Institutul de Matematică şi Informatică "Vladimir Andrunachievici"
Universitatea de Stat din MoldovaRO EN
Artificial Bee Colony with Different Mutation Schemes: A comparative study
Authors: I. Abu Doush, B. Hasan, M. Al-Betar, E. Al Maghayreh, F. Alkhateeb, M. Hamdan
Keywords: Artiifcial Bee Colony, Evolutionary Algorithms, Mutation, Meta-heuristic algorithm, Polynomial mutation.
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Keywords: Artiifcial Bee Colony, Evolutionary Algorithms, Mutation, Meta-heuristic algorithm, Polynomial mutation.
Abstract
Artificial Bee Colony (ABC) is a swarm-based metaheuristic for continuous optimization. Recent work hybridized this algorithm with other metaheuristics in order to improve performance. The work in this paper, experimentally evaluates the use of different mutation operators with the ABC algorithm. The introduced operator is activated according to a determined probability called mutation rate (MR). The results on standard benchmark function suggest that the use of this operator improves performance in terms of convergence speed and quality of final obtained solution. It shows that Power and Polynomial mutations give best results. The fastest convergence was for the mutation rate value (MR=0.2).Iyad Abu Doush 1, Basima Hani F. Hasan 1, Mohammed Azmi Al-Betar 2, Eslam Al Maghayreh 1, Faisal Alkhateeb 1
1 Yarmouk University
Computer Science Department, Irbid, Jordan
E-mail:
2Jadara University
Computer Science Department, Irbid, Jordan
1 Yarmouk University
Computer Science Department, Irbid, Jordan
E-mail:
2Jadara University
Computer Science Department, Irbid, Jordan
Fulltext
– 0.50 Mb
Contents
- Solving Problems in Various Domains by Hybrid Models of High Performance Computations
- Chromatic Polynomials Of Some (m,l) - Hyperwheels
- A New Full-Newton Step O(n) Infeasible Interior-Point Algorithm for P*(k)-horizontal Linear Complementarity Problems
- Search tree-based approach for the p-median problem using the ant colony optimization algorithm
- Artificial Bee Colony with Different Mutation Schemes: A comparative study
- A Note on Solvable Polynomial Algebras
- Dynamic Object Identification with SOM-based neural networks
- Evaluating the impact of software metrics on defects prediction. Part 2
