Analysis Design and Applications of Intelligent Algorithms

Abstract

After analyzing the research gaps and study of various population based algorithms newlinethree algorithms selected for research namely PSO, ABC and AMO. Based on cons newlineand prons of these algorithms following objectives are formed: newline1. Modify the existing nature-inspired algorithms (i.e. PSO, ABC and AMO) newlinein order to make them more efficient and accurate by enhancing their diversification newlineand intensification capabilities. This may possible by tuning newlineof control parameters, hybridization of one algorithm with other population newlinebased probabilistic or deterministic algorithm(s) and introducing new newlinecontrol parameters or new step. newline2. Discovery of application of newly developed algorithms to solve real world newlinecomplex optimization problems like Welded beam design optimization problem, newlinePressure Vessel design without Granularity, Frequency-Modulated sound newlinewave and Compression Spring problem. newline1.5 Research Contributions newlineEvery step of the research process which is adopted to carry out this research work newlineis briefly shown in Figure 1.2. newlineTo accomplish the devised objectives, new variants of PSO, ABC and AMO are newlinedesigned. The developed algorithms are compared with the existing algorithms newlineand some recent variants of PSO, ABC and AMO on the basis of accuracy, efficiency newlineand reliability. Results proved that proposed variants outperform existing newlinealgorithms. newline