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<p>Sustainable construction project management requires balancing competing objectives such as time, cost, and environmental impact under inherent uncertainties. This study proposes a novel fuzzy unified non-dominated sorting genetic algorithm III (Fuzzy U-NSGA-III) to optimize multi-mode project scheduling by addressing the time–cost–environmental impact (TCE) trade-offs. The model integrates fuzzy logic to handle uncertainty in activity durations, costs, and emissions using triangular fuzzy numbers (TFNs), enabling realistic representation of project variability. A mathematical framework is developed for defuzzification and integration into the multi-objective optimization model. The proposed Fuzzy U-NSGA-III is applied to a real-life construction project comprising 21 activities, each with five execution modes, to generate a diverse set of Pareto-optimal solutions. Performance is evaluated through visual trade-off plots, correlation analysis, and comprehensive benchmarking against existing multi-objective algorithms, including MOACO, MOTLBO, MODE, NSGA-III, and Fuzzy-MOPSO. Results show that the proposed method outperforms alternatives in convergence, diversity, and efficiency, achieving superior Hypervolume (HV), spacing (Sp), and non-uniformity of Pareto fronts (NPF), with significantly lower computational time. The model demonstrates strong adaptability, scalability, and practical utility for sustainable decision-making in complex construction environments, offering project managers a robust tool for optimizing conflicting project objectives under uncertainty.</p>

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Fuzzy U-NSGA-III based optimization of time–cost–environmental impact trade-offs in multi-mode sustainable construction project scheduling

  • 期刊论文

  • 发表日期：

    2025年11月25日

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  • Chayan Gupta,
  • Subash Kumar Bhattarai,
  • Ashwin Parihar,
  • Nageswara Rao Lakkimsetty,
  • Swapnil S. Ninawe,
  • B. Soujanya

摘要

Sustainable construction project management requires balancing competing objectives such as time, cost, and environmental impact under inherent uncertainties. This study proposes a novel fuzzy unified non-dominated sorting genetic algorithm III (Fuzzy U-NSGA-III) to optimize multi-mode project scheduling by addressing the time–cost–environmental impact (TCE) trade-offs. The model integrates fuzzy logic to handle uncertainty in activity durations, costs, and emissions using triangular fuzzy numbers (TFNs), enabling realistic representation of project variability. A mathematical framework is developed for defuzzification and integration into the multi-objective optimization model. The proposed Fuzzy U-NSGA-III is applied to a real-life construction project comprising 21 activities, each with five execution modes, to generate a diverse set of Pareto-optimal solutions. Performance is evaluated through visual trade-off plots, correlation analysis, and comprehensive benchmarking against existing multi-objective algorithms, including MOACO, MOTLBO, MODE, NSGA-III, and Fuzzy-MOPSO. Results show that the proposed method outperforms alternatives in convergence, diversity, and efficiency, achieving superior Hypervolume (HV), spacing (Sp), and non-uniformity of Pareto fronts (NPF), with significantly lower computational time. The model demonstrates strong adaptability, scalability, and practical utility for sustainable decision-making in complex construction environments, offering project managers a robust tool for optimizing conflicting project objectives under uncertainty.