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<p>Efficient construction schedule optimization is crucial yet challenging due to resource constraints and dynamic conditions. This study proposes a hybrid method combining NSGA-III and the Improved Arithmetic Optimization Algorithm (IAOA) to enhance solution quality and convergence speed. IAOA refines the original AOA by enhancing both exploration and exploitation phases, thereby mitigating the risk of local optima and broadening the search space. These refinements bolster NSGA-III’s effectiveness in addressing intricate optimization challenges. To demonstrate its practical applicability, a case study focused on concrete construction scheduling was conducted, illustrating the method’s ability to balance key factors such as project duration, cost, and resource allocation. This proposed framework offers a scalable solution for construction professionals and contributes to the advancement of multi-objective optimization techniques in dynamic scheduling environments.</p>

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A Hybrid NSGA-III and improved arithmetic optimization algorithm (IAOA) approach for time, cost, and resource allocation

  • 期刊论文

  • 发表日期：

    2025年6月23日

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  • Vu Hong Son Pham,
  • Ngoc Thao Phuong Hoang,
  • Duc Anh Tuan Le

摘要

Efficient construction schedule optimization is crucial yet challenging due to resource constraints and dynamic conditions. This study proposes a hybrid method combining NSGA-III and the Improved Arithmetic Optimization Algorithm (IAOA) to enhance solution quality and convergence speed. IAOA refines the original AOA by enhancing both exploration and exploitation phases, thereby mitigating the risk of local optima and broadening the search space. These refinements bolster NSGA-III’s effectiveness in addressing intricate optimization challenges. To demonstrate its practical applicability, a case study focused on concrete construction scheduling was conducted, illustrating the method’s ability to balance key factors such as project duration, cost, and resource allocation. This proposed framework offers a scalable solution for construction professionals and contributes to the advancement of multi-objective optimization techniques in dynamic scheduling environments.