Journal ArticleDOI
A comparative study of Artificial Bee Colony algorithm
Dervis Karaboga,Bahriye Akay +1 more
TLDR
Results show that the performance of the ABC is better than or similar to those of other population-based algorithms with the advantage of employing fewer control parameters.About:
This article is published in Applied Mathematics and Computation.The article was published on 2009-08-01. It has received 2835 citations till now. The article focuses on the topics: Artificial bee colony algorithm & Meta-optimization.read more
Citations
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Journal ArticleDOI
Hybrid Seeker Optimization Algorithm for Global Optimization
TL;DR: Comparisons show that the proposed hybridization of the seeker optimization algorithm with the well known artificial bee colony (ABC) algorithm outperforms six state-of-the-art algorithms in terms of the quality of the resulting solutions as well as robustenss on most of the test functions.
Journal ArticleDOI
Cuckoo search with varied scaling factor
TL;DR: This study proposes a varied scaling factor (VSF) strategy that samples a value from the range [0,1] uniformly at random for each iteration of CS, and integrates the VSF strategy into several advanced CS variants.
Journal ArticleDOI
Lexicographic bottleneck mixed-model assembly line balancing problem
TL;DR: It is shown how a complex production planning problem can be solved using sophisticated artificial intelligence techniques with optimised parameters and two effective meta-heuristics are proposed.
Book ChapterDOI
Genetic Algorithm Based on Enhanced Selection and Log-Scaled Mutation Technique
TL;DR: The presented selection and mutation schemes improved GA, as named Enhanced Selection and Log-scaled Mutation GA (ESALOGA), selects the best chromosomes from a pool of parents and children after crossover to enhance the computational power of Genetic Algorithm (GA) for global optimization of multi-modal problems.
A new simplified swarm optimization (SSO) using exchange local search scheme
TL;DR: A novel simplified swarm optimization (SSO) algorithm to overcome the above convergence problem by incorporating it with the new local search strategy and can achieve the highest classification accuracy.
References
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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
Adaptation in natural and artificial systems
TL;DR: Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.
Journal ArticleDOI
Differential Evolution – A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces
Rainer Storn,Kenneth Price +1 more
TL;DR: In this article, a new heuristic approach for minimizing possibly nonlinear and non-differentiable continuous space functions is presented, which requires few control variables, is robust, easy to use, and lends itself very well to parallel computation.
Book
Self-Organizing Maps
TL;DR: The Self-Organising Map (SOM) algorithm was introduced by the author in 1981 as mentioned in this paper, and many applications form one of the major approaches to the contemporary artificial neural networks field, and new technologies have already been based on it.
Book
Genetic Algorithms + Data Structures = Evolution Programs
TL;DR: GAs and Evolution Programs for Various Discrete Problems, a Hierarchy of Evolution Programs and Heuristics, and Conclusions.