Novel fish swarm heuristics for bound constrained global optimization problems

Authors:
Ana Maria A. C. Rocha;Edite M. G. P. Fernandes;Tiago F. M. C. Martins
Affiliations:
Department of Production and Systems, University of Minho, Braga, Portugal;Algoritmi R&D Centre, University of Minho, Braga, Portugal;Algoritmi R&D Centre, University of Minho, Braga, Portugal
Venue:
ICCSA'11 Proceedings of the 2011 international conference on Computational science and its applications - Volume Part III
Year:
2011

Citing 8
Cited 5

A Numerical Evaluation of Several Stochastic Algorithms on Selected Continuous Global Optimization Test Problems

Journal of Global Optimization
Design and Analysis of Experiments

Design and Analysis of Experiments
A particle swarm pattern search method for bound constrained global optimization

Journal of Global Optimization
A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm

Journal of Global Optimization
A hybrid alternate two phases particle swarm optimization algorithm for flow shop scheduling problem

Computers and Industrial Engineering
Continuous ant colony system and tabu search algorithms hybridized for global minimization of continuous multi-minima functions

Computational Optimization and Applications
Homogeneous genetic algorithms

International Journal of Computer Mathematics
An artificial fish swarm algorithm based and ABC supported qos unicast routing scheme in NGI

ISPA'06 Proceedings of the 2006 international conference on Frontiers of High Performance Computing and Networking

Artificial fish swarm algorithm for unconstrained optimization problems

AMERICAN-MATH'12/CEA'12 Proceedings of the 6th WSEAS international conference on Computer Engineering and Applications, and Proceedings of the 2012 American conference on Applied Mathematics
An artificial fish swarm filter-based method for constrained global optimization

ICCSA'12 Proceedings of the 12th international conference on Computational Science and Its Applications - Volume Part III
Solving multidimensional 0---1 knapsack problem with an artificial fish swarm algorithm

ICCSA'12 Proceedings of the 12th international conference on Computational Science and Its Applications - Volume Part III
An artificial fish swarm algorithm based hyperbolic augmented Lagrangian method

Journal of Computational and Applied Mathematics
A simplified binary artificial fish swarm algorithm for 0-1 quadratic knapsack problems

Journal of Computational and Applied Mathematics

Quantified Score

Hi-index	0.00

Visualization

Abstract

The heuristics herein presented are modified versions of the artificial fish swarm algorithm for global optimization. The new ideas aim to improve solution accuracy and reduce computational costs, in particular the number of function evaluations. The modifications also focus on special point movements, such as the random, search and the leap movements. A local search is applied to refine promising regions. An extension to bound constrained problems is also presented. To assess the performance of the two proposed heuristics, we use the performance profiles as proposed by Dolan and Moré in 2002. A comparison with three stochastic methods from the literature is included.