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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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Journal ArticleDOI

A fuzzified Pareto multiobjective cuckoo search algorithm for power losses minimization incorporating SVC

TL;DR: This paper presents an application of multiobjective cuckoo search (MOCS) algorithm for reduction in transmission line losses by placing static VAR compensator (SVC) at an optimal location.
Journal ArticleDOI

Multi-objective cuckoo search algorithm for optimized pathways for 75 % renewable electricity mix by 2050 in Algeria

TL;DR: In this paper, the authors presented the most credible options to increase the share of renewable energy resource in the Algerian electricity power system by 2050 using multi-objective cuckoo search algorithm.
Journal ArticleDOI

Cuckoo search algorithm based on repeat-cycle asymptotic self-learning and self-evolving disturbance for function optimization

TL;DR: A new improved cuckoo search algorithm based on the repeat-cycle asymptotic self-learning and self-evolving disturbance (RC-SSCS) is proposed, which has better convergence velocity and optimization accuracy.
Book ChapterDOI

Nature-Inspired Algorithms: Success and Challenges

TL;DR: The key features of nature-inspired metaheuristic algorithms are discussed by analyzing their diversity and adaptation, exploration and exploitation, attractions and diffusion mechanisms, as well as some open problems.
Journal ArticleDOI

Multi-objective cuckoo search algorithm for optimized pathways for 75 % renewable electricity mix by 2050 in Algeria

- 01 Feb 2022 - 
TL;DR: In this article , the authors presented the most credible options to increase the share of renewable energy resource in the Algerian electricity power system by 2050 using multi-objective cuckoo search algorithm.
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.