Abstract
Various algorithms inspired by evolutionary and physical processes have been extensively applied in solving complex construction engineering optimization problems. In this paper, Artificial Immune Systems (AIS), a computational approach inspired by the processes of human immune system, is introduced in terms of its basic mechanisms and its applications in construction engineering. Specifically, Clonal Selection Algorithm (CSA), one of main algorithms that form AIS, is based on clonal selection process of the immune system which includes the selection, hypermutation, and receptor editing processes. We discuss the CSA in detail and present its application in the classic construction optimization problem, construction site utilization planning (CSUP), which is the decision making process for identifying the most optimal layout of temporary facilities designed to support the construction process. When applied to a test case published in research literature, we found that CSA shows a robust capacity to search the solution space effectively and efficiently.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 267-273 |
| Number of pages | 7 |
| Journal | Procedia Engineering |
| Volume | 145 |
| DOIs | |
| State | Published - 2016 |
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Keywords
- Artificial Immune Systems
- Clonal Selection Algorithm
- CLONALG
- Optimization
ASJC Scopus subject areas
- Engineering(all)
Cite this
Application of Clonal Selection Algorithm in Construction Site Utilization Planning Optimization. / Wang, Xi; Deshpande, Abhijeet S.; Dadi, Gabriel B.; Salman, Baris.
In: Procedia Engineering, Vol. 145, 2016, p. 267-273.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Application of Clonal Selection Algorithm in Construction Site Utilization Planning Optimization
AU - Wang, Xi
AU - Deshpande, Abhijeet S.
AU - Dadi, Gabriel B.
AU - Salman, Baris
PY - 2016
Y1 - 2016
N2 - Various algorithms inspired by evolutionary and physical processes have been extensively applied in solving complex construction engineering optimization problems. In this paper, Artificial Immune Systems (AIS), a computational approach inspired by the processes of human immune system, is introduced in terms of its basic mechanisms and its applications in construction engineering. Specifically, Clonal Selection Algorithm (CSA), one of main algorithms that form AIS, is based on clonal selection process of the immune system which includes the selection, hypermutation, and receptor editing processes. We discuss the CSA in detail and present its application in the classic construction optimization problem, construction site utilization planning (CSUP), which is the decision making process for identifying the most optimal layout of temporary facilities designed to support the construction process. When applied to a test case published in research literature, we found that CSA shows a robust capacity to search the solution space effectively and efficiently.
AB - Various algorithms inspired by evolutionary and physical processes have been extensively applied in solving complex construction engineering optimization problems. In this paper, Artificial Immune Systems (AIS), a computational approach inspired by the processes of human immune system, is introduced in terms of its basic mechanisms and its applications in construction engineering. Specifically, Clonal Selection Algorithm (CSA), one of main algorithms that form AIS, is based on clonal selection process of the immune system which includes the selection, hypermutation, and receptor editing processes. We discuss the CSA in detail and present its application in the classic construction optimization problem, construction site utilization planning (CSUP), which is the decision making process for identifying the most optimal layout of temporary facilities designed to support the construction process. When applied to a test case published in research literature, we found that CSA shows a robust capacity to search the solution space effectively and efficiently.
KW - Artificial Immune Systems
KW - Clonal Selection Algorithm
KW - CLONALG
KW - Optimization
UR - http://www.scopus.com/inward/record.url?scp=84999852018&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84999852018&partnerID=8YFLogxK
U2 - 10.1016/j.proeng.2016.04.073
DO - 10.1016/j.proeng.2016.04.073
M3 - Article
VL - 145
SP - 267
EP - 273
JO - Procedia Engineering
JF - Procedia Engineering
SN - 1877-7058
ER -