assesses the algorithms’ performance. For a suite of benchmark functions, the standard deviation and the mean best of the results are reported. Additionally, the Friedman test specifies the average ranking from the obtained results. The effect of the complex-order operation and the population size are analyzed using the Taguchi test. An application example illustrates the performance of the CPSO.
Description
Keywords
Fractional calculus Complex-order Particle swarm optimization Sensitivity analysis