An Improved Black Widow Optimization Algorithm for Engineering Constrained Optimization Problems

In solving engineering constrained optimization problems, the conventional black widow algorithm (BWOA) has some shortcomings such as insufficient robustness and slow convergence speed. Therefore, an improved (IBWOA) is proposed by combining methods of double chaotic map, Cauchy center gravity inverse difference mutation golden sine guidance strategy. Firstly, quality initial population BWOA based on map; Secondly, in order to make full use information between current optimal position thus improve accuracy, (Gold-SA) introduced update individuals; Finally, barycenter reverse differential operator employed increase diversity population, avoid local global search ability algorithm. addition, characteristics IBWOA are analyzed Markov process probability reaches 1 for globally solution. The performance was evaluated eight continuous / discrete hybrid problems typical benchmark functions. results show that can speed effectively comparing with other algorithms.