Multi-strategy Remora Optimization Algorithm for Solving Multi-extremum Problems

Abstract A metaheuristic algorithm that simulates the foraging behavior of remora has been proposed in recent years, called ROA. ROA mainly host parasitism and switching remora. However, experiment, it was found there is still room for improvement performance When dealing with complex optimization problems, often falls into local optimal solutions, also problem too-slow convergence. Inspired by natural rule “Survival fittest”, this paper proposes a random restart strategy to improve ability jump out solution. Secondly, inspired remora, adds an information entropy evaluation visual perception based on With blessing three strategies, multi-strategy Remora Optimization Algorithm (MSROA) proposed. Through 23 benchmark functions IEEE CEC2017 test functions, MSROA comprehensively tested, experimental results show strong capabilities. In order further verify application practice, tests through five practical engineering which proves competitiveness solving problems.