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
Study on improved cuckoo search algorithm applied in parameters estimation of multi-layer soil: 1D and 3D
TL;DR: In this paper, an improved cuckoo search (ICS) algorithm is presented to solve the parameter estimation problem of soil structure, the objective function is constructed based on the relative root-mean-square error between measured and calculated soil apparent resistivity curves.
Proceedings ArticleDOI
Computation Offloading Optimization in Mobile Edge Computing Based on Multi-Objective Cuckoo Search Algorithm
Chunjin Song,Hui Zhou +1 more
TL;DR: Simulation studies indicate that the proposed DMOCS-CO algorithm can effectively achieve the multi-objective optimization of computation offloading in mobile edge computing and perform better than two other classic algorithms.
Book ChapterDOI
Analysis of Variable Learning Rate Back Propagation with Cuckoo Search Algorithm for Data Classification
TL;DR: A novel meta-heuristic search algorithm, called cuckoo search (CS), with variable learning rate to train the network, which will speed up the slow convergence and solve the local minima problem of the backpropagation algorithm.
Journal ArticleDOI
An application of the whale optimization algorithm with Levy flight strategy for clustering of medical datasets
TL;DR: In this paper, a new and effective clustering algorithm was developed by using the Whale Optimization Algorithm (WOA) and Levy flight (LF) strategy that imitates the hunting behavior of whales.
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.