Scholarlink

<p>The study proposes a novel hybrid multi-objective optimization model to enhance efficiency and sustainability in bridge construction projects. By synergistically integrating Multi-Objective Ant Colony Optimization (MOACO) with NSGA-III, the framework simultaneously optimizes four critical dimensions: project time, cost, construction quality, and carbon emissions. Addressing the construction industry’s growing demand for environmentally responsible yet economically viable solutions, the model offers a transparent, data-driven decision-support mechanism capable of delivering unbiased and high-performance outcomes. The framework evaluates alternative construction strategies characterized by varying allocations of resources, schedules, quality targets, and environmental footprints. Through the global diversity preservation of NSGA-III and the strong local search capability of MOACO, decision-makers can effectively minimize time, cost, and emissions while maximizing construction quality. The robustness and practical relevance of the proposed model were validated using a real-world case study of a 300-meter bridge project. Comparative evaluation against established benchmarking algorithms, including MOTLBO and MOPSO, demonstrated superior or competitive performance across all objectives. Further correlation and trade-off analyses confirmed the model’s capability to generate realistic, implementable, and well-balanced solutions. Overall, the proposed hybrid optimization framework provides project managers with objective, evidence-based insights, establishing a new benchmark for smart, sustainable, and performance-oriented infrastructure development.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Hybrid NSGA-III–MOACO multi-objective optimization framework for advancing time, cost, quality, and carbon performance in bridge construction projects

  • 期刊论文

  • 发表日期：

    2026年2月3日

查看全文
  • Ippili Saikrishnamacharyulu,
  • G. Prasanna Kumar,
  • Santoshinee Mohapatra,
  • Soumyaprakash Sahoo,
  • Debendra Maharana,
  • Abu Rashid

摘要

The study proposes a novel hybrid multi-objective optimization model to enhance efficiency and sustainability in bridge construction projects. By synergistically integrating Multi-Objective Ant Colony Optimization (MOACO) with NSGA-III, the framework simultaneously optimizes four critical dimensions: project time, cost, construction quality, and carbon emissions. Addressing the construction industry’s growing demand for environmentally responsible yet economically viable solutions, the model offers a transparent, data-driven decision-support mechanism capable of delivering unbiased and high-performance outcomes. The framework evaluates alternative construction strategies characterized by varying allocations of resources, schedules, quality targets, and environmental footprints. Through the global diversity preservation of NSGA-III and the strong local search capability of MOACO, decision-makers can effectively minimize time, cost, and emissions while maximizing construction quality. The robustness and practical relevance of the proposed model were validated using a real-world case study of a 300-meter bridge project. Comparative evaluation against established benchmarking algorithms, including MOTLBO and MOPSO, demonstrated superior or competitive performance across all objectives. Further correlation and trade-off analyses confirmed the model’s capability to generate realistic, implementable, and well-balanced solutions. Overall, the proposed hybrid optimization framework provides project managers with objective, evidence-based insights, establishing a new benchmark for smart, sustainable, and performance-oriented infrastructure development.