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Combined Trust Region with Particle swarm for Multi-objective Optimisation

Author

Listed:
  • Zeinab M. H. Hendawy

    (Menofia University)

  • M. A. El-Shorbagy

    (Menofia university)

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.

Suggested Citation

  • Zeinab M. H. Hendawy & M. A. El-Shorbagy, 2015. "Combined Trust Region with Particle swarm for Multi-objective Optimisation," Proceedings of International Academic Conferences 2703860, International Institute of Social and Economic Sciences.
    • Handle: RePEc:sek:iacpro:2703860
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    File URL: https://iises.net/proceedings/18th-international-academic-conference-london/table-of-content/detail?cid=27&iid=046&rid=3860
    File Function: First version, 2015
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    Cited by:

    1. Mohammed A. El-Shorbagy & Fatma M. Al-Drees, 2023. "Studying the Effect of Introducing Chaotic Search on Improving the Performance of the Sine Cosine Algorithm to Solve Optimization Problems and Nonlinear System of Equations," Mathematics, MDPI, vol. 11(5), pages 1-25, March.

    More about this item

    Keywords

    Multi-objective Optimisation- Trust Region Method- Particle Swarm Optimisation- Weighted Method;

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