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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

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Developing a fuzzy bi-objective programming and MCDM model for bridge maintenance strategy optimization.

Fereydoon Shojaei¹, Heidar Dashti Naserabadi², Mohammad Javad Taheri Amiri³

¹Department of Civil Engineering, Islamic Azad University, Qeshm Branch, Qeshm, Iran.

Scientific Reports

|June 10, 2024

Summary

This summary is machine-generated.

This study optimizes bridge maintenance in Babolsar, Iran, using a multi-objective model. Increased budgets prioritize costlier repairs for greater impact on bridge reliability and network performance.

Keywords:

Bridge maintenance cost Budget constraint Life cycle cost MOPSO Maintenance strategy Optimization model User cost

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Area of Science:

Civil Engineering
Transportation Engineering
Operations Research

Background:

Bridges are vital urban infrastructure requiring consistent maintenance.
Effective bridge maintenance ensures network functionality and minimizes user costs.
Urban bridge networks face challenges in balancing maintenance costs, user impacts, and reliability.

Purpose of the Study:

Develop a multi-objective optimization model for bridge maintenance and repair strategies.
Incorporate budget constraints, life cycle costs, user costs (traffic delays, vehicle expenses), and network reliability.
Optimize maintenance decisions for bridges in Babolsar, Iran.

Main Methods:

Formulated a multi-objective optimization model for bridge maintenance.
Employed a multi-objective particle swarm optimization algorithm for problem-solving.
Conducted sensitivity analysis on budget levels and cost parameters (hourly costs, time value of vehicles).

Main Results:

The optimization model effectively balances competing objectives under budget constraints.
Increased budget levels led to a higher number of more expensive repairs.
Costlier maintenance interventions showed a more significant positive impact on overall bridge performance and network reliability.

Conclusions:

The developed model provides a robust framework for strategic bridge maintenance planning.
Budget allocation significantly influences the selection of maintenance strategies, favoring high-impact repairs.
Optimized maintenance planning is crucial for ensuring the long-term reliability and cost-effectiveness of urban bridge networks.