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This study explores integrating Building Information Modeling (BIM) and Value Engineering (VE) to enhance cost management and project value optimization in residential construction. The primary aim is to develop a comprehensive framework that synergizes 5th Dimension Building Information Modeling (5D BIM) with VE processes to identify and evaluate the most cost-effective construction alternatives. Employing a mixed-methods approach, this research includes an extensive review of existing practices, an integrated BIM-VE framework proposal, and the application of 5D BIM principles to improve visualization, cost estimation, and scheduling. The findings reveal that integrating BIM and VE significantly enhances project efficiency, quality, and cost-effectiveness. Specifically, the case study of a twin villa project demonstrates a 42% reduction in floor material costs and a 30% reduction in door material costs, resulting in an overall project cost savings of 35%. Additionally, the integrated approach contributes to a 15% reduction in project duration and a notable improvement in design quality and stakeholder collaboration. This research contributes significantly by providing a robust framework for BIM and VE integration, emphasizing its potential to revolutionize cost management practices in the construction industry. The novelty of this study lies in its detailed and practical approach to merging BIM with VE, offering a viable solution for resource optimization and sustainable building practices. This study highlights the transformative potential of BIM-VE integration, advocating for its broader adoption to achieve superior project outcomes.

The solid waste management (SWM) represents one of the most important challenges worldwide in the current period. Also, it contributes to large negative effect on the three aspects of sustainability which are environmental, social and economic sustainability. Approximately 50% of total annual global generated solid waste (SW) is from construction and demolition waste (CDW). The case of CDW in Egypt has become a major challenge, and Egypt encounters many challenges that obstacle the way for development of efficient SWM especially towards ensuring safe disposal of CDW. This paper aims to investigate: (1) the rising problem related to SW in Egypt showing its main causes; (2) CDW percentages in greater Cairo; (3) the unsafe disposal of CDW waste in Egypt through reviewing most recent research papers; and (4) automation in construction techniques that were previously implemented for better CDW management (CDWM). Findings and recommendations of CDWM improvement in Egypt from this study are expected to encourage research on automated construction technique towards ensuring safe disposal of CDW in Egypt which would be of great effect towards improving sustainability levels in the Egyptian construction sector.

This study identifies a critical knowledge gap, revealing how the deterioration of roads, compounded by extensive usage and additional factors, poses significant risks to the road networks’ functionality. Without a robust fund allocation and prioritization strategy, the extent of this risk may be overlooked, adversely affecting the performance of essential infrastructure elements. Our research introduces an integrated decision-making model for existing road infrastructures to address this gap. This innovative approach combines a Geographic Information System (GIS)-based road management model with a fund allocation prioritization strategy, enhanced by an optimization engine via a genetic algorithm. The primary aim is to precisely determine Maintenance and Repair (M&R) interventions tailored to the condition states, thereby improving the Pavement Condition Index (PCI) of the road segments. The research is structured around three key objectives: (1) develop a detailed GIS-based road management database incorporating inspection data and attributes of road infrastructure for proactive M&R decision-making; (2) efficiently allocate funds to maintain service delivery on deteriorated roads; and (3) pinpoint the optimal type and timing of M&R interventions to boost the condition and performance of the road segments. Anticipated results will provide asset managers with a comprehensive decision support system for executing effective M&R practices.