A Generalized Stochastic Petri Net Approach for Modeling Activities of Human Operators in Intermodal Container Terminals

Abstract

This paper proposes a Petri net (PN) representation of the activities performed by the key human operators for unloading/loading containers in an intermodal maritime container terminal (CT) with a low level of automation. These processes are the core of the export, import, and transshipment cycles executed in the terminal. The aim of this paper is to consider both the human component and the material handling resources, e.g., cranes and transporters, by defining an accurate model, which describes how to coordinate humans and use the system resources necessary for serving mother or feeder ships. The developed generalized stochastic PN-based model is of limited complexity and represents a complete, unambiguous, and readable model of the target process before coding it in the target simulation tool. The modular integrated model is tested and validated by the simulation of typical and perturbed scenarios of the Taranto CT, a real terminal that is taken as a case study for its complexity and similarity to CTs with multiple transport modes.Note to Practitioners-This paper proposes a new perspective for modeling, simulating, and controlling container terminals (CTs). Usually, the participation of human operators to the unloading/loading processes is neglected. However, a bad behavior of human operator can significantly modify the CT performances. Moreover, a few CTs are characterized by a low or partial level of automation. Then, the cooperation between the humans and the material handling equipment is important for executing several key tasks with efficiency (with respect to the deadlines), safety, and sustainability for humans. The complexity arising from a human-in-the-loop system demands for more accurate models that can reduce prediction errors and avoid unnecessary extra-equipment costs. Therefore, we propose an approach to explicitly consider the roles and main functions performed by a typical team of specialized operators. To verify the model accuracy and validate it, we simulate both standard and perturbed conditions of the Taranto CT. Given that the operators are usually assigned well-established tasks, the approach can be useful: 1) to improve the employment of humans and their supervisory activity; 2) to identify critical or faulty situations that involve operators or are caused by their errors and anomalous behaviors, thereby to improve safety and protect the handling equipment (e.g., by identifying delays and message losses in Manuscript operators' communication); and 3) to increase automation, by reassigning tasks from humans to automatic equipment.

Restoration duration estimation applying generally distributed transition stochastic Petri nets considering the switching failure of breakers

“…Similarly, for each transition, t ∈ T, pre-set and postset, are shown as ∘ t and t°, respectively. The system state changes based on the PN firing rule: a transition is enabled if its prior place(s) has/have at least as many tokens as the weight of its input arc(s) [25]. To acquire more knowledge in this field, interested readers can refer to [26][27][28].…”

Modeling and Solving the Three Seaside Operational Problems Using an Object-Oriented and Timed Predicate/Transition Net

“…For example, Yin et al [39] proposed an agent-based approach for dynamic port planning. Murty et al [27] used a Decision Support System (DSS) to help make decisions for yard operations in a CT. The DSS aimed to use minimal resources to minimize the berthing time of vessels, the waiting time of customer trucks, the congestion on the roads, storage blocks, and docks inside the terminal, and to best utilize the available storage space.…”

“…task_token ("ship 9",0,container (11,50,45)). task_token ("ship 9",0,container (13,27,22)). task_token ("ship 9",0,container (15,50,45)).…”

“…The branch and bound (B & B) approach has been applied towards QCSP [23]. Timed Petri net (PN) has been used to deal with QCSP [26], and stochastic PNs have been applied for the modeling and analysis of the activities of human operations [27] and logistic systems [28] for a container terminal. Decision support systems (DSSs) have been used to solve both BAP and QCAP [2], and as a tool for decision making [3,29].…”

Performance Analysis of Honeypot with Petri Nets

“…This motivates us to evaluate and examine the performance of the honeypot in a quantitative way. In this paper, we propose to use Stochastic Petri Nets (SPN) [5,6] to model and analyze three network scenarios: the one protected by a firewall, the one protected by both a firewall and IDS [7] and the one deployed with a firewall, IDS and honeynet. Then, we evaluate the performance of the honeypot based on the three corresponding SPN models.…”