- Tytuł:
- A hybrid PSO approach for solving non-convex optimization problems
- Autorzy:
-
Ganesan, T.
Vasant, P.
Elamvazuthy, I. - Tematy:
-
Kuhn-Tucker conditions (KT)
non-convex optimization
particle swarm optimization (PSO)
semi-classical particle swarm optimization (SPSO) - Pokaż więcej
- Data publikacji:
- 2012
- Powiązania:
- https://bibliotekanauki.pl/articles/229756.pdf Link otwiera się w nowym oknie
- Źródło:
-
Archives of Control Sciences; 2012, 22, 1; 87-105
1230-2384 - Pojawia się w:
- Archives of Control Sciences
- Opis:
- The aim of this paper is to propose an improved particle swarm optimization (PSO) procedure for non-convex optimization problems. This approach embeds classical methods which are the Kuhn-Tucker (KT) conditions and the Hessian matrix into the fitness function. This generates a semi-classical PSO algorithm (SPSO). The classical component improves the PSO method in terms of its capacity to search for optimal solutions in non-convex scenarios. In this work, the development and the testing of the refined the SPSO algorithm was carried out. The SPSO algorithm was tested against two engineering design problems which were; ‘optimization of the design of a pressure vessel’ (P1) and the ‘optimization of the design of a tension/compression spring’ (P2). The computational performance of the SPSO algorithm was then compared against the modified particle swarm optimization (PSO) algorithm of previous work on the same engineering problems. Comparative studies and analysis were then carried out based on the optimized results. It was observed that the SPSO provides a better minimum with a higher quality constraint satisfaction as compared to the PSO approach in the previous work.
- Dostawca treści:
- Biblioteka Nauki
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