Efficient multi-objective optimization algorithms for construction site layout problem

Document Type : Article

Authors

1 Centre of Excellence for Fundamental Studies in Structural Engineering, Iran University of ‎Science and Technology, Narmak, Tehran, P.O. Box 16846-13114, Iran‎

2 School of Civil Engineering, Iran University of Science and Technology, Narmak, Tehran, b P.O. Bo x 16846 - 13114, Iran

Abstract

Construction site layout planning is one of the managerial aspects of the construction industry and has significant impacts on performance of the sites. Since in real site layout optimization, many objectives are involved, therefore multi-objective algorithms are needed. In this study, multi-objective version of two meta-heuristics, CBO and ECBO, are developed and their applicability and performance are checked on a case study. The quality of the results obtained, verify the ability of these algorithms in finding optimal pareto front on this problem. Another tool that is utilized in this study is data envelopment analysis (DEA) which by calculating the efficiency of optimal pareto front layouts, can help decision makers to select the final layout among the candidates. It should be mentioned that the DEA has previously been used in models with multiple inputs and outputs.

Keywords

Main Subjects


References

1. Sadeghpour, F. and Andayesh, M. The constructs of
site layout modeling: an overview", Canad. J. Civil
Eng., 42(3), pp. 199-212 (2015).
2. Tommelein, I.D., Levitt, R.E., and Hayes-Roth, B.
Sight plan model for site layout", Knowl Creat Di us
Util., 118(4), pp. 749-766 (1991).
3. Li, H. and Love, P.E. Genetic search for solving construction
site-level unequal-area facility layout problems",
Automat Construct., 9(2), pp. 217-226 (2000).
4. Lien, L.-C. and Cheng, M.-Y. A hybrid swarm intelligence
based particle-bee algorithm for construction
site layout optimization", Expert Syst Applic., 39(10),
pp. 9642-9650 (2012).
5. For, L., Around, R., Tam, B.C.M., Tong, T.K.L.,
and Chan, W.K.W. Genetic algorithm for optimizing
supply locations around tower crane", J. Construct
Eng. Manag., 127(4), pp. 315-321 (2001).
6. Cheung, S.O. Tong, T.K.L., and Tam, C.M. Site precast
yard layout arrangement through genetic algorithms",
Automat Construct., 11, pp. 35-46 (2002).
7. Xu, J. and Li, Z. Multi-objective dynamic construction
site layout planning in fuzzy random environment",
Automat Construct., 27, pp. 155-169 (2012).
8. Yahya, M. and Saka, M.P. Construction site layout
planning using multi-objective arti cial bee colony
algorithm with Levy
ights", Automat Construct., 38,
pp. 14-29 (2014).
9. Hammad, A.W.A. Akbarnezhad, A., and Rey, D. A
multi-objective mixed integer nonlinear programming
model for construction site layout planning to minimise
noise pollution and transport costs", Automat
Construct., 61, pp. 73-85 (2016).
10. El-Rayes, K., Asce, M., and Khalafallah, A. Tradeo
between safety and cost in planning construction
site layouts", J. Constuct Eng. Manag., 131(11), pp.
1186-1195 (2005).
11. Yeh, I.-C. Architectural layout optimization using
annealed neural network", Automat Construct., 15(4),
pp. 531-539 (2006).
12. Lam, K.C., Tang, C.M., and Lee, W.C. Application
of the entropy technique and genetic algorithms
to construction site layout planning of medium-size
projects", Construct Manag Econom., 23(2), pp. 127-
145 (2005).
13. Calis, G. and Yuksel, O. An improved ant colony
optimization algorithm for construction site layout
problems", J. Build Construct Plan Res., 3, pp. 221-
232 (2015).
14. Lam, K., Ning, X., and Ng, T. The application of
the ant colony optimization algorithm to the construction
site layout planning problem", Construct Manag
Econom., 25(4), pp. 359-374 (2007).
15. Adrian, A.M., Utamima, A., and Wang, K.-J. A
comparative study of GA, PSO and ACO for solving
construction site layout optimization", KSCE J. Civil
Eng., 19(3), pp. 520-527 (2014).
16. Zhang, H. and Wang, J.Y. Particle swarm optimization
for construction site unequal-area layout", J.
Construct Eng. Manag., 134(9), pp. 739-748 (2008).
17. Lien, L.-C. and Cheng, M.-Y. A hybrid swarm intelligence
based particle-bee algorithm for construction site
layout optimization", Expert Syst. Applic., 39(10), pp.
9642-9650 (2012).
18. Kaveh, A., Shakouri Mahmud Abadi, A., and
Zolfaghari Moghaddam, S. An adapted harmony
search based algorithm for facility layout optimization",
Int. J. Civil Eng., 10(1), pp. 1-6 (2012).
19. Kaveh, A., Khanzadi, M., Alipour, M., and Moghaddam,
M.R. Construction site layout planning problem
using two new meta-heuristic algorithms", Iranian J.
Sci. Technol., Civil Eng. Trans., 40(4), pp. 263-275
(2016).
20. Ning, X., Lam, K.C., and Lam, M.C.K. A decisionmaking
system for construction site layout planning",
Autom Construct., 20(4), pp. 459-473 (2011).
21. Azadeh, A., Motevali Haghighi, S., Asadzadeh, S.M.,
and Saedi, H. A new approach for layout optimization
in maintenance workshops with safety factors: The
case of a gas transmission unit", J. Loss Prevent Proc.
Indust., 26(6), pp. 1457-1465 (2013).
22. Kaveh, A. and Mahdavi, V.R. Colliding bodies optimization:
A novel meta-heuristic method", Comput
Struct., 139, pp. 18-27 (2014).
23. Kaveh, A. and Ilchi Ghazaan, M. Enhanced colliding
bodies optimization for design problems with continuous
and discrete variables", Adv. Eng. Softw., 77, pp.
66-75, (2014).
24. Deb, K., Pratap, A., Agarwal, S., and Meyarivan, T.
A fast and elitist multiobjective genetic algorithm:
NSGA-II", IEEE Trans Evol Comput., 6(2), pp. 182-
197 (2002).
25. Kaveh, A., Advances in Metaheuristic Algorithms for
Optimal Design of Structures, Springer International
Publishing, Switzerland, 2nd edition, (2017).
26. Kaveh, A., Applications of Metaheuristic Optimization
Algorithms in Civil Engineering, Springer, Switzerland
(2017).
2062 A. Kaveh et al./Scientia Iranica, Transactions A: Civil Engineering 25 (2018) 2051{2062
27. Farrell, M.J. The measurement of productive e-
ciency", J.R. Stat. Soc. Ser. A, 120(3), pp. 253-290
(1957).
28. Charnes, A. Cooper, W.W., and Rhodes, E. Measuring
the eciency of decision making units", European
J. Oper. Res., 2(6), pp. 429-444 (1978).