Open AccessJournal Article
Multi-objective particle swarm optimization algorithm based on crowding distance sorting and its application
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TL;DR: Comparison results illustrated that this algorithm outperformed Strength Pareto Evolutionary Algorithm 2(SPEA2) in the convergence and diversity characteristics of Pare to optimal front with shorter computation time, higher efficiency and robustness.
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About: This article is published in Computer Integrated Manufacturing Systems. The article was published on 01 Jan 2008. and is currently open access. The article focuses on the topics: Multi-swarm optimization & Particle swarm optimization.
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A cluster based PSO with leader updating mechanism and ring-topology for multimodal multi-objective optimization
TL;DR: A new cluster based particle swarm optimization algorithm (PSO) with leader updating mechanism and ring-topology for solving MMOPs is presented and leader updating strategy is introduced to identify the best leaders in PSO.
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Evolving fusion-based visibility restoration model for hazy remote sensing images using dynamic differential evolution
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Multi-objective optimal scheduling of reconfigurable assembly line for cloud manufacturing
TL;DR: Experimental results indicate that the proposed approach can significantly improve the production efficiency (i.e. increased production load balance, minimized reconstruction cost, and minimized delayed workload).
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Multi-objective optimization design method for the machine tool’s structural parts based on computer-aided engineering
TL;DR: In this paper, a multi-objective optimization design method was proposed to improve the static and dynamic performance of the machine tool's structural parts and achieve lightweight design at the same time, while a modified particle swarm optimization algorithm and grey relational analysis method were adapted to solve the model.
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Multi-Objective Optimization of Start-up Strategy for Pumped Storage Units
TL;DR: Compared with the single objective optimization, the proposed multi-objective optimization of start-up strategy not only greatly shortens the speed rise time and the speed overshoot, but also makes the speed curve quickly stabilize.
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