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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A novel fuzzy time series forecasting method based on the improved artificial fish swarm optimization algorithm
TL;DR: A novel fuzzy time series forecasting method which uses a hybrid artificial fish swarm optimization algorithm for the determination of interval lengths and introduces the chemotactic behavior of Bacterial foraging optimization into foraging behavior.
Journal ArticleDOI
A hybrid DPSO with Levy flight for scheduling MIMO radar tasks
TL;DR: A hybrid discrete particle swarm optimization (DPSO) algorithm with Levy flight is proposed for a solution to the model that takes the task internal structure, the characteristics of task scheduling in the MIMO radar and the three task scheduling principles into consideration.
Journal Article
Review of Different Sequence Motif Finding Algorithms.
TL;DR: A general classification of motif discovery algorithms with new sub-categories that facilitate building a successful motif discovery algorithm is presented and a summary of comparison between them is presented.
Journal ArticleDOI
A novel complex valued cuckoo search algorithm.
Yongquan Zhou,Hongqing Zheng +1 more
TL;DR: To expand the information of nest individuals, the idea of complex-valued encoding is used in cuckoo search (PCS); the gene of individuals is denoted by plurality, so a diploid swarm is structured by a sequence plurality.
Journal ArticleDOI
Raccoon Optimization Algorithm
TL;DR: A novel algorithm called the raccoon optimization algorithm (ROA), inspired by the rummaging behaviors of real raccoons for food, which achieves higher accuracy with lower coverage time and is compared with nine other well-known optimization algorithms.
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.