Self-Organizing Migrating Algorithm with narrowing search space strategy for robot path planning

This article introduces a version of the Self-Organizing Migrating Algorithm with narrowing search space strategy named iSOMA. Compared to previous two versions, SOMA T3A and Pareto that ranked 3rd 5th respectively in IEEE CEC (Congress on Evolutionary Computation) 2019 competition, iSOMA is equipped more advanced features notable improvements including applying jumps order, immediate update, instead searching intersecting edges hyperplanes, partial replacement individuals population when global best improved no further. Moreover, proposed algorithm organized into processes initialization, self-organizing, migrating, replacement. We tested performance this new by using three benchmark test suites 2013, 2015, 2017, which, together contain total 73 functions. Not only it superior other SOMAs, but also yields promising results against representatives well-known algorithmic families such as Differential Evolution Particle Swarm Optimization. we demonstrate application for path planning drone, while avoiding static obstacles catching target.