Optimization of Reinforced Concrete Cantilever Retaining Wall using Particle Swarm Optimization. Issue 1 (1st February 2022)

• Record Type: Journal Article
• Authors: Srivastava, Shubham; Pandey, Saurabh; Kumar, Rajesh
• Is Part Of: IOP conference series. Volume 1225:Issue 1(2022)
• Publication Date: 2022-02-01
• Subjects: Particle Swarm Optimization -- Retaining Wall -- MATLAB -- Cantilever -- Optimization; Materials science -- Periodicals; 620.1105
• DOI: 10.1088/1757-899X/1225/1/012042
• Languages: English
• ISSNs: 1757-8981

Abstract

Abstract: The design of structures depends on designer's experience and generally, the designer proceeds with trial and error until he arrives at a design which satisfies prescribed limit states. This is especially true for reinforced concrete structures in which the structural configuration is decided first and then reinforcement requirements are determined, resulting in higher cost. Retaining walls involve a large number of variables and therefore have been far from optimization. However, since retaining walls comprise of 20-30 percent of the cost of highways in hilly regions, their optimization is critical to economy of the project. Particle Swarm Optimization (PSO) does not require the objective function to be linear or differentiable and hence is ideally suited for optimization of retaining walls. This study uses PSO as a tool for the optimizing a Cantilever RC Retaining Wall. The objective function consists of two parts - cost function and penalty term. A program and GUI was developed to implement PSO. A reduction in cost was achieved from 8% -17% depending on the height of retaining wall, while the optimization in weight varied from 9%-34%.