Optimum design of reinforced concrete counterfort retaining walls using TLBO, Jaya algorithm

Öztürk H. T., Dede T., Türker E.

STRUCTURES, vol.25, pp.285-296, 2020 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 25
  • Publication Date: 2020
  • Doi Number: 10.1016/j.istruc.2020.03.020
  • Journal Name: STRUCTURES
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.285-296
  • Keywords: Optimization, Counterfort retaining wall, TLBO algorithm, Jaya algorithm, SAP2000-OAPI, LEARNING-BASED OPTIMIZATION, INTELLIGENCE, TESTS
  • Karadeniz Technical University Affiliated: Yes


In this study, the optimum design of a reinforced concrete counterfort retaining wall for minimum cost is investigated by using TLBO and Jaya algorithms. There are 17 design variables in the problem of reinforced concrete counterfort retaining wall created in the study. These design variables are related to the wall geometry and steel reinforcement in various parts of the wall. There are a number of charts used in the technical literature to determine the cross-sectional effects of the stem and heel slabs of the wall. However, it is seen that these charts have been prepared at certain aspect ratios of the plates. In this case, Open Application Programming Interface of SAP2000 Software (called SAP2000-API) is used within the algorithm to realize a more realistic structural analysis. Thus, the desired structural analysis can be performed by applying external loads on the wall model prepared in SAP2000 Software through MATLAB Software where the algorithm is encoded. The desired cross-sectional effects are taken from this Software and used in the algorithm. The problem has a total of 46 constraints which consist of checks of sliding, overturning, and bearing capacity of the wall, reinforced concrete cross-section controls, and conditions related to size and reinforcement. The performance of the algorithms according to the findings from the optimum design performed on a numerical application is evaluated with standard statistical data and Wilcoxon test. According to Wilcoxon test, it is also observed that TLBO algorithm is more successful than Jaya algorithm for this problem.