Ant direction hybrid differential evolution for solving large capacitor placement problems

This paper presents an ant direction hybrid differential evolution (ADHDE) with integer programming which is effective and efficient for solving large capacitor placement problems in distribution systems. The use of proper mutation operator in hybrid differential evolution (HDE) can accelerate the search of a global solution. However, the selection of mutation operator depends on the problem. In this study, the ADHDE method utilizes the concept of ant colony search to search the proper mutation operator to accelerate searching out the global solution. Various-scale application systems are used to compare the performance of the proposed method with HDE, simulated annealing, and ant system. Numerical results show that the performance of the proposed ADHDE method is better than the other methods. Also, the ADHDE method is superior to some other methods in terms of solution power loss and costs.