Background: In today’s complex and rapidly changing global markets, supply chain resilience (SCR) has become critical for businesses aiming to maintain continuity and competitive advantage. Disruptions and challenges in the supply chain will always exist; therefore, preparing in advance and improving resilience for the upcoming consequences should be the utmost important goal. Methods: Digital twins (DTs) provide a comprehensive view of product performance, enabling companies to adopt an end-to-end approach to product management. To maximize product and service value, supply chains must also be managed holistically. Results: Therefore, companies will need smarter strategies to balance inventory costs, availability and lead times. The optimal setup of suppliers, manufacturing, logistics and stock locations will ensure high service levels and meet customer expectations. Additionally, supply chains must be resilient, and capable of maintaining performance during disruptions and adapting to demand changes. Conclusions: This paper aims to provide a comprehensive review of the state of the art in digital twin applications within supply chains, focusing on their role in improving visibility, agility and decision-making. This paper explores how digital twins might integrate with emerging technologies such as IoT, AI and blockchain, fostering a more adaptive and robust supply chain ecosystem.

For logistic chains that have a maritime component, the ports transition involves a set of specific operations inside maritime container terminals. This can be cargo handling operations from the terrestrial vehicle in the storage area of ports, from port storage area in the maritime ships, as well as storage operations in the port area and other container terminal activities. Taking into consideration the multi-flow interactions and the non-uniform arrival of vessels and inland vehicles, discrete event simulation stands as a feasible technique for investigating berthing capacity during the initial planning stage of the terminal or for operative planning of logistic processes at the terminal. If the storage area is analysed as a queuing system, the quality serving attributes could be evaluate. When different distributions for arrival flows of the containers in the maritime container terminal are taken into consideration, the quality serving attributes are difficult to estimate. In our paper, a discrete simulation model is developed in ARENA software for case of a maritime container terminal. The estimation of the general measures of performance for the container port terminals through simulation could provide data for the implementation in the management plans by port administrations.

This paper introduces a simulation model designed as a decision-making tool to assess and analyze various crowd management strategies with a focus on enhancing sustainability in airport operations. This model specifically addresses the challenges and risks associated with managing passenger flows within airport terminals. By simulating different scenarios, the model aims to provide valuable insights into how to effectively handle crowd dynamics and enhance overall terminal efficiency, safety, and sustainability. This case study was conducted at Henri Coanda International Airport, ARENA 12 simulation software being used in order to model the passenger flows within the airport terminal. Two scenarios were considered: The first one involves maintaining a fixed number of security and check-in desks for the two airline groups. In contrast, the second scenario allows for a variable number of security and check-in desks for the same airline groups. By optimizing resource allocation and minimizing waiting time, this model contributes to more sustainable airport management operations. Three measures of performance (MOPs) were selected to assess the system activity: the average passenger waiting time, the average passenger number queue length, and the average utilization rate. Comparing the results, we concluded that the second scenario shows a relative improvement in almost all performance measures when compared to the first scenario.

Background: The habitat structure, the environmental impact, the market acceptance, the changes in consumers’ preferences, and the pandemic urged for innovative solutions in urban last-mile delivery. Parcel lockers are among the most preferred solutions by customers due to their home proximity, time availability, and cost efficiency. Methods: This paper introduces an agent-based model (ABM) and a Monte Carlo simulation program to analyze in detail the activity of parcel locker points. The ABM describes the behavior of the agents (customers, parcels, lockers, delivery agents). The simulation is realized using ARENA 12 software. Two scenarios are created based on the number of daily delivery shifts; for each scenario, 300 simulation experiments with various input data are conducted. Results: Three measures of performance (MOPs) are selected to assess the system activity: the number of daily delivered parcels, the delivery time of an order, and the daily delayed orders. The simulation outputs reveal significant predictors of MOPs and disclose moments when actions need to be taken to increase system capacity or change customer behavior. Conclusions: The versatility of the simulation model in terms of input variables makes it a useful decision support tool for planning by highlighting quantitative assessments, organizing delivery activity, along with influences due to customer behavior changes.

One of the most frustrating problems when dealing with risks it’s that they come in so many different forms. They can appear at any point in a port logistic system, they can interrupt the supply of raw materials or products, they can cause demand fluctuations (peak or collapse), inventory problems (lack or crowding), dispatch delay. Risks can range on a scale from small delay to a natural disaster, from short term to a permanent damage, with effects localized on a part of a supply chain or affecting the whole chain activity. The risk management allows port administration to take appropriate measures to reduce the consequences of a risk, to provide a good reliability of the logistic system or to design a resilient one. The paper investigates the major risks in port logistics and adequate measures to minimizing their effects. A risk management tree is set-up. Using computer simulation modelling, a case study investigates the port logistic system behaviour under different risk scenarios and evaluates the reliability of the system and its resilience. The operation capacity for different port logistics sub-system is assessed taking into consideration the required operating standards and the measures of performance (e.g. waiting time for vessels and transport vehicles, storage area and time for commodities) of the logistic system are computed.

Sea ports are important nodes in the supply chain, joining two high capacity transport modes: rail and maritime transport. The huge cargo flows transiting port requires high capacity construction and installation such as berths, large capacity cranes, respectively shunting yards. However, the port shunting yards specificity raises several problems such as: limited access since these are terminus stations for rail network, the in-output of large transit flows of cargo relatively to the scarcity of the departure/arrival of a ship, as well as limited land availability for implementing solutions to serve these flows. It is necessary to identify technological solutions that lead to an answer to these problems. The paper proposed a simulation model developed with ARENA computer simulation software suitable for shunting yards which serve sea ports with access to the rail network. Are investigates the principal aspects of shunting yards and adequate measures to increase their transit capacity. The operation capacity for shunting yards subsystem is assessed taking in consideration the required operating standards and the measure of performance (e.g. waiting time for freight wagons, number of railway line in station, storage area, etc.) of the railway station are computed. The conclusion and results, drawn from simulation, help transports and logistics specialists to test the proposals for improving the port management.