Abstract
The Prisoner Transportation Problem is an NP-hard combinatorial problem and a complex variant of the Dial-a- Ride Problem. Given a set of requests for pick-up and delivery and a homogeneous fleet, it consists of assigning requests to vehicles to serve all requests, respecting the problem constraints such as route duration, capacity, ride time, time windows, multi-compartment assignment of conflicting prisoners and simultaneous services in order to optimize a given objective function. In this paper, we present anew solution framework to address this problem that leads to an efficient heuristic. A comparison with computational results from previous papers shows that the heuristic is very competitive for some classes of benchmark instances from the literature and clearly superior in the remaining cases. Finally, suggestions for future studies are presented.

Abstract
The Prisoner Transportation Problem is an NP-hard combinatorial problem and a complex variant of the Dial-a-Ride Problem. Given a set of requests for pick-up and delivery and a homogeneous fleet, it consists of assigning requests to vehicles to serve all requests, respecting the problem constraints such as route duration, capacity, ride time, time windows, multi-compartment assignment of conflicting prisoners and simultaneous services in order to optimize a given objective function. In this paper, we present a new solution framework to address this problem that leads to an efficient heuristic. A comparison with computational results from previous papers shows that the heuristic is very competitive for some classes of benchmark instances from the literature and clearly superior in the remaining cases. Finally, suggestions for future studies are presented.

Abstract
This study focuses on improving the picking processes within a Picking-by-Line (PBL) warehouse through the development of a simulation model to assess different layouts and new operational rules. Utilizing a combination of Discrete Event Simulation (DES) and Agent-Based Modeling (ABS) in AnyLogic, the simulation model was validated against real-world Key Performance Indicators (KPIs) to ensure accuracy. The study identified three primary improvement opportunities. To address these opportunities, four scenarios were tested. The results showed varying impacts on productivity, with three of the four scenarios yielding improvements in picking productivity. Pilot testing confirmed the simulation model's predictions. The findings indicate that balancing travel distance reduction with congestion management is key to increasing picking productivity. This study reaffirms the value of simulation modeling in warehouse management, providing a robust framework for free-risk testing. © 2025 Elsevier B.V., All rights reserved.

Abstract
Complex systems, characterised by high interconnectedness and unpredictability, demand structured approaches to support decision-making, system integration, and operational efficiency. This study aims to develop a comprehensive understanding of these systems to facilitate the implementation of Digital Twins (DTs) in Complex Operations Environments (COEs). A Systematic Literature Review (SLR), following PRISMA methodology, is conducted and complemented by a grounded theory approach to identify, organise, and synthesise system characteristics. The result is a hierarchical conceptualisation comprising eight core categories that capture the essential dimensions of complexity, including: Process and System Interoperability, Human Relationships, Behaviour/Nature, Products and Services, Multi-processes, Performance, System Structure, and Management and Skill Requirements. This framework offers a structured foundation for designing and implementing DT-based decision support in COEs.

Abstract
Photovoltaic (PV) panels serve as a standard solution for the collection of solar energy. The flat photovoltaic solar plate design has been the most adopted by the market for its ease of installation. However, this design faces limitations due to geometric constraints and the sun's trajectory through the day. Inspiration was drawn from nature to overcome these limitations by utilizing the tridimensional hexagonal shape observed in honeycomb structures. The used approach aimed to explore a novel design that can reduce the constraints of flat PV panels while maximizing energy output. The unique 3D arrangement of the hexagonal pyramid enables the installation of mirrors inside to ease the reflection of photons and to increase energy production compared to flat panels. Furthermore, this design presents an opportunity to incorporate a water capture and heating system, thereby increasing the system's overall usage.

Abstract
Net Zero Energy Building (NZEB) is a concept that promotes the reduction of energy consumption in buildings by applying energy efficiency measures. The energy supply for the remaining demand should only come from sources with low CO2 emissions. Despite abundant research on NZEB for new buildings, only a small number of studies address its application to those already existing. This study aims to bridge this research gap by organizing the proposed methods to transform existing buildings into NZEB. The research method is a systematic literature review covering the methodological development and the application of the concept. We conducted a bibliometric and Scientometric analysis of 117 articles and a content analysis of 48 of them. The results highlighted that the methods identified follow similar stages: (i) planning, (ii) data collection, (iii) pre-design, (iv) design, and (v) delivery. The sub-stage with the highest frequency (88%) was the presentation of the efficiency measure package, making it an essential step in the transformation process. The review did not find specific topics, such as equipment listing and performance, occupant engagement, and charrette design. Finally, the study established guidelines for future research.