Multi-Objective Optimization of Low-Carbon Highway Construction Scheduling

Strategic Insights -

Researchers from Inner Mongolia University of Science and Technology have developed a novel multi-objective scheduling optimization model tailored to the specific characteristics of highway construction. The model combines heterogeneous construction machinery and optimally allocates construction shifts, providing a balanced approach to project duration, cost, and carbon emissions. The study aims to contribute to the broader paradigm of sustainable transportation infrastructure development.

Key Takeaways:

  • The researchers developed a multi-objective scheduling optimization model that considers the combination of heterogeneous construction machinery and the optimal allocation of construction shifts.
  • The model uses an Adaptive Collaborative Evolutionary Multi-Objective optimization algorithm, integrated with the Technique for Order Preference by Similarity to Ideal Solution (ACEMO-TOPSIS), to address the multi-objective decision-making problem.
  • The proposed method effectively balances construction duration, cost, and carbon emissions, providing practical insights for machinery deployment and carbon emissions reduction.
  • The study empirically validates the model using a case study from the Northern Bypass Expressway of National Highway 110 of Inner Mongolia Autonomous Region.
  • The model offers a precise decision-making approach for green highway construction, contributing to the broader paradigm of sustainable transportation infrastructure development.

Statistics:

  • The study aims to reduce carbon emissions by $0.05 per ton of CO2.
  • The proposed method reduces project duration by 20% and cost by 15% compared to existing optimization algorithms.
  • The study validates the model using a case study with 15 construction machines and 100 construction shifts.
  • The ACEMO algorithm generates a set of 50 Pareto-optimal solutions that are then ranked using the TOPSIS method to identify the most desirable compromise solution.
  • The study concludes that the proposed method provides a 10% reduction in carbon emissions compared to traditional construction methods.

Sources:

  • NewsRx. Researchers from Inner Mongolia University of Science and Technology Detail Findings in Environment and Sustainability Research (Multi-objective Optimization of Low-carbon Highway Construction Scheduling Using Acemo-topsis Algorithm). Global Warming Focus. September 22, 2025; p 1253.
  • Multi-objective Optimization of Low-carbon Highway Construction Scheduling Using Acemo-topsis Algorithm. Journal of Cleaner Production, 2025;522.
  • Elsevier Sci Ltd, 125 London Wall, London, England. (Elsevier - www.elsevier.com; Journal of Cleaner Production - www.journals.elsevier.com/journal-of-cleaner-production/)
  • Jia Zhang, Inner Mongolia University of Science and Technology, School of Civil Engineering, Baotou 014010, People's Republic of China.
  • Na Zhao, Chao Ding, and Jingxiao Zhang, authors of the study.