Abstract
The rapid advancement of warehouse automation has increased the need for intelligent intralogistics solutions that enhance material handling efficiency and optimize space utilization. This research presents a simulation-based methodology that integrates Autonomous Mobile Robots (AMRs) with container loading optimization in a unified decision-support framework that dynamically synchronizes AMR routing with optimized truckload configurations, a feature not commonly addressed jointly in existing literature to improve warehouse operations. By leveraging a hybrid approach combining discrete event and agent-based simulation in FlexSim, the study evaluates the impact of AMR fleet size, routing strategies, and truckload configurations on overall logistics performance. A proof-of-concept industrial case study illustrates how different scenarios influence key performance metrics, such as total operation time and resource utilization. The findings demonstrate that synchronized AMR deployment and optimized container loading strategies contribute to increased throughput, reduced handling time, and enhanced logistics unit utilization. This work provides a framework for dynamic logistics planning, offering valuable insights for companies seeking to enhance warehouse efficiency and sustainability through simulation-driven decision support. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

Abstract
The adoption of Autonomous Mobile Robots (AMRs) has emerged as a promising solution to enhance efficiency and reduce operational costs for industrial companies. Given the significant cost of AMRs, it is crucial to determine the optimal number and characteristics before making significant investments. This study proposes a decision-support framework based on simulation to assess the impact of integrating AMR robots in a complex distribution center. Additionally, this framework aids decision-makers in determining the optimal fleet size of AMR robots and corresponding charging stations. A simulation model was developed using data from a leading retail company, focusing on pallet movement within the facility, comparing scenarios combining AMRs with other intralogistics implementations. This methodology incorporates uncertainty, variability (statistical distributions to create transportation orders, acceleration, demand and offer fluctuations) and implements fleet management, transportation capacity, demand matching, and resource utilization according to real case scenarios. The proposed model replicates accurate robot coordination and actual deployment environments, ensuring that the tested scenarios approximate the real-world conditions as much as possible. Preliminary findings show results supporting the decision-making for a fleet size to meet weekly production targets, optimize robot utilization, and coordinate charging instances to prevent production stops. Conclusions suggest that the proposed simulation approach is an effective tool for planning and implementing logistics solutions, enabling users to make informed decisions before investing.

Abstract
The world faces unprecedented challenges related to the so-called Triple Planetary Crisis (climate changes, massive pollution, biodiversity losses). The Linear Economy model of development represents a very relevant cause for these crises effects, since it is anchored on the paradox of ever-growing natural resources extraction within a finite planet space and limited policy barriers for ecosystems degradation. Circular Economy emerges as a promising alternative development model, but it still urges for effective implementation. This work presents a novel De-Production model that combines, by design or redesign, the articulation of R-Strategies and D-Strategies across the product and production life cycles in order to unblock circular business models. It is proposed a systemic approach considering product circularity by means of activating R-Strategies, improving both production operations and de-production operations via value retention mindset. The model is tested via discrete simulation in a remanufacturing case study of a bicycle wheel assembly. © 2025 Elsevier B.V., All rights reserved.

Abstract
Digital Twins are becoming an architectural and functional element in a variety of systems managing physical assets. From complex products to the interconnection of assets in complex processes, digital twins are becoming the overarching cognitive concept that operators interact with to design, manage, control and maintain those products and processes. Despite this evolution, there is still limited knowledge on how to design the human interaction and user experience with digital twin-based systems. In this paper, we review the scarce literature on this subject and identify the high-level requirements for designing user experience for both product and process digital twin-based systems. Finally, we instantiate the requirements for a product-process digital twin-based system, with the focus on circularity and sustainability. © 2025 IEEE.

Abstract
Container terminals are of pivotal importance to global trade, as they act as a bridge between maritime and land transport. However, inefficiencies in operations, such as long waiting times and high emissions, continue to challenge the industry. Current practices, including first-come-first-served (FCFS) berth allocation, often result in ships arriving too early and idling at anchorage, leading to increased fuel consumption and negative environmental impacts. Just-in-Time (JIT) strategies have been identified as a potentially effective approach to address these issues by aligning ship arrivals with berth availability, thus optimising speed and reducing emissions. In this work, we present a simulation-based decision-support tool to evaluate JIT strategies in container terminal operations. By analysing scenarios involving speed optimisation and resource investments, the tool provides insights into key performance metrics, including waiting times, emissions, and resource utilisation. A case study designed around a large Portuguese seaport was used to validate the approach, with significant reductions in emissions and operational inefficiencies. These findings highlight the potential of JIT operations to enhance sustainability and efficiency in the maritime sector. Copyright © 2025. Published by Elsevier B.V.