The use of intelligent search algorithms in the cost optimization of road pavement thickness design
Since road pavements consume a significant portion of the financial resources of construction costs, design engineers aim to find an appropriate pavement thickness design with minimum possible cost. The optimal design can be located using intelligent search algorithms. This study compares the perfor...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-05-01
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| Series: | Ain Shams Engineering Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2090447921003610 |
| _version_ | 1811294163062226944 |
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| author | Mansour Tohidi Navid Khayat Abdoulrasoul Telvari |
| author_facet | Mansour Tohidi Navid Khayat Abdoulrasoul Telvari |
| author_sort | Mansour Tohidi |
| collection | DOAJ |
| description | Since road pavements consume a significant portion of the financial resources of construction costs, design engineers aim to find an appropriate pavement thickness design with minimum possible cost. The optimal design can be located using intelligent search algorithms. This study compares the performance of genetic algorithm and particle swarm optimization to determine the efficacy of intelligent algorithms in determining the economically optimal pavement thickness design. The software required to implement the two algorithms for solving the pavement design and the simulation–optimization model were developed. Then, nine completed projects in Khuzestan, in Southwestern Iran, were evaluated using the manual design approach of consulting engineers, and the projects’ capabilities were compared by applying the programs developed for the two algorithms to the projects. The results indicated using GA and PSO reduced design costs by 9–26.5% and 5–25%, respectively compared to the manual design, and GA outperforms PSO by 1–5.5% regarding cost savings. |
| first_indexed | 2024-04-13T05:12:24Z |
| format | Article |
| id | doaj.art-f5efc9307e3d4a72a4ce32a3b4e6b9ce |
| institution | Directory Open Access Journal |
| issn | 2090-4479 |
| language | English |
| last_indexed | 2024-04-13T05:12:24Z |
| publishDate | 2022-05-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ain Shams Engineering Journal |
| spelling | doaj.art-f5efc9307e3d4a72a4ce32a3b4e6b9ce2022-12-22T03:00:59ZengElsevierAin Shams Engineering Journal2090-44792022-05-01133101596The use of intelligent search algorithms in the cost optimization of road pavement thickness designMansour Tohidi0Navid Khayat1Abdoulrasoul Telvari2Department of Civil Engineering, Ahvaz Branch, Islamic Azad University, Ahvaz, IranCorresponding author.; Department of Civil Engineering, Ahvaz Branch, Islamic Azad University, Ahvaz, IranDepartment of Civil Engineering, Ahvaz Branch, Islamic Azad University, Ahvaz, IranSince road pavements consume a significant portion of the financial resources of construction costs, design engineers aim to find an appropriate pavement thickness design with minimum possible cost. The optimal design can be located using intelligent search algorithms. This study compares the performance of genetic algorithm and particle swarm optimization to determine the efficacy of intelligent algorithms in determining the economically optimal pavement thickness design. The software required to implement the two algorithms for solving the pavement design and the simulation–optimization model were developed. Then, nine completed projects in Khuzestan, in Southwestern Iran, were evaluated using the manual design approach of consulting engineers, and the projects’ capabilities were compared by applying the programs developed for the two algorithms to the projects. The results indicated using GA and PSO reduced design costs by 9–26.5% and 5–25%, respectively compared to the manual design, and GA outperforms PSO by 1–5.5% regarding cost savings.http://www.sciencedirect.com/science/article/pii/S2090447921003610Asphalt PavementOptimal Pavement DesignIHAP Design MethodGenetic Algorithm (GA)Particle Swarm Optimization (PSO) |
| spellingShingle | Mansour Tohidi Navid Khayat Abdoulrasoul Telvari The use of intelligent search algorithms in the cost optimization of road pavement thickness design Ain Shams Engineering Journal Asphalt Pavement Optimal Pavement Design IHAP Design Method Genetic Algorithm (GA) Particle Swarm Optimization (PSO) |
| title | The use of intelligent search algorithms in the cost optimization of road pavement thickness design |
| title_full | The use of intelligent search algorithms in the cost optimization of road pavement thickness design |
| title_fullStr | The use of intelligent search algorithms in the cost optimization of road pavement thickness design |
| title_full_unstemmed | The use of intelligent search algorithms in the cost optimization of road pavement thickness design |
| title_short | The use of intelligent search algorithms in the cost optimization of road pavement thickness design |
| title_sort | use of intelligent search algorithms in the cost optimization of road pavement thickness design |
| topic | Asphalt Pavement Optimal Pavement Design IHAP Design Method Genetic Algorithm (GA) Particle Swarm Optimization (PSO) |
| url | http://www.sciencedirect.com/science/article/pii/S2090447921003610 |
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