The use of Automated Guided Vehicles for container loading and unloading has emerged as a key solution in response to the increasing demand for port efficiency, driven by the growing volume of port operations. We formulate a routing problem, extended from existing literature, that determines the trajectories of these vehicles in an automated port environment while ensuring collision-free paths. We show that when the physical paths of the AGVs is fixed the problem reduces to a job shop scheduling problem with blocking constraints and no swap allowed, very little studied in the literature. We also develop an Iterative Path Reinsertion algorithm to improve the trajectories of the AGV for a given solution. Results show the efficiency of our approach both in terms of solution quality and of computational time for instances of various sizes. The conclusion outlines future research directions.

Port automation has emerged as a transformative solution enabling seaport management to efficiently handle the escalating volume of operations, driven in part by the advancements in low-cost long-distance maritime transport. In this context, the use of Automated Guided Vehicles for the loading and unloading of ships creates a need to optimize the conflict-free routing of these vehicles, in order to guarantee the safe transportation of goods within automated container terminals. In this work, we propose an Integer Linear Programming model to address the problem of collision-free path planning of Automated Guided Vehicles in container terminals where each vehicle is associated to one routing request. Numerical experiments are performed to evaluate the proposed method’s performances. Conclusions are drawn regarding its efficiency, and future avenues of research to address the problem are proposed.

This paper is about routing problem of Automated Intelligent Vehicles (AIVs) in a port. The objective is to prove the effectiveness of automated system for the transfer of containers in port terminals. The capacity of ships keeps increasing which means a huge volume of transported containers. For competition reasons, the time needed to load/unload ships must be reduced. For that, an automated system becomes a priority in order to increase the productivity and reduce operating costs. This paper is about modeling and scheduling problems to enable the routing of the AIV s. The modeling is done with transition timed Petri nets (T - TPN) that behave under earliest firing policy. The scheduling problem of AIVs is treated using Beam search with the obj ective of finding a control sequence between an initial state and a reference one with minimal time. An example is used to illustrate the approach.

This paper is about the incremental computation of control sequences for complex discrete event systems (DES) in uncertain environments. Transition-timed Petri nets (T-TPN) that behave under earliest firing policy are used to model a class of flexible manufacturing systems (FMS) where operations are proceeded with partial routing flexibility (namely hybrid FMS). Uncertainties are assumed to occur due to interruption of operations or unreliable resources. The objective is to find a control sequence from an initial state to a reference one with a trade-off between performance and robustness. For that, a systematic T-TPN-based multi-level formalism is used for the modelling. Then a new cost function is introduced to estimate the time and risk to reach the reference. A modified beam search algorithm is also proposed to selectively explore the PN state space and search for the best control sequence.

In this paper a systematic method is proposed for the modeling of hybrid flexible manufacturing systems (FMS) with timed Petri nets including buffer places. Hybrid FMS are workshops consisting of a combination of operations, some in job shop and others in open shop. Three basic functions are proposed to iteratively construct the complete model. The method automatically builds the incidence matrices, the initial marking vector and the temporal parameter vector from a synthetic description of the workshop.