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
Optimization of PV Based Standalone Hybrid Energy System using Cuckoo Search Algorithm
TL;DR: Using a real world data for an existing educational organization in India, it is proven that the proposed optimization method meets all the requirements of the system and PV/B/DG configuration returns a lower annualized cost as well as leads to lower emissions.
Book ChapterDOI
Co-Operation of Biology-Related Algorithms for Constrained Multiobjective Optimization
TL;DR: Simulation results suggest that the proposed algorithm COBRA-m works effectively and is first validated against a subset of test functions, and then applied to known multiobjective design problems such as welded beam design and disc brake design.
Book ChapterDOI
Hybridization Cuckoo Search Algorithm for Extracting the ODF Maxima
TL;DR: This research presents a series of hybridizations that can improve the performance of the basic BCSA and achieve favorable results.
Journal ArticleDOI
Comparing the performance of different types of distributed fuzzy-based traffic signal controllers
Proceedings ArticleDOI
The Adaptive Discrete Cuckoo Search for Parallel Flow Shop Problem
Lei Zhang,Nan Yin,Shaocan Wang +2 more
TL;DR: To solve the problem aiming at minimizing maximum makespan, an adaptive discrete cuckoo search (ADCS) algorithm is proposed, which introduces cross and mutation disturbance factors, and proposes an adaptive parameter.
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.