Boosting sparrow search algorithm for multi-strategy-assist engineering optimization problems

An improved optimization algorithm, namely, multi-strategy-sparrow search algorithm (MSSSA), is proposed to solve highly non-linear problems. In MSSSA, a circle map utilized improve the quality of population. Moreover, adaptive survival escape strategy (ASES) enhance ability sparrows. producer stage, craziness factor integrated with ASES introduced accuracy and ability. scout facilitates sparrows successful from danger. Besides, opposition-based learning or Gaussian–Chachy variation helps optimal individuals local solutions. The performance MSSSA investigated on well-known 23 basic functions CEC2014 test suite. Furthermore, applied optimize real-life engineering results show that presents excellent feasibility practicality compared other state-of-the-art algorithms.