Hybrid Cooperative Scatter Search Algorithm with Elite Learning Mechanism

A novel hybrid cooperative scatter search (SS) algorithm with an elite learning mechanism (HSSA) is proposed for addressing complex continuous global optimization problems. The HSSA integrates the evolutionary mechanism of the backtracking search algorithm (BSA) into the reference set update process of SS. In addition, an elite individual-guided learning mechanism is proposed to guide the evolutionary direction of the population through the information provided by the current optimal individual. An opposition-based learning mechanism is adopted to avoid the population from falling into stagnation. Experimental results conducted on the CEC2017 benchmark test set demonstrate the effectiveness of the HSSA algorithm.