Optimizing Retaining Walls through Reinforcement Learning Approaches and Metaheuristic Techniques

The structural design of civil works is closely tied to empirical knowledge and the design professional’s experience. Based on this, adequate designs are generated in terms of strength, operability, and durability. However, such designs can be optimized to reduce conditions associated with the struc...

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Bibliographic Details
Published inMathematics (Basel) Vol. 11; no. 9; p. 2104
Main Authors Lemus-Romani, José, Ossandón, Diego, Sepúlveda, Rocío, Carrasco-Astudillo, Nicolás, Yepes, Victor, García, José
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 28.04.2023
Subjects
Analysis
Carbon
Carbon dioxide
Concrete
concrete retaining walls
Construction industry
Design
Emission standards
Emissions
Heuristic methods
Interdisciplinary aspects
Linear programming
Mathematics
metaheuristics
Methods
Optimization algorithms
Optimization techniques
Retaining walls
Seismic engineering
Structural design
Transfer functions
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Summary:The structural design of civil works is closely tied to empirical knowledge and the design professional’s experience. Based on this, adequate designs are generated in terms of strength, operability, and durability. However, such designs can be optimized to reduce conditions associated with the structure’s design and execution, such as costs, CO2 emissions, and related earthworks. In this study, a new discretization technique based on reinforcement learning and transfer functions is developed. The application of metaheuristic techniques to the retaining wall problem is examined, defining two objective functions: cost and CO2 emissions. An extensive comparison is made with various metaheuristics and brute force methods, where the results show that the S-shaped transfer functions consistently yield more robust outcomes.
ISSN:2227-7390
2227-7390
DOI:10.3390/math11092104