Journal ArticleDOI
Particle Swarm Optimization Applications to Mechanical Engineering- A Review
Ninad Kulkarni,Sujata Patekar,Trupti Bhoskar,Omkar Kulkarni,Ganesh Kakandikar,Vilas M. Nandedkar +5 more
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TLDR
The applications of PSO include optimal weight design of a gear train, Simultaneous Optimization of Design and Machining Tolerances, Process Parameter Optimization in Casting, and Machine Scheduling Problem.About:
This article is published in Materials Today: Proceedings.The article was published on 2015-01-01. It has received 55 citations till now. The article focuses on the topics: Multi-swarm optimization & Particle swarm optimization.read more
Citations
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Journal ArticleDOI
Particle Swarm Optimization: A Comprehensive Survey
TL;DR: Particle swarm optimization (PSO) is one of the most well-regarded swarm-based algorithms in the literature as mentioned in this paper , and many researchers have been modifying it resulting in a large number of PSO variants with either slightly or significantly better performance.
Journal ArticleDOI
Material and shape optimization of bi-directional functionally graded plates by GIGA and an improved multi-objective particle swarm optimization algorithm
TL;DR: A method integrating generalized iso-geometrical analysis (GIGA) and an improved multi-objective particle swarm optimization algorithm (IMOPSO) is proposed, with numerous technical advantages.
Journal ArticleDOI
Application of generalized regression neural network optimized by fruit fly optimization algorithm for fracture toughness in a pearlitic steel
Ling Qiao,Yong Liu,Jingchuan Zhu +2 more
TL;DR: In this article, a generalized regression neural network (GRNN) optimized by fruit fly optimization algorithm (FOA) was developed to improve the predictive accuracy of small number of samples, and the quantitative relationship between alloying elements and fracture toughness was further investigated based on the developed model.
Journal ArticleDOI
Adaptive chaotic particle swarm algorithm for isogeometric multi-objective size optimization of FG plates
Chao Wang,Chao Wang,Tiantang Yu,Jose L. Curiel-Sosa,Neng-gang Xie,Tinh Quoc Bui,Tinh Quoc Bui +6 more
TL;DR: An effective multi-objective optimization methodology that combines the isogeometric analysis (IGA) and adaptive chaotic particle swarm algorithm is presented for optimizing ceramic volume fraction (CVF) distribution of functionally graded plates (FGPs) under eigenfrequencies.
Journal ArticleDOI
Artificial intelligence techniques in refrigeration system modelling and optimization: A multi-disciplinary review
Rasel Ahmed,Shuhaimi Mahadzir,Nor Erniza Mohammad Rozali,Kallol Biswas,Fahad Matovu,Kamran Ahmed +5 more
TL;DR: This comprehensive review presents state-of-the-art theory and application of the most widely used CI techniques such as GA, PSO, SA, DE, HTS, CRO, MOGA, and NSGA II in the optimization of various refrigeration systems.
References
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Journal ArticleDOI
Particle swarm optimization
TL;DR: A snapshot of particle swarming from the authors’ perspective, including variations in the algorithm, current and ongoing research, applications and open problems, is included.
Proceedings ArticleDOI
A new optimizer using particle swarm theory
TL;DR: The optimization of nonlinear functions using particle swarm methodology is described and implementations of two paradigms are discussed and compared, including a recently developed locally oriented paradigm.
Proceedings ArticleDOI
A modified particle swarm optimizer
Yuhui Shi,Russell C. Eberhart +1 more
TL;DR: A new parameter, called inertia weight, is introduced into the original particle swarm optimizer, which resembles a school of flying birds since it adjusts its flying according to its own flying experience and its companions' flying experience.
Journal ArticleDOI
Particle Swarm Optimization: Basic Concepts, Variants and Applications in Power Systems
TL;DR: This paper presents a detailed overview of the basic concepts of PSO and its variants, and provides a comprehensive survey on the power system applications that have benefited from the powerful nature ofPSO as an optimization technique.
Proceedings ArticleDOI
A new locally convergent particle swarm optimiser
TL;DR: This paper introduces a new Particle Swarm Optimisation (PSO) algorithm with strong local convergence properties, which performs much better with a smaller number of particles, compared to the original PSO.