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Sustainable Road Infrastructure Decision-Making: Custom NSGA-II with Repair Operators for Multi-Objective Optimization

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  • Andrés Ruiz-Vélez

    (Institute of Concrete Science and Technology (ICITECH), Universitat Politècnica de València, 46022 València, Spain)

  • José García

    (Escuela de Ingeniería de Construcción y Transporte, Pontificia Universidad Católica de Valparaíso, Valparaíso 2362804, Chile)

  • Julián Alcalá

    (Institute of Concrete Science and Technology (ICITECH), Universitat Politècnica de València, 46022 València, Spain)

  • Víctor Yepes

    (Institute of Concrete Science and Technology (ICITECH), Universitat Politècnica de València, 46022 València, Spain)

Abstract

The integration of sustainability principles into the structural design and decision-making processes for transportation infrastructure, particularly concerning reinforced concrete precast modular frames (RCPMF), is recognized as crucial for ensuring outcomes that are environmentally responsible, economically feasible, and socially beneficial. In this study, this challenge is addressed, with the significance of sustainable development in modern engineering practices being underscored. A novel approach, which is a combination of multi-objective optimization (MOO) with multi-criteria decision-making (MCDM) techniques, is proposed, tailored specifically for the design and selection of RCPMF. The effectiveness of three repair operators—statistical-based, random, and proximity-based—in optimizing economic, environmental, and social objectives is evaluated. Precise evaluation of objective functions is facilitated by a customized Non-dominated Sorting Genetic Algorithm II (NSGA-II) algorithm, complemented by a detailed life cycle analysis (LCA). The utilization of simple additive weighting (SAW) and fair un choix adéquat (FUCA) methods for the scoring and ranking of the MOO solutions has revealed that notable excellence in meeting the RCPMF design requirements is exhibited by the statistical-based repair operator, which offers solutions with lower impacts across all dimensions and demonstrates minimal variability. MCDM techniques produced similar rankings, with slight score variations and a significant correlation of 0.9816, showcasing their consistent evaluation capacity despite distinct operational methodologies.

Suggested Citation

  • Andrés Ruiz-Vélez & José García & Julián Alcalá & Víctor Yepes, 2024. "Sustainable Road Infrastructure Decision-Making: Custom NSGA-II with Repair Operators for Multi-Objective Optimization," Mathematics, MDPI, vol. 12(5), pages 1-21, February.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:5:p:730-:d:1348781
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    References listed on IDEAS

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    1. Kyriacou, Andreas P. & Muinelo-Gallo, Leonel & Roca-Sagalés, Oriol, 2019. "The efficiency of transport infrastructure investment and the role of government quality: An empirical analysis," Transport Policy, Elsevier, vol. 74(C), pages 93-102.
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