Job-shop based framework for simultaneous scheduling of machines and automated guided vehicles

A Timed Colored Petri Net Simulation-Based Self-Adaptive Collaboration Method for Production-Logistics Systems

“…A token in this place represents a production task p 2 A token in this place represents a worker p 3 A token in this place represents a material p 4 A token in this place represents the attendance of the worker p 5 A token in this place represents enough materials p 6 A token in this place represents the absence of the worker p 7 A token in this place represents insufficient materials p 8 A token in this place represents the sataus information of a machine p 9 A token in this place represents the sataus information of an AGV p 10 A token in this place represents the finish of the machine processing p 11 A token in this place represents the request to the logistics task p 12 A token in this place represents the detection result p 13 A token in this place represents the qualified WIP p 14 A token in this place represents the nearest and available AGV p 15 A token in this place represents the unqualified WIP p 16 A token in this place represents the remote or unavailable AGV p 17 A token in this place represents an out-buffer p 18 A token in this place represents the selected logistics task p 19 A token in this place represents the correct start point p 20 A token in this place represents the transport time p 21 A token in this place represents the transport to the destination p 22 A token in this place represents the correct destination p 23 A token in this place represents the end and next cycle Figure 3 shows the TCPN model of the self-adaptive collaboration method. This model refers to the basic cycle of production-logistics systems, which consists of twenty-three places and fourteen transitions.…”

Hybrid multiobjective genetic algorithms for integrated dynamic scheduling and routing of jobs and automated-guided vehicle (AGV) in flexible manufacturing systems (FMS) environment

“…Simultaneously, scheduling of machines and AGV is the only means of ensuring the validity of all the individual schedules [2]. Algorithms in the literature that simultaneously schedule jobs and AGVs alone while ignoring AGVs routing and dispatching includes single objective approach [13][14][15][16][17][18] and multiple objective approach [19,20]. Bilge and Ulusoy [15] present an algorithm for simultaneous scheduling of workstations and AGVs in FMS using nonlinear mixed integer programming.…”

Complexity of Scheduling Problem in Single-Machine Flexible Manufacturing System with Cyclic Transportation and Unlimited Buffers

“…Such a model is the simplest system with the AGV-based transportation, and its complexity status has not been studied yet. Most literature has been devoted to FMS problems with many vehicles [22][23][24] and with the unidirectional single-loop transportation system [25]. A single vehicle has been analyzed in the context of more complex systems: with buffers [26], with many machines (station) [27], or with dedicated machines [23].…”

“…Most literature has been devoted to FMS problems with many vehicles [22][23][24] and with the unidirectional single-loop transportation system [25]. A single vehicle has been analyzed in the context of more complex systems: with buffers [26], with many machines (station) [27], or with dedicated machines [23]. Particularly, Suri and Desiraju [28] considered the production environment with only one vehicle, but in a more complex FMS, namely in the FMS with a single discrete material handling device (MHD).…”

“…Particularly, Suri and Desiraju [28] considered the production environment with only one vehicle, but in a more complex FMS, namely in the FMS with a single discrete material handling device (MHD). Lacomme et al [23] deal with the problem of simultaneously scheduling jobs on machines and identical automated guided vehicles, analyzing many machines and many AGVs.…”