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The ongoing issues in global supply chain disruptions have raised many concerns of port productivity, among which port congestion is a key issue. This article implements an integrated tactical–operational optimization framework which raises the capabilities of port information systems to deliver smarter decision-making processes in ports through a decision support system. To this end, we developed a library of multiple smart models for the optimization of port operations, independently engaged in parallel but mathematically coordinated to achieve autonomous real-time distributed optimization, using a novel event-driven structure to enable future implementations using digital twins. The framework was tested to benchmark different commercial solvers on several real instances for the port under study. The results show a strong improvement in port operational planning. [ABSTRACT FROM AUTHOR]

In this study, we introduce an advanced system for sustainable pavement management that leverages cutting-edge machine learning and computer vision techniques to detect and classify pavement damage. By utilizing models such as EfficientNetB3, ResNet18, and ResNet50, we develop robust classifiers capable of accurately identifying various types of pavement distress. To further enhance our dataset, we employ a Swin Transformer-based Generative Adversarial Network (GAN) to synthetically generate images of pavement cracks, thereby augmenting the training data. Our approach aims to improve the efficiency and accuracy of pavement damage assessment, contributing to more effective and sustainable road maintenance practices. This research aligns with the sustainable development goals by fostering innovative methods that extend the lifespan of infrastructure, reducing the need for resource-intensive repairs, and promoting the longevity and reliability of road networks. The outcomes of this study are discussed in terms of their potential impact on infrastructure safety and sustainability, with suggestions for future research directions. This study demonstrates how integrating advanced machine learning techniques into pavement management systems can enhance decision-making, optimize resource allocation, and improve the sustainability of infrastructure maintenance practices. By leveraging big data and sophisticated algorithms, stakeholders can proactively address pavement deterioration, extend asset lifespan, and optimize maintenance efforts based on real-time data-driven insights. [ABSTRACT FROM AUTHOR]

Freight transportation can be defined as the movement of goods and services to customers to obtain a monetary reward. Poor quality transport infrastructure implies higher travelling times and costs. This indirectly affects the productivity of a region since transportation costs are directly related to sales prices. Therefore, infrastructure investments become important for improving the competitiveness of a region. The problem with these investments is that they take time and require a large amount of money. Consequently, it is extremely important to prioritise this type of investment. This paper will first explain whether transportation investment or a sustainable transportation method affect the exported freight accessibility and if it also affects regional productivity using a linear regression model with the aid of a data-driven geographical information system. It uses spatial separation, gravity, and cumulative opportunity measures to calculate accessibility. Finally, the paper denotes which regions are highly affected by improvements in road, river, and railway networks using Colombia as a case study. The comparison considers travelling time and costs savings under each scenario. The results indicate that the gravity measure was the most appropriate accessibility measure for analysing the Gross Domestic Product (GDP). The scenario analyses suggest that zones farthest from the seaports are more sensitive to accessibility changes; consequently, they will receive higher improvements in their regional GDP with a national-level implementation of transport infrastructure investments. Thus, project prioritisation should be performed in regions where the investments lead to a decreased travel cost between regions and ports., Author(s): Maria Jubiz-Diaz (corresponding author) [1]; Maria Saltarin-Molino [2]; Julian Arellana [3]; Carlos Paternina-Arboleda [1,4]; Ruben Yie-Pinedo [1] 1. Introduction Transportation plays an important role in a country's economy and [...]

Humanitarian logistics encompasses a wide spectrum of conditions or constraints for supply chains, yet its focus on mitigating human suffering efficiently is what has motivated organizations and governments to make rapid decisions in real time. In this article, through the approach to an emergency such as COVID-19, we propose a two-stage model capable of considering human suffering, the cost of humanitarian logistics, and the benefit obtained by the interaction of suppliers that generally behave as oligopolies through a mathematical programming model and one of the cooperative games. Our main finding was the adaptability of a previously validated model for humanitarian logistics to the ongoing COVID-19 pandemic, where the externalities had greater relevance in social costs than private costs., Author(s): Oscar L. Pineda-Martinez (corresponding author) [1]; Carlos D. Paternina-Arboleda [1]; Guisselle A. García-Llinás [1] 1. Introduction In terms of attention to the occurrence of disasters or emergency situations similar [...]

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This paper presents an information-technology-based collaboration framework that facilitates disaster response operations. The collaboration framework incorporates a web collaboration service, radio frequency identification (RFID) tags, a building blackbox system (BBS), a geo-database, and a geographic information system (GIS). Through the integration of these technologies, the framework provides a collaboration medium for first responders, including civil engineers, to cohesively respond to disasters. Access to critical building information, such as construction documents, through the BBS supports assessments of building integrity during disaster response. Building assessment information is stored on RFID tags, which are accessible to first responders through digital devices via a wireless ad hoc network. With on-site assessment information shown on a digital map, decision makers locate, collect, and distribute critical resources through the GIS to first responders. In addition, the decision makers at distributed locations evaluate the incident through discussion sessions, hosted by the web collaboration environment, for integrated decision making. Test-bed simulations for the framework have been carried out with encouraging results at the training ground of the Illinois Fire Service Institute. DOI: 10.1061/(ASCE)CP. 1943-5487.0000033 CE Database subject headings: Disasters; Emergency services; Damage; Assessment; Information systems; Information management; Geographic information systems; Computer networks. Author keywords: Disasters; Emergency services; Damage assessment; Information systems; Information management; Ad hoc networks; Geographic information systems.

The ability to effectively communicate progress information and represent as-built and as-planned progress discrepancies are identified as key components for successful project management that allow corrective decisions to be made in a timely manner. However, current formats of reporting (e.g., textual progress reports, progress curves, and photographs) may not properly and quickly communicate project progress. Current monitoring methods also require manual data collection and extensive data extraction from different construction documents, which distract managers from the important task of decision making. Therefore, to facilitate progress monitoring, this paper proposes visualization of performance metrics that aims to represent progress deviations through superimposition of four-dimensional (4D) as-planned model over time-lapsed photographs in single and comprehensive visual imagery. As a part of the developed system, registration of the 4D model with photographs, augmenting photographs, and occlusion removal for progress images are presented. While contextual information is preserved, the as-built photographs are enhanced and augmented with 4D as-planned model in which the performance metrics are visualized. The augmented photographs provide a consistent platform for representing as- planned, as-built, and progress discrepancies information and facilitate communication and reporting processes. DOI: 10.1061/(ASCE)0887-3801(2009)23:6(391) CE Database subject headings: Monitoring; Imaging techniques; Computer aided simulation; Information technology (IT); Construction management; Registration.