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The construction industry significantly contributes to global resource consumption and environmental degradation, necessitating a shift toward sustainable practices. Recycling construction materials, such as concrete, steel, and glass, offers a promising solution to reduce environmental impact and conserve resources. However, optimizing recycled materials for cost-effectiveness and sustainability remains a challenge. This study applies Linear Programming (LP) to optimize the use of recycled materials in construction projects in the GCC, balancing cost reduction and environmental goals. The LP model minimizes material costs while adhering to regulatory constraints and sustainability targets. Using data from real construction projects, the model integrates constraints on material availability, CO2 reduction, and minimum recycled content. The results demonstrate that LP optimization reduces construction costs by 41.05%, from $2.04 billion to $1.20 billion.Additionally, the model achieves significant environmental benefits, reducing CO2 emissions by 62.5% for recycled concrete, 80% for recycled steel, and 70% for recycled glass compared to virgin materials. The study concludes that LP is an effective tool for optimizing material allocation in construction, ensuring cost efficiency and environmental sustainability. It recommends integrating LP models into construction planning to meet economic and regulatory requirements, advancing the GCC’s sustainability goals and enhancing green building practices.
Recycled Materials, Construction, Linear Programming, Cost-Effectiveness, Environmental Sustainability, Sustainability, Optimization, Carbon Footprint, Resource Conservation, GCC, Building Materials, Waste Reduction, Circular Economy, CO2 Emissions, Material Allocation.