Hybridization of genetic algorithm and fuzzy based TOPSIS method to solve the robot path planning problem for multi objectives

Abstract

A variety of approaches are employed to solve the Mobile Robot Path Planning Problem (MRPP), which is the essential domain of research from industrial automation to domestic appliances. Since MRPP is categorized as an NP-hard problem, non-deterministic approaches are preferred to obtain optimal results. The Genetic Algorithm(GA) is the popular methodology for determining the optimal path for robot navigation. The complexity increases in finding the optimal path for the MRPP problem, if more than one objective is to be considered. To reduce the complexity, one of the multi-criteria decision analysis (MCDA) methodologies with fuzzy logic is hybridized to solve MRPP without losing the advantage of the GA approach. In this article, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is employed for determining the best path out of given paths. As a preprocessing of the population, a Genetic Algorithm (GA) is employed, which is having the advantage of exploring the population with crossover, mutation, and selection operators. The output of the GA is given to the Fuzzy TOPSIS method where the degree of preference is given as the linguistic variable.