An Artificial Bee Colony Algorithm for Solving Constrained Optimization Problems

By using the direct comparison rule of a fixed proportion for individual selection so that a certain percentage of better infeasible solutions remain in the population and introducing the optimal solution information at the scout bee stage so that the scout bee has more opportunities to search near the optimal solution, an artificial bee colony algorithm based the direct comparison rule of a fixed proportion is presented to overcome the disadvantages of artificial bee colony algorithm easily trapped in local optimum. The standard test functions results illustrate that the improved artificial bee colony algorithm works better than basic artificial bee colony algorithm for most test functions.