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Journal ArticleDOI

Multiobjective cuckoo search for design optimization

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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.
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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.

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A Novel MPPT Method Based on Cuckoo Search Algorithm and Golden Section Search Algorithm for Partially Shaded PV System

TL;DR: A new MPPT algorithm is proposed by combining the CS algorithm with golden section search (GSS) to take beneficial features from both the algorithms to improve the performance of the algorithm.
Journal ArticleDOI

Multi-Objective Stochastic Fractal Search: a powerful algorithm for solving complex multi-objective optimization problems

TL;DR: The results of simulations and the Wilcoxon rank-sum test showed that the MOSFS is able to provide the most promising Pareto front for the problem considering various performance metrics at a 95% confidence level.
Journal ArticleDOI

Optimal location of STATCOM in multimachine power system for increasing loadability by Cuckoo Search algorithm

TL;DR: A new metaheuristic method, the Cuckoo Search (CS) algorithm, based on the life of a bird family is proposed in this paper for optimal design of static synchronous compensator (STATCOM) in a multimachine environment.
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Swarm Intelligence: Past, Present and Future

TL;DR: A short but timely analysis about swarm intelligence algorithms and their links with self-organization is provided in this article, where different characteristics and properties are analyzed from both mathematical and qualitative perspectives.
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Bio-inspired computation: Recent development on the modifications of the cuckoo search algorithm

TL;DR: The recent advances of these modifications made to the original cuckoo search are reviewed by analyzing recent published papers tackling this subject and it is found that the population reduction and usage of biased random walk are the most frequently used modifications.
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

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

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

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.