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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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Citations
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Journal ArticleDOI

Survey of Lévy Flight-Based Metaheuristics for Optimization

TL;DR: A comprehensive survey of the Lévy flight-based metaheuristic algorithms is conducted and the future insights and development direction in the area of LÉvy flight are discussed.
Proceedings ArticleDOI

Cuckoo search algorithm and its application for secondary protein structure prediction

TL;DR: This study investigates application of cuckoo search (CS) algorithm on the protein folding problem based on AB off-lattice model and demonstrates that CS outperforms other algorithms in a meaningful way.
Journal ArticleDOI

Dominant color component and adaptive whale optimization algorithm for multilevel thresholding of color images

TL;DR: In this article , the dominant color component (DCC) of an image is extracted for optimal multilevel thresholding and a novel segmentation score is introduced to justify the methodology.
Book ChapterDOI

Optimization of Control Systems by Cuckoo Search

TL;DR: Comparative results with GA prove the effectiveness of CS in the optimization of feedback control systems with a generalized PID controller.
Journal ArticleDOI

Parameter selection for CLAHE using multi-objective cuckoo search algorithm for image contrast enhancement

TL;DR: In this article, Multi-objective Cuckoo Search (MOCS) is employed to determine optimal parameters for the Contrast Limited Adaptive Histogram Equalization (CLAHE) method.
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.