Development of computer-controlled material handling model by means of fuzzy logic and genetic algorithms

The aim of the study is to develop a unique approach to the problem of material handling control by means of artificial intelligence (computer intelligence) with respect to automated guided vehicle (AGV) path routing. In the analysed case the material handling system is fully integrated with IT tools and is considered under the constraint that the path cannot be changed during travel along a given loop, therefore, the path is predicted prior to every successive loop. The vector (ordered set) of stations requesting transportation service was determined by means of fuzzy logic, while the sequence of stations in a loop was optimised with genetic algorithms. The dispatch station can play the role of a switching station between the zones, where every AGV path loop begins and ends. This paper presents a system for both AGVs and semi-autonomous transportation vehicles where the human driver is informed of the route to follow. The subsequent verification of the developed model, by means of computer simulation, confirms that the proposed solution is effective. While the presented solution can be applied in a discrete manufacturing system, it can be considered as a part of the general manufacturing concept. (C) 2019 Elsevier B.V. All rights reserved.