Journal ArticleDOI
Multiobjective cuckoo search for design optimization
Xin-She Yang,Suash Deb +1 more
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TLDR
A new cuckoo search for multiobjective optimization is formulated and applied to solve structural design problems such as beam design and disc brake design.About:
This article is published in Computers & Operations Research.The article was published on 2013-06-01. It has received 729 citations till now. The article focuses on the topics: Metaheuristic & Cuckoo search.read more
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Journal ArticleDOI
Artificial Intelligence and Bio-Inspired Soft Computing-Based Maximum Power Plant Tracking for a Solar Photovoltaic System under Non-Uniform Solar Irradiance Shading Conditions—A Review
Amjad Ali,Kashif Irshad,Mohammad Farhan Khan,Moinul Hossain,Ibrahim N. A. Al-Duais,Muhammad Zeeshan Malik +5 more
TL;DR: In this article, a comprehensive review of articles on soft computing-based maximum power point tracking (SC-MPPT) techniques under non-uniform irradiance conditions along with their operating principles, block/flow diagram is presented.
Journal ArticleDOI
Component sizing of a plug-in hybrid electric vehicle powertrain, Part A: coupling bio-inspired techniques to meshless variable-fidelity surrogate models
TL;DR: In the present investigation, the authors propose a variable fidelity optimisation framework for component sizing of a plug-in hybrid electric vehicle PHEV powertrain that can be divided into two different stages.
Proceedings ArticleDOI
Global Maximum Power Point Tracking for PV Array under Partial Shading using Cuckoo Search
TL;DR: The research in this paper is focussed on 6×4 TCT Configuration of PV array to bring out maximum energy under any environmental condition and Cuckoo search algorithm is applied under considered shadowing scenario.
Journal ArticleDOI
Minimization of Torque Ripple in the Brushless DC Motor Using Constrained Cuckoo Search Algorithm
TL;DR: In this article, the authors presented the application of the cuckoo search (CS) algorithm in attempts to the minimization of the commutation torque ripple in the brushless DC motor (BLDC).
Book ChapterDOI
A New Multiple Objective Cuckoo Search for University Course Timetabling Problem
TL;DR: A new multiple objective cuckoo search based timetabling (MOCST) tool has been developed in order to solve the multiple objective UCTP and it was found that the CSLF outperformed the CSGRW for almost all datasets whilst the computational times required by the proposed methods were slightly difference.
References
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Journal ArticleDOI
A fast and elitist multiobjective genetic algorithm: NSGA-II
TL;DR: This paper suggests a non-dominated sorting-based MOEA, called NSGA-II (Non-dominated Sorting Genetic Algorithm II), which alleviates all of the above three difficulties, and modify the definition of dominance in order to solve constrained multi-objective problems efficiently.
Proceedings ArticleDOI
Particle swarm optimization
TL;DR: A concept for the optimization of nonlinear functions using particle swarm methodology is introduced, and the evolution of several paradigms is outlined, and an implementation of one of the paradigm is discussed.
Book
Multi-Objective Optimization Using Evolutionary Algorithms
Kalyanmoy Deb,Deb Kalyanmoy +1 more
TL;DR: This text provides an excellent introduction to the use of evolutionary algorithms in multi-objective optimization, allowing use as a graduate course text or for self-study.
Journal ArticleDOI
Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach
Eckart Zitzler,Lothar Thiele +1 more
TL;DR: The proof-of-principle results obtained on two artificial problems as well as a larger problem, the synthesis of a digital hardware-software multiprocessor system, suggest that SPEA can be very effective in sampling from along the entire Pareto-optimal front and distributing the generated solutions over the tradeoff surface.
Journal ArticleDOI
MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition
Qingfu Zhang,Hui Li +1 more
TL;DR: Experimental results have demonstrated that MOEA/D with simple decomposition methods outperforms or performs similarly to MOGLS and NSGA-II on multiobjective 0-1 knapsack problems and continuous multiobjectives optimization problems.