Flying Squirrel Optimizer (FSO): A novel SI-based optimization algorithm for engineering problems

Abstract

This paper provides a novel meta-heuristic optimization algorithm. The behaviors of flying squirrels in the nature are the main inspiration of this research. These behaviors include flying from tree to tree and walking on the ground or on a tree branch to find food. They also contact each other with chirp or squeak. This algorithm is named flying squirrel optimizer (FSO). Two main theories of motion were used for the simulation of flying and walking of the flying squirrels and they are Lévy flight and normal random walk. FSO is also benchmarked on twelve mathematical functions and the answers are compared with MFO, PSO, GSA, BA, FPA, SMS, and FA. The results show that FSO can provide good results when compared with these well-known meta-heuristics approaches. Five classical engineering problems and a real issue in the field of dam engineering were employed to challenge the FSO abilities in solving engineering design problems. The results also show that the proposed FSO algorithm can be used on a wide range of problems with unknown search spaces.