Pressure Vessel Design Simulation: Implementing of Multi-Swarm Particle Swarm Optimization

Sinan Q. Salih, Abdulrahman A. Alsewari, Z. Yaseen
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引用次数: 33

Abstract

The new era knowledge of optimization algorithm is massively boosted recently. Among several optimization models, multi-swarm approach has been proposed most recently for balancing the exploration and exploitation capability through the Particle Swarm Optimization (PSO) algorithm. The proposed multi-swarm model which is called Meeting Room Approach (MRA), is tested and evaluated based on solving normal and large-scale problems. In the current research, the feasibility of the proposed Multi-Swarm Particle Swarm Optimization (MPSO) is adopted to simulate mechanical engineering problem namely pressure vessel design (PVD). The results indicated the potential of the proposed MPSO model on simulating the PVD problem with optimum solution over the standalone PSO. Further, the current study results authenticated against other famous meta-heuristics models. Overall, MPSO reported an excellent optimization solution with fast convergence learning process.
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压力容器设计仿真:多群粒子群优化的实现
近年来,优化算法的新时代知识大量涌现。在众多优化模型中,最近提出的多群方法是通过粒子群优化算法来平衡勘探和开发能力。提出的多群模型被称为会议室方法(Meeting Room Approach, MRA),在解决常规问题和大规模问题的基础上进行了测试和评估。在目前的研究中,采用多群粒子群优化方法(MPSO)来模拟机械工程问题即压力容器设计(PVD)的可行性。结果表明,所提出的粒子群模型在模拟PVD问题上具有优于独立粒子群的最优解的潜力。此外,目前的研究结果验证了其他著名的元启发式模型。总体而言,MPSO报告了一种具有快速收敛学习过程的优秀优化方案。
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