Grey wolf optimizer with global search strategy

A grey wolf optimization algorithm with global search strategy is proposed to address the issue that the standard grey wolf optimizer (GWO) has the disadvantage of global search ability. Adaptive weight and search strategy randomly are added to strengthen the global search ability. 13 test function are used to test the performance of the proposed algorithm compared with other well-known meta-heuristics, and the results show that the proposed algorithm is feasible and effective.