Abstract
ABSTRACTWe compare two models of two-level facility location problems for network design in autonomous ground vehicle (AGV) operations. The two-level model consists of locations for charging stations (main facilities), as well as for storage locations (substations). Demand points will represent processing locations. In both formulations, demands are assigned to substations and substations are assigned to main facilities. The formulations differ in whether each connection between a facility and a substation is counted once in absolute terms, or once per demand. These represent two different views, in which transfer between a main facility and substation is carried out either in bulk, e.g. using a shuttle, or by each AGV independently. Selected experimental results are presented for geometric networks and networks consisting of uniformly distributed points on a regular mesh. These results indicate that the two formulations lead to vastly different network designs in terms of the number of facilities and connectivity.
Highlights
The rise of Industry 4.0 and the increasing importance of cyber-physical systems have motivated a number of new applications and optimisation problems in production and manufacturing (Jazdi, 2014; Lee, Bagheri, & Kao, 2015)
Selected experimental results are presented for geometric networks and networks consisting of uniformly distributed points on a regular mesh. These results indicate that the two formulations lead to vastly different network designs in terms of the number of facilities and connectivity
Architectural design is among the main aspects (Touchton, Galluzzo, Kent, & Crane, 2006), along with in-plant transport organisation (Gola & Kłosowski, 2017; Kłosowski, Gola, & Thibbotuwawa, 2018), scheduling and rescheduling in autonomous ground vehicle (AGV) operations (Bocewicz, Banaszak, Nielsen, & Muszyński, 2017), predictive control of AGVs (Falcone, Borrelli, Tseng, Asgari, & Hrovat, 2008), as well as tracking of the vehicles (Wit, Crane, & Armstrong, 2004)
Summary
The rise of Industry 4.0 and the increasing importance of cyber-physical systems have motivated a number of new applications and optimisation problems in production and manufacturing (Jazdi, 2014; Lee, Bagheri, & Kao, 2015). In this context, interesting optimisation problems arise in the design of cyber-physical system infrastructure, which is of an increasing importance to improve efficiency of various operations (Rajkumar, Lee, Sha, & Stankovic, 2010) Such infrastructure problems often lead to specific location problems (Nasab, Tavana, & Yousefi, 2014), e.g. typically in determining charging station locations (Mehar & Senouci, 2013). The second model counts each such connection per demand The latter model is practically equivalent to what is currently known in the literature as the multilevel facility location problem (Marić, 2012). These models are interpreted in a way such that the connections between charging hubs and storage space can be interpreted as carried out in bulk, e.g. using a shuttle service, or, alternatively, with each AGV independently.
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