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Li, W.X., Zhou, Q., Zhu, Y. and Pan, F. (2012) An Improved MOPSO with a Crowding Distance Based External Archive Maintenance Strategy. In: Tan, Y., Shi, Y. and Ji, Z., Eds., Advances in Swarm Intelligence. ICSI 2012, Springer, 74-82.

has been cited by the following article:

• TITLE: A New Multiobjective Particle Swarm Optimization Using Local Displacement and Local Guides

  AUTHORS: Saïd Charriffaini Rawhoudine, Abdoulhafar Halassi Bacar

  KEYWORDS: Particle Swarm Optimization, Multiobjective Optimization, Attractor-Based Displacement, Square Root Distance, Crowding Distance

  JOURNAL NAME: Open Journal of Optimization, Vol.13 No.2, June 27, 2024

  ABSTRACT: This paper introduces a novel variant of particle swarm optimization that leverages local displacements through attractors for addressing multiobjective optimization problems. The method incorporates a square root distance mechanism into the external archives to enhance the diversity. We evaluate the performance of the proposed approach on a set of constrained and unconstrained multiobjective test functions, establishing a benchmark for comparison. In order to gauge its effectiveness relative to established techniques, we conduct a comprehensive comparison with well-known approaches such as SMPSO, NSGA2 and SPEA2. The numerical results demonstrate that our method not only achieves efficiency but also exhibits competitiveness when compared to evolutionary algorithms. Particularly noteworthy is its superior performance in terms of convergence and diversification, surpassing the capabilities of its predecessors.