Use of Hybrid PSOGSA Search Algorithm for Optimum Design of RC Beam

Authors(2) :-Sonia Chutani, Jagbir Singh

A more realistic and optimum design of reinforced concrete (RC) beam using a hybrid of particle swarm optimization and gravitational search algorithm (PSOGSA) is presented in this paper. Optimal size and reinforcement of the beam element have been found by employing the technique in computer aided environment, whereby the whole process of analysis, design and optimization has been coded in C++. The analysis and design procedure follows specifications of Indian codes. Use of gravitational search along with standard particle swarm optimization technique has been found to possess a better capability to escape from local optimums with faster convergence than the standard PSO and GSA. In this approach, different variables of beam element have been considered as continuous functions and rounded off appropriately to imbibe the practical relevance of the present study. Few beam design examples have been considered to emphasis the validity of this optimum design procedure.

Authors and Affiliations

Sonia Chutani
Ph.D Scholar, IKG Punjab Technical University, Kapurthala, Punjab, India
Jagbir Singh
Department of Civil Engineering, Guru Nanak Dev Engineering College, Ludhiana, Punjab, India

Optimum Design, Particle Swarm Optimization, Gravitational Search Algorithm, Indian Design Standards.

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Publication Details

Published in : Volume 3 | Issue 5 | July-August 2017
Date of Publication : 2017-08-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 480-487
Manuscript Number : IJSRSET1734130
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Sonia Chutani, Jagbir Singh, " Use of Hybrid PSOGSA Search Algorithm for Optimum Design of RC Beam, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 3, Issue 5, pp.480-487, July-August-2017.
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