Constrained optimization via particle evolutionary swarm optimization algorithm (PESO)
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
On the performance of artificial bee colony (ABC) algorithm
Applied Soft Computing
Journal of Global Optimization
Evolutionary algorithms, homomorphous mappings, and constrained parameter optimization
Evolutionary Computation
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
Differential evolution in constrained numerical optimization: An empirical study
Information Sciences: an International Journal
A modified Artificial Bee Colony (ABC) algorithm for constrained optimization problems
Applied Soft Computing
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
Engineering optimizations via nature-inspired virtual bee algorithms
IWINAC'05 Proceedings of the First international work-conference on the Interplay Between Natural and Artificial Computation conference on Artificial Intelligence and Knowledge Engineering Applications: a bioinspired approach - Volume Part II
Useful infeasible solutions in engineering optimization with evolutionary algorithms
MICAI'05 Proceedings of the 4th Mexican international conference on Advances in Artificial Intelligence
A refactoring method for cache-efficient swarm intelligence algorithms
Information Sciences: an International Journal
Search biases in constrained evolutionary optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Stochastic ranking for constrained evolutionary optimization
IEEE Transactions on Evolutionary Computation
Society and civilization: An optimization algorithm based on the simulation of social behavior
IEEE Transactions on Evolutionary Computation
A simple multimembered evolution strategy to solve constrained optimization problems
IEEE Transactions on Evolutionary Computation
Coordinating metaheuristic agents with swarm intelligence
Journal of Intelligent Manufacturing
Journal of Intelligent Manufacturing
Journal of Intelligent Manufacturing
International Journal of Metaheuristics
Computational Optimization and Applications
Hi-index | 0.00 |
Artificial bee colony (ABC) algorithm developed by Karaboga is a nature inspired metaheuristic based on honey bee foraging behavior. It was successfully applied to continuous unconstrained optimization problems and later it was extended to constrained design problems as well. This paper introduces an upgraded artificial bee colony (UABC) algorithm for constrained optimization problems. Our UABC algorithm enhances fine-tuning characteristics of the modification rate parameter and employs modified scout bee phase of the ABC algorithm. This upgraded algorithm has been implemented and tested on standard engineering benchmark problems and the performance was compared to the performance of the latest Akay and Karaboga's ABC algorithm. Our numerical results show that the proposed UABC algorithm produces better or equal best and average solutions in less evaluations in all cases.