Journal ArticleDOI
A comparative study of Artificial Bee Colony algorithm
Dervis Karaboga,Bahriye Akay +1 more
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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
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A Discrete Artificial Bee Colony Algorithm for Minimizing the Total Flow Time in the Blocking Flow Shop Scheduling
TL;DR: In this article, a discrete artificial bee colony algorithm is proposed for solving the blocking flow shop scheduling problem with total flow time criterion, where the solution in the algorithm is represented as job permutation and an initialization scheme based on a variant of the NEH (Nawaz-Enscore-Ham) heuristic and a local search is designed to construct the initial population with both quality and diversity.
Journal ArticleDOI
Solving Traveling Salesman Problem by Using Combinatorial Artificial Bee Colony Algorithms
Dervis Karaboga,Beyza Gorkemli +1 more
TL;DR: In this paper, new versions of ABC algorithm to solve TSP are introduced and described in detail, and both CABC and qCABC algorithms demonstrate good performance for TSP and also the new definition in quick ABC (qABC) improves the convergence performance of CABC on TSP.
Journal ArticleDOI
Heuristic algorithm based optimal power flow model incorporating stochastic renewable energy sources
TL;DR: A grey wolf optimisation technique (GWO) is employed to achieve optimisation in modified IEEE-30 and IEEE-57 bus test systems and it is compared in simulation to five other nature-inspired global optimisation algorithms and two well-established hybrid algorithms.
Journal ArticleDOI
Estimation of fuel cost curve parameters for thermal power plants using the ABC algorithm
TL;DR: This paper presents an application of the articial bee colony (ABC) algorithm to estimate the fuel cost curve parameters of thermal power plants and shows that the ABC algorithm is stronger than the others at solving such a problem.
Journal ArticleDOI
A novel artificial bee colony algorithm with local and global information interaction
Qiuzhen Lin,Miaomiao Zhu,Genghui Li,Genghui Li,Wenjun Wang,Laizhong Cui,Jianyong Chen,Jian Lu +7 more
TL;DR: The experimental results show that ABCLGII is better than or at least competitive to the state-of-the-art ABC variants in terms of solution quality, robustness and convergence speed.
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.