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http://dx.doi.org/10.12989/sem.2013.47.2.227

Constructability optimal design of reinforced concrete retaining walls using a multi-objective genetic algorithm  

Kaveh, A. (Centre of Excellence for Fundamental Studies in Structural Engineering, School of Civil Engineering, Iran University of Science and Technology)
Kalateh-Ahani, M. (Centre of Excellence for Fundamental Studies in Structural Engineering, School of Civil Engineering, Iran University of Science and Technology)
Fahimi-Farzam, M. (Centre of Excellence for Fundamental Studies in Structural Engineering, School of Civil Engineering, Iran University of Science and Technology)
Publication Information
Structural Engineering and Mechanics / v.47, no.2, 2013 , pp. 227-245 More about this Journal
Abstract
The term "constructability" in regard to cast-in-place concrete construction refers mainly to the ease of reinforcing steel placement. Bar congestion complicates steel placement, hinders concrete placement and as a result leads to improper consolidation of concrete around bars affecting the integrity of the structure. In this paper, a multi-objective approach, based on the non-dominated sorting genetic algorithm (NSGA-II) is developed for optimal design of reinforced concrete cantilever retaining walls, considering minimization of the economic cost and reinforcing bar congestion as the objective functions. The structural model to be optimized involves 35 design variables, which define the geometry, the type of concrete grades, and the reinforcement used. The seismic response of the retaining walls is investigated using the well-known Mononobe-Okabe analysis method to define the dynamic lateral earth pressure. The results obtained from numerical application of the proposed framework demonstrate its capabilities in solving the present multi-objective optimization problem.
Keywords
reinforced concrete cantilever retaining wall; constructability; reinforcing bar congestion; multi-objective optimization; non-dominated sortiong genetic algorithm;
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Times Cited By KSCI : 2  (Citation Analysis)
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