Combined Trust Region with Particle swarm for Multi-objective Optimisation

Zeinab M. H. Hendawy () and M. A. El-Shorbagy ()
Additional contact information
Zeinab M. H. Hendawy: Menofia University
M. A. El-Shorbagy: Menofia university

No 2703860, Proceedings of International Academic Conferences from International Institute of Social and Economic Sciences

Abstract: A novel approach is presented to solve multi-objective optimisation problems (MOOP).The algorithm combines the Trust Region (TR) algorithm with the Particle Swarm Optimisation (PSO) method.The MOOP is converted to a single objective optimisation problem (SOOP) using weighted method and some of the points in the search space are generated. For each point, the TR algorithm is used to solve the SOOP to obtain a point on the Pareto frontier. All points obtained are used as particle position for PSO to get all the points on the Pareto frontier. The algorithm is tested using several bench mark problems and coded using MATLAB 7.2 which show successful result in finding a Pareto optimal set.

Keywords: Multi-objective; Optimisation-; Trust; Region; Method-; Particle; Swarm; Optimisation-; Weighted; Method (search for similar items in EconPapers)
Pages: 19 pages
Date: 2015-09
New Economics Papers: this item is included in nep-cmp
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Published in Proceedings of the Proceedings of the 18th International Academic Conference, London, Sep 2015, pages 292-310

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Persistent link: https://EconPapers.repec.org/RePEc:sek:iacpro:2703860

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