ORIGINAL ARTICLE Approaches of fuzzy systems applied to an AGV dispatching system in a FMS V. F. Caridá & O. Morandin Jr. & C. C. M. Tuma Received: 12 August 2014 /Accepted: 18 January 2015 /Published online: 12 February 2015 # Springer-Verlag London 2015 Abstract Excellence in manufacturing systems has been rec- ognized as one of the main factors behind the success of in- dustrial companies or production companies. New technology for manufacturing processes plays a significant role in this process. Achieving the potential of technological innovations in production, however, requires a wide range of management, as well as engineering issues related to the system. The han- dling capacity of advanced materials is essential because with- out this ability of providing the material needed for the proper workstation at the right time and in the right amount, the whole plant will become “bogged down.” This makes it less efficient and thus produces less profit, and/or it operates at higher costs. This paper proposes two approaches for the dispatching of AGV (automated guided vehicle) using sys- tems fuzzy. The first use hierarchical fuzzy rule-based model building in which the main feature is to make the base of fuzzy rules is smaller and simpler but with high coverage and inter- pretability. The second use adaptive genetic fuzzy system with simple prediction in which the main feature is to increase the sensitivity of the system about the variables. Both approaches using multiple attributes and having the objective decrease the makespan in a FMS (flexible manufacturing system). Keywords Automated guided vehicles . AGV dispatching . Fuzzy system . Multi-attribute . FMS . Makespan minimization 1 Introduction There is a widespread perception that material handling is a key component in reaching flexibility, manufacturing, energy, and agility goals. Material handling technology to address these concerns is the automated guided vehicle (AGV). An AGV is a mobile robot/vehicle used to transport materials in manufacturing environments, designed to receive and execute instructions, follow a path or track, and receive and distribute materials. The vehicles generally follow a path that can go in many directions and can usually be easily reconfigured ac- cording to the manufacturer’ s plant. Instructions for an AGV show where the vehicle should move, how to reach the desti- nation, and what to do when it arrives there [1]. 1.1 General problems related to AGV automated guided vehicles (AGVs) are popular materials handling systems in automated processes, flexible manufacturing systems, and even in container handling in ports [2–4]. Many projects related to AGV have been proposed. There are several points inherent to the problem that increasingly seeks improvement for greater flexibility, competitiveness, quality, etc. Different objectives can be found in the literature as to minimize the total transport cost of the path, minimizing travel distance or minimizing the travel time [5]. Le-Anh and De Koster [6] are presented a review of the development and control to automated guided vehi- cle systems. The authors cite the key issues that involve the automated guided vehicle systems, such as amount and type of vehicles, routing, position of the idle vehi- cle, battery management/fuel ratio, deadlock resolution, and scheduling of vehicles. V. F. Caridá (*) : O. Morandin Jr. : C. C. M. Tuma Department of Computer Science, Federal University of São Carlos, Rodovia Washington Luis, Km 235, 13565-905 São Carlos, SP, Brazil e-mail: vinicius_carida@dc.ufscar.br Int J Adv Manuf Technol (2015) 79:615–625 DOI 10.1007/s00170-015-6833-8