Evolutionary Algorithms in Engineering Applications
Evolutionary Algorithms in Engineering Applications
How to Solve It: Modern Heuristics
How to Solve It: Modern Heuristics
Derivative-Free Filter Simulated Annealing Method for Constrained Continuous Global Optimization
Journal of Global Optimization
Journal of Global Optimization
Self-adaptive velocity particle swarm optimization for solving constrained optimization problems
Journal of Global Optimization
Artificial Bee Colony (ABC) Optimization Algorithm for Solving Constrained Optimization Problems
IFSA '07 Proceedings of the 12th international Fuzzy Systems Association world congress on Foundations of Fuzzy Logic and Soft Computing
Particle swarm optimization: Tabu search approach to constrained engineering optimization problems
WSEAS Transactions on Mathematics
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WSEAS TRANSACTIONS on SYSTEMS
Image edge detection using ant colony optimization
WSEAS Transactions on Signal Processing
Unified particle swarm optimization for solving constrained engineering optimization problems
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part III
Useful infeasible solutions in engineering optimization with evolutionary algorithms
MICAI'05 Proceedings of the 4th Mexican international conference on Advances in Artificial Intelligence
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Artificial bee colony algorithm is an optimization algorithm based on a particular intelligent behaviour of honeybee swarms. In this paper we present a novel algorithm named GABC which integrates artificial bee colony algorithm (ABC) with self-adaptive guidance adjusted for engineering optimization problems. The novel algorithm speeds up the convergence and improves the algorithm's exploitation. We tested our guided algorithm on four standard engineering benchmark problems. The experimental results show that GABC algorithm can outperform ABC algorithm in most of the cases.