The Modify Version of Artificial Bee Colony Algorithm to solve Real Optimization problems

The Artificial Bee Colony(ABC) algorithm is one of the best applicable optimization algorithm. In this work, we make some modifications to improve the ABC algorithm based on convergence speed of solution. In order to, we add some conditions to selected food sources by bees. So, if solution have been enough near to optimal solution, then further search exist around the food sources. That, this is near to optimal solution because, we can replace lower and upper bounds of food sources with smaller values relate to last search. Therefore, the new search is near to optimal solution and after n(1 < n << maxcycles of algorithm ) iteration, optimal solution achieves. Finally, we illustrate convergence speed of the MABC algorithm that is faster than ABC algorithm. There are some examples.