Particle swarm optimization - tabu search (PSO-TS) with mass extinction applied to nonlinear optimization problems / Crystal Dianne C. Yutiamco

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Yutiamco, Crystal Dianne C

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TextLanguage: English Publication details: 2010Description: 101 leavesSubject(s):

Dissertation note: Thesis (BS Computer Science) -- University of the Philippines Mindanao, 2010 Abstract: This study serves an attempt to improve the solutions acquired by the hybrid PSO with Mass Extinction by incorporating another metaheuristic called tabu search. This study also serves as an additional contribution to several scientific fields and may lead to another research in the future. PSO-TS with Mass Extinction is an algorithm which aims to get an optimal solution for the Rosenbrock, Rastigin and Griewank function. The parameter setting s were divided to three groups according to the particle dimensions for all the benchmark problems and the average solution quality, average solution time, best solution quality and best solution time were determined for each problem. The results for PSO-TS with Mass Extinction were also compared with those of PSO with Mass Extinction using charts and tables. For most cases, PSO-TS with Mass Extinction outperforms PSO with Mass Extinction in terms of the average solution quality and best solution quality. However, it took a longer time for PSO-TS with Mass Extinction to achieve a solution as compared to PSO with Mass Extinction since PSO-TS with Mass Extinction required additional processes for the Tabu Search Algorithm

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Cover image	Item type	Current library	Collection	Call number	Status	Date due	Barcode
	Thesis	University Library General Reference	Room-Use Only	LG993.5 2010 C6 Y88 (Browse shelf(Opens below))	Not For Loan		3UPML00012605
	Thesis	University Library Archives and Records	Preservation Copy	LG993.5 2010 C6 Y88 (Browse shelf(Opens below))	Not For Loan		3UPML00033244

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Thesis (BS Computer Science) -- University of the Philippines Mindanao, 2010

This study serves an attempt to improve the solutions acquired by the hybrid PSO with Mass Extinction by incorporating another metaheuristic called tabu search. This study also serves as an additional contribution to several scientific fields and may lead to another research in the future. PSO-TS with Mass Extinction is an algorithm which aims to get an optimal solution for the Rosenbrock, Rastigin and Griewank function. The parameter setting s were divided to three groups according to the particle dimensions for all the benchmark problems and the average solution quality, average solution time, best solution quality and best solution time were determined for each problem. The results for PSO-TS with Mass Extinction were also compared with those of PSO with Mass Extinction using charts and tables. For most cases, PSO-TS with Mass Extinction outperforms PSO with Mass Extinction in terms of the average solution quality and best solution quality. However, it took a longer time for PSO-TS with Mass Extinction to achieve a solution as compared to PSO with Mass Extinction since PSO-TS with Mass Extinction required additional processes for the Tabu Search Algorithm

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