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<p>Bridge construction projects are inherently complex, involving numerous interdependent activities, sustainability concerns, and risk factors. Traditional optimization methods in construction primarily focus on minimizing time and cost, often overlooking energy consumption and risk mitigation. To address this gap, this study proposes a novel multi-objective (MOTLBO) framework for discrete time–cost-energy-risk optimization in bridge construction projects under the integrated project delivery (IPD) approach. The framework aims to simultaneously minimize project duration, total cost, energy consumption, and construction risk by evaluating multiple execution modes for each activity in a reinforced concrete girder bridge project. A real-world case study is used to generate Pareto-optimal solutions, offering a diverse set of trade-offs for informed decision-making. The proposed model demonstrates superior performance compared to established algorithms (NSGA-II, NSGA-III, MOACO, and MOPSO) in terms of hypervolume (HV), inverted generational distance (IGD), and spacing metrics (Sp). Further validation using R<sup>2</sup> metrics confirms the model’s accuracy across all four objectives. A weighted sum method (WSM) is employed to select the most balanced solution, and correlation analysis reveals significant interdependencies among objectives. The study offers a robust and computationally efficient decision-support tool for enhancing sustainability, cost-effectiveness, and risk management in large-scale infrastructure projects.</p>

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Discrete time–cost-energy-risk optimization in bridge construction projects under integrated project delivery using multi-objective teaching–learning-based optimization

  • 期刊论文

  • 发表日期：

    2025年5月13日

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  • Abhishek Shrivastava,
  • Shobhana Singh

摘要

Bridge construction projects are inherently complex, involving numerous interdependent activities, sustainability concerns, and risk factors. Traditional optimization methods in construction primarily focus on minimizing time and cost, often overlooking energy consumption and risk mitigation. To address this gap, this study proposes a novel multi-objective (MOTLBO) framework for discrete time–cost-energy-risk optimization in bridge construction projects under the integrated project delivery (IPD) approach. The framework aims to simultaneously minimize project duration, total cost, energy consumption, and construction risk by evaluating multiple execution modes for each activity in a reinforced concrete girder bridge project. A real-world case study is used to generate Pareto-optimal solutions, offering a diverse set of trade-offs for informed decision-making. The proposed model demonstrates superior performance compared to established algorithms (NSGA-II, NSGA-III, MOACO, and MOPSO) in terms of hypervolume (HV), inverted generational distance (IGD), and spacing metrics (Sp). Further validation using R2 metrics confirms the model’s accuracy across all four objectives. A weighted sum method (WSM) is employed to select the most balanced solution, and correlation analysis reveals significant interdependencies among objectives. The study offers a robust and computationally efficient decision-support tool for enhancing sustainability, cost-effectiveness, and risk management in large-scale infrastructure projects.