A novel weighted update position mechanism to improve the performance of sine cosine algorithm
Mostafa Meshkat, Mohsen Parhizgar · 2017
Sine cosine algorithm (SCA) is one of the most recent population-based optimization algorithms proposed for solving optimization problems. In the present study, in order to improve the performance of this algorithm, a new weighted update position mechanism (WUPM) was employed instead of the position update method of search agents in SCA. In the proposed method, in addition to a position and fitness, each search agent is assigned a weight based on its fitness. The position of each search agent is updated based on the average position of some of the other agents, the best solution obtained, and the previous weighted position of the search agent. In order to assess the performance of the proposed method, a set of benchmark functions was used. Comparison of the results indicated that in addition to a higher accuracy achieving the global optimum, the proposed method is able to converge faster compared to standard SCA.