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
Citations
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Journal ArticleDOI
A survey on applications and variants of the cuckoo search algorithm
TL;DR: A comprehensive review of all conducting intensive research survey into the pros and cons, main architecture, and extended versions of this algorithm.
Journal ArticleDOI
Artificial ecosystem-based optimization: a novel nature-inspired meta-heuristic algorithm
TL;DR: The overall comparisons suggest that the optimization performance of AEO outperforms that of other state-of-the-art counterparts, especially for real-world engineering problems, and is more competitive than other reported methods in terms of both convergence rate and computational efforts.
Journal ArticleDOI
Improved cuckoo search algorithm for hybrid flow shop scheduling problems to minimize makespan
TL;DR: A recently developed cuckoo search (CS) metaheuristic algorithm is presented in this paper to minimize the makespan for the HFS scheduling problems and computational results show that the ICS algorithm outperforms many other metaheuristics.
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A comparison of different global MPPT techniques based on meta-heuristic algorithms for photovoltaic system subjected to partial shading conditions
TL;DR: A comprehensive assessment of the behavior performance of two optimization techniques for extracting the global MPP from the partially shaded PVPS shows that the CS−based tracker has superiority compared with PSO.
Journal ArticleDOI
Nature-Inspired Optimization Algorithms: Challenges and Open Problems.
TL;DR: In this paper, the authors provide an in-depth review of some recent nature-inspired algorithms with the emphasis on their search mechanisms and mathematical foundations, identifying some challenging issues and five open problems concerning the analysis of algorithmic convergence and stability.
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.