Grey Wolf Optimization Algorithm for Single Mobile Robot Scheduling

Abstract

Development of reliable and efficient material transport system is one of the basic requirements for creating an intelligent manufacturing environment. Nowadays, intelligent mobile robots have been widely used as one of the components to satisfy this requirement. In this paper, a methodology based on Grey Wolf Optimization (GWO) algorithm is proposed in order to find the optimal solution of the nondeterministic polynomial-hard (NP-hard) single mobile robot scheduling problem. The performance criterion is to minimize total transportation time of the mobile robot while it performs internal transport of raw materials, goods, and parts in manufacturing system. The scheduling plans are obtained in Matlab environment and tested by Khepera II mobile robot system within a static laboratory model of manufacturing environment. Experimental results show the applicability and effectiveness of the developed intelligent approach in real world conditions.