A novel disruption in biogeography-based optimization with application to optimal power flow problem

Biogeography-based optimization (BBO) is an emerging meta-heuristic algorithm. Due to ease of implementation and very few user-dependent parameters, BBO gained popularity among researchers. The performance of BBO is highly dependent on its two operators, migration and mutation. The performance of BBO can be significantly improved by either modifying these operators or by introducing a new operator into it. This paper proposes a new operator, namely the disruption operator to improve the capability of exploration and exploitation in BBO. The proposed DisruptBBO (DBBO) has been tested on well-known benchmark problems and compared with various versions of BBO and other state-of-the-art metaheuristics. The experimental results and statistical analyses confirm the superior performance of the proposed DBBO in solving various nonlinear complex optimization problems. The proposed algorithm has also been applied to the optimal power flow optimization problem from the electrical engineering background.