LAUSR

Zone-controlled, guidepath-based transport system (ZC-GBTS) is a modeling abstraction that has been used extensively for the modeling of the safe interaction of a number of agents that circulate in a constricted medium. The traffic scheduling problem in these transport systems is very hard, and in some recent work of ours, we have proposed a model predictive control (MPC) scheme for simplifying this problem. The detailed implementation of this MPC scheme depends on certain structural and operational properties of the underlying ZC-GBTS. In this article, we detail the aforementioned MPC scheme for a ZC-GBTS subclass that is characterized as “open and irreversible”; the presented results leverage some earlier similar developments of ours for the subclass of “open and reversible” ZC-GBTS. Note to Practitioners—Open and irreversible zone-controlled, guidepath-based transport system is a natural abstraction of the traffic dynamics that take place in many unit-load material handling systems (MHSs), like the automated guided vehicle (AGV) systems that are used in various production and logistics environments and the overhead monorail systems that are used in most semiconductor manufacturing facilities. In these environments, vehicles are circulating in a “guidepath network” that is defined either by the physical structure of the employed MHS (as in the case of the overhead monorail systems) or, more artificially, in an effort to isolate the traffic of these vehicles from the surrounding environment (as in the case of the AGV systems). Furthermore, in order to ensure safe and collision-free motion for the traveling vehicles, the various edges of this guidepath network are further divided into zones, and it is stipulated that each zone can be allocated to at most one agent at any time. This restriction renders the considered transport systems susceptible to deadlock, and therefore, their traffic controller must control the generated traffic for time-based performance considerations, like the maximization of the system throughput or the minimization of the experienced delays, but also for ensuring traffic-liveness, i.e., the ability of every vehicle to complete successfully its current assignment and engage in similar assignments in the future. The resulting problem is very complex, and the current article provides a complete and computationally efficient solution to it.