Optimization of shallow foundation using gravitational search algorithm

Mohammad Khajehzadeh, Mohd. Raihan Taha, Ahmed El-Shafie, Mahdiyeh Eslami

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

In this study an effective method for nonlinear constrained optimization of shallow foundation is presented. A newly developed heuristic global optimization algorithm called Gravitational Search Algorithm (GSA) is introduced and applied for the optimization of foundation. The algorithm is classified as random search algorithm and does not require initial values and uses a random search instead of a gradient search, so derivative information is unnecessary. The optimization procedure controls all geotechnical and structural design constraints while reducing the overall cost of the foundation. To verify the efficiency of the proposed method, two design examples of spread footing are illustrated. To further validate the effectiveness and robustness of the GSA, these examples are solved using genetic algorithm. The results indicate that the proposed method could provide solutions of high quality, accuracy and efficiency for optimum design of foundation.

Original languageEnglish
Pages (from-to)1124-1130
Number of pages7
JournalResearch Journal of Applied Sciences, Engineering and Technology
Volume4
Issue number9
Publication statusPublished - 2012

Fingerprint

Constrained optimization
Global optimization
Structural design
Genetic algorithms
Derivatives
Costs
Optimum design

Keywords

  • Gravitational search algorithm
  • Minimum cost
  • Optimization
  • Shallow foundation

ASJC Scopus subject areas

  • Engineering(all)
  • Computer Science(all)

Cite this

Optimization of shallow foundation using gravitational search algorithm. / Khajehzadeh, Mohammad; Taha, Mohd. Raihan; El-Shafie, Ahmed; Eslami, Mahdiyeh.

In: Research Journal of Applied Sciences, Engineering and Technology, Vol. 4, No. 9, 2012, p. 1124-1130.

Research output: Contribution to journalArticle

Khajehzadeh, Mohammad ; Taha, Mohd. Raihan ; El-Shafie, Ahmed ; Eslami, Mahdiyeh. / Optimization of shallow foundation using gravitational search algorithm. In: Research Journal of Applied Sciences, Engineering and Technology. 2012 ; Vol. 4, No. 9. pp. 1124-1130.
@article{ee061e5b55f147b0bcfc005fc0f8070a,
title = "Optimization of shallow foundation using gravitational search algorithm",
abstract = "In this study an effective method for nonlinear constrained optimization of shallow foundation is presented. A newly developed heuristic global optimization algorithm called Gravitational Search Algorithm (GSA) is introduced and applied for the optimization of foundation. The algorithm is classified as random search algorithm and does not require initial values and uses a random search instead of a gradient search, so derivative information is unnecessary. The optimization procedure controls all geotechnical and structural design constraints while reducing the overall cost of the foundation. To verify the efficiency of the proposed method, two design examples of spread footing are illustrated. To further validate the effectiveness and robustness of the GSA, these examples are solved using genetic algorithm. The results indicate that the proposed method could provide solutions of high quality, accuracy and efficiency for optimum design of foundation.",
keywords = "Gravitational search algorithm, Minimum cost, Optimization, Shallow foundation",
author = "Mohammad Khajehzadeh and Taha, {Mohd. Raihan} and Ahmed El-Shafie and Mahdiyeh Eslami",
year = "2012",
language = "English",
volume = "4",
pages = "1124--1130",
journal = "Research Journal of Applied Sciences, Engineering and Technology",
issn = "2040-7459",
publisher = "Maxwell Scientific Publications",
number = "9",

}

TY - JOUR

T1 - Optimization of shallow foundation using gravitational search algorithm

AU - Khajehzadeh, Mohammad

AU - Taha, Mohd. Raihan

AU - El-Shafie, Ahmed

AU - Eslami, Mahdiyeh

PY - 2012

Y1 - 2012

N2 - In this study an effective method for nonlinear constrained optimization of shallow foundation is presented. A newly developed heuristic global optimization algorithm called Gravitational Search Algorithm (GSA) is introduced and applied for the optimization of foundation. The algorithm is classified as random search algorithm and does not require initial values and uses a random search instead of a gradient search, so derivative information is unnecessary. The optimization procedure controls all geotechnical and structural design constraints while reducing the overall cost of the foundation. To verify the efficiency of the proposed method, two design examples of spread footing are illustrated. To further validate the effectiveness and robustness of the GSA, these examples are solved using genetic algorithm. The results indicate that the proposed method could provide solutions of high quality, accuracy and efficiency for optimum design of foundation.

AB - In this study an effective method for nonlinear constrained optimization of shallow foundation is presented. A newly developed heuristic global optimization algorithm called Gravitational Search Algorithm (GSA) is introduced and applied for the optimization of foundation. The algorithm is classified as random search algorithm and does not require initial values and uses a random search instead of a gradient search, so derivative information is unnecessary. The optimization procedure controls all geotechnical and structural design constraints while reducing the overall cost of the foundation. To verify the efficiency of the proposed method, two design examples of spread footing are illustrated. To further validate the effectiveness and robustness of the GSA, these examples are solved using genetic algorithm. The results indicate that the proposed method could provide solutions of high quality, accuracy and efficiency for optimum design of foundation.

KW - Gravitational search algorithm

KW - Minimum cost

KW - Optimization

KW - Shallow foundation

UR - http://www.scopus.com/inward/record.url?scp=84862094260&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84862094260&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:84862094260

VL - 4

SP - 1124

EP - 1130

JO - Research Journal of Applied Sciences, Engineering and Technology

JF - Research Journal of Applied Sciences, Engineering and Technology

SN - 2040-7459

IS - 9

ER -