On the performance of artificial bee colony (ABC) algorithm
Applied Soft Computing
Journal of Global Optimization
An artificial bee colony algorithm for the leaf-constrained minimum spanning tree problem
Applied Soft Computing
Using bees to solve a data-mining problem expressed as a max-sat one
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
Cooperative bees swarm for solving the maximum weighted satisfiability problem
IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
Artificial bee colony algorithm for the capacitated vehicle routing problem
ECC'11 Proceedings of the 5th European conference on European computing conference
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
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This paper describes an object-oriented software system for continuous optimization by a modified artificial bee colony (ABC) metaheuristic. Karaboga's ABC algorithm was successfully used on many optimization problems and there is also a corresponding program in C. We implemented a modified version in C# which is easier for maintenance since it is object-oriented and which uses threads and significantly increases execution speed on multicore processors. The application includes flexible GUI (graphical user interface) and it was successfully tested on standard benchmark problems and one additional problem.