Optimizing sustainability in infrastructure projects: a framework integrating time, economic, social and environmental perspectives

Purpose This study aims to present a significant advancement in the optimization of sustainable infrastructure projects (IPs) by introducing a multiobjective framework that integrates traditional metrics of time and cost with social and environmental impacts. This paper focuses on choosing the best alternatives to complete the project with the least time, cost, environmental and social impact. Design/methodology/approach The proposed decision-support framework is structured into three submodels: a duration and cost submodel, an environmental impact submodel and a social impact submodel. Each submodel quantifies one dimension of project sustainability. Nondominated sorting genetic algorithm-II is used to generate Pareto-optimal solutions that balance project time, cost, environmental impacts and social costs. To support decision-making among these optimal solutions, Shannon entropy is applied to objectively calculate the weights of each objective based on their variability, and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is used to rank and select the best alternative. The framework’s effectiveness is validated through a real-world case study involving a major IP in the new administrative capital, Egypt. Findings The model generated 500 Pareto-optimal solutions for “Link 2 Road” project, revealing key trade-offs between sustainability objectives. The fastest solution achieved 254 days duration with minimal social costs (LE 4,562,449), while the most environmental friendly option reduced emissions by 32% at 593 days. A balanced TOPSIS-optimized solution combined competitive metrics: 283 days (11% faster than average), LE 54,735,194 cost, high environmental performance (Infrastructure Environmental Index, IEI, of 967.9) and significantly reduced social impacts (LE 4,961,804, 45% below worst-case). These results demonstrate how the framework enables data-driven decisions across all sustainability dimensions. These results provide infrastructure managers with actionable data to: (1) quantify sustainability trade-offs during planning, (2) justify green construction investments and (3) align projects with sustainable development goals while controlling costs and schedules fundamentally changing how sustainability is operationalized in infrastructure delivery. Originality/value This study offers significant value by bridging a critical gap in construction management literature through its integrated approach to achieve sustainability. The introduction of the IEI and Infrastructure Social Cost Index provides standardized metrics for quantifying environmental and social impacts. The framework serves as a practical tool for project managers and policymakers, facilitating the selection of construction methods that align with sustainability goals while maintaining cost and schedule efficiency. By embedding environmental and social considerations into early project planning, this research promotes a proactive approach to sustainable infrastructure development, contributing to global efforts in green construction and responsible resource management.