Optimization of Critical Infrastructure Location Using TTH Metaheuristic Algorithm with Cost-Benefit Principle Approach

Document Type : Original Article

Authors

1 Department of Civil engineering, Ro.C., Islamic Azad University, Roudehen, Iran.

2 Assistant Professor, Department of Civil engineering, Ro.C., Islamic Azad University, Roudehen, Iran.

Abstract

In recent decades, one of the country's fundamental challenges in the fields of defense and security has been the traditional view of the subject of passive defense. In such a way that planning for the location of infrastructures at the national level, cities or even construction sites, has been carried out without considering technological tools such as artificial intelligence and metaheuristic algorithms and solely based on the experience of experts in the field of passive defense engineering. Considering the classification of location problems as an NP-complete problem, traditional and precise mathematical methods, especially for medium and large-scale problems, cannot find the optimal solution in a reasonable time and while respecting all the principles of passive defense. As a result, researchers and scholars have been looking for alternative scientific methods to solve these problems that can provide the best answer at the right time. The best solution to this challenge is the use of metaheuristic algorithms.New metaheuristic methods have the potential to provide optimal solutions in a shorter time frame while respecting all the principles of location. Two case studies have been selected for this study to demonstrate the usefulness and efficiency of the TTH metaheuristic algorithm in optimizing location and layout of construction sites. In the first case study, the best, average and worst solutions were 12.538, 12.541 and 12.548 respectively, and in the second case study, the best solutions were 92.758, 96.386 and 100.014, which are more optimal than the results of the ECBO (Enhanced colliding bodies optimization), CBO (Colliding bodies optimization) and PSO (Particle swarm optimization) algorithms. Numerical studies show that the TTH algorithm can achieve promising results and has advantages in addressing complex optimization problems.

Keywords

Smiley face

References

  1. AM. Adrian, A. Utamima, and KJ. Wang, “A comparative study of GA PSO and ACO for solving construction site layout optimization,” KSCE. J. Civil. Eng., vol. 19(3), pp. 520–527, 2014.

https://doi.org/10.1007/s12205-013-1467-6

  1. CK. Wong, IWH. Fung, and CM. Tam, “Comparison of using mixedinteger programming and genetic algorithms for construction site facility layout planning,” J. Constr. Eng. Manag., vol. 136(10), pp.1116–1128, 2010.

http://dx.doi.org/10.1061/(ASCE)CO.1943-7862.0000214

  1. KC. Lam, CM. Tang, and WC. Lee, “Application of the entropy technique and genetic algorithms to construction site layout planning of medium-size projects,” Construct Manage Econ., vol. 23(2), pp. 127–145, 2005.

https://doi.org/10.1080/0144619042000202834

  1. IC. Yeh, “Architectural layout optimization using annealed neural network,” Automat Constr., vol 15(4), pp.531–539, 2006.

http://dx.doi.org/ 10.1016/j.autcon.2005.07.002

  1. DM. Tate, AE. Smith, “Unequal-area facility layout by genetic search,” IIE Trans., vol 27(4), pp.465–472, 1995.

http://dx.doi.org/ 10.1080/00207543.2013.774481

  1. H. Azarbonyad, R. Babazadeh, “A genetic algorithm for solving quadratic assignment problem (QAP),” Neural. Evol. Comput., pp. 2–5, 2014.

https://doi.org/10.48550/arXiv.1405.5050

  1. IC. Yeh, “Construction site layout using annealed neural network,” J. Comput. Civil. Eng., vol 9(7), pp.201–208, 1995.

http://dx.doi.org/10.1061/(ASCE)0887-3801(1995)9:3(201)

  1. H. Said, K., El-Rayes, “Performance of global optimization models for dynamic site layout planning of construction projects,” Automat Construct., vol 36, pp.71–78, 2013.

http://dx.doi.org/10.1016/j.autcon.2013.08.008

  1. X. Ning, KC. Lam, and MCK. Lam, “Dynamic construction site layout planning using max-min ant system,” Automat Construct., vol 19(1), pp.55–65, 2010.

http://dx.doi.org/10.1016/j.autcon.2009.09.002

  1. SS. Shahebrahimi, A. Lork, D. Sedaghat Shayegan, and A. Amir Kardoust, “Optimization of construction site layout planning with combination of metaheuristic algorithms,” Int. J. Nonlinear Anal. Appl., pp.1-12, 2024.

https://doi.org/10.22075/ijnaa.2024.33972.5070

  1. HM. Sanad, MA. Ammar, and ME. Ibrahim, “Optimal construction site layout considering safety and environmental aspects,” J. Constr. Eng .Manag., vol 134(7), pp.536–544, 2008.

https://doi.org/10.1061/ASCE0733-93642008134:7536

  1. ID. Tommelein, RE. Levitt, and B. Hayes-Roth, “Site-layout modeling: how can artificial intelligence help,” J. Constr. Eng. Manag., vol 118(3), pp.594–611, (1993).

https://doi.org/10.1061/(ASCE)0733-9364(1992)118:3(594)

  1. MR. Garey, DS. Johnson, “A guide to the theory of NPcompleteness,” A series of books in the mathematical sciences., 1979.

https://www.amazon.com/Computers-Intractability-NP-Completeness-Mathematical-Sciences/dp/0716710455

  1. IC. Yeh, “Construction site layout using annealed neural network,” J. Comput. Civil. Eng., vol 9(7), pp.201–208, 1995.

http://dx.doi.org/10.1061/(ASCE)0887-3801(1995)9:3(201)

  1. R.C. Eberhart, J. Kennedy, “A New Optimizer Using Particle Swarm Theory,” Proceedings of the Sixth International Symposium on Micro Machine and Human Science, Nagoya., pp.39-43, 1995.

https://doi.org/10.1109/MHS.1995.494215

  1. H. Zhang, JY. Wang, “Particle swarm optimization for construction site unequal-area layout,” J. Constr. Eng. Manag., vol 134(9), pp.739–748, (2008).

http://dx.doi.org/10.1061/(ASCE)0733-9364(2008)134:9(739)

  1. J. Xu, Z., Li, “Multi-objective dynamic construction site layout planning in fuzzy random environment,” Automat Construct., vol 27, pp.155–169, 2012.

http://dx.doi.org/10.1016/j.autcon.2012.05.017

  1. LC. Lien, MY. Cheng, “A hybrid swarm intelligence based particle-bee algorithm for construction site layout optimization,” Expert Syst Appl., vol 39(10), pp.9642–9650, 2012.

https://dl.acm.org/doi/10.1016/j.eswa.2012.02.134

  1. M. Dorigo, V. Maniezzo, and A. Colorni, “The ant system: Optimization by a colony of cooperating agents,” IEEE Trans. Syst. Man Cybern. Part B Cybern., vol 26( 1), pp. 29–41, 1996.

https://doi.org/10.1109/3477.484436

  1. K.C. Lam, X. Ning, T., Ng, “The application of the ant colony optimization algorithm to the construction site layout planning problem,” Construct. Manage. Econ., vol 25(4), pp. 359–374. (2007).

http://dx.doi.org/10.1080/01446190600972870

  1. S. O. Cheung, T. K. L. Tong, and C. M., Tam, “Site pre-cast yard layout arrangement through genetic algorithms,” Autom. Constr., vol 11(1), pp. 35–46, 2002.

https://doi.org/10.1016/S0926-5805(01)00044-9

  1. H. Li, PED. Love, “Site-level facilities layout using genetic algorithms,” J. Comput. Civil Eng., vol 12(4), pp.227–23, 1998.

https://doi.org/10.1061/(ASCE)0887-3801(1998)12:4(227)

  1. H. Li, PED. Love, “Genetic search for solving construction sitelevel unequal-area facility layout problems,” Automat Construct., vol 9(2), pp.217–226, 2000.

https://doi.org/10.1016/S0926-5805(99)00006-0

  1. MJ. Mawdesley, SH. Al-jibouri, and H. Yang, “Genetic algorithms for construction site layout in project planning,” J. Constr. Eng. Manag., vol 128(4), pp.418–426, 2002.

https://doi.org/10.1061/(ASCE)0733-9364(2002)128:5(418)

  1. MJ. Mawdesley, SH. Al-jibouri, “Proposed genetic algorithms for construction site layout,” Eng Appl. Artif. Intell., vol 16(3), pp.501–509, (2003).

https://doi.org/10.1016/j.engappai.2003.09.002

  1. PP. Zouein, H. Harmanani, and A. Hajar, “Genetic algorithm for solving site layout problem with unequal-size and constrained facilities,” J. Comput. Civil. Eng., vol 16(2), pp.143, 2002.

http://dx.doi.org/10.1061/(ASCE)0887-3801(2002)16:2(143)

  1. HM. Osman, ME. Georgy, and ME. Ibrahim, “A hybrid CAD-based construction site layout planning system using genetic algorithms,” Automat Construct., vol 12(6), pp.749–764, 2003.

http://dx.doi.org/10.1016/S0926-5805(03)00058-X

  1. E. Gharaie, A. Afshar, and M., Jalali, “Site layout optimization with ACO algorithm,” In: Proceedings of the 5th WSEAS international conference on artificial intelligence, Knowledge Engineering and Data Bases, Madrid., pp.90–94, 2006.
  2. A. Kaveh, Y. Vazirnia, “Construction Site Layout Planning Problem Using Metaheuristic Algorithms: A Comparative Study,” Iranian Journal of Science and Technology-Transactions of Civil Engineering., August2019.

https://doi.org/10.1007/s40996-018-0148-6

  1. M. Xu, Z. Mei, S. Luo, and Y. Tan, “Optimization algorithms for construction site layout planning: a systematic literature review. Eng,” Constr. Archit. Manage., July 2020.

http://dx.doi.org/10.1108/ECAM-08-2019-0457

  1. A. Ghadiri, D. Sedaghat Shayegan, and A. Amir Kardoust, “Multi objective firefly optimization algorithm for construction site layout planning,” Iranian. J. optim., vol 14(4), pp.245-260, 2022.
  2. A. Rouhi, E. Pira, “WHOFWA: An Effective Hybrid Metaheuristic Algorithm Based on Wild Horse Optimizer and Fireworks Algorithm,” J. Electr. Comput. Eng. Innovations., vol 12(2), pp. 319-342, 2024.

https://doi.org/10.22061/jecei.2024.10422.699

  1. A. Kaveh, AK. Shirzadi Javid, Y. Vazirnia, “Physics-inspired Metaheuristics for Construction Site Layout Planning Problem,” Period Polytech Civil Eng., vol 68(1), pp. 68–87, 2024.

https://doi.org/10.3311/PPci.22902

  1. A. Kaveh, M. Khanzadi, M. Alipour, and M. Rajabi Naraky, “ CBO and CSS algorithms for resource allocation and time-cost trade-off,” Period Polytech Civil Eng., vol 59(3), pp. 361–371, 2015.

https://doi.org/10.3311/PPci.7788

  1. A. Kaveh, VR. Mahdavi, “Colliding bodies optimization: a novel meta-heuristic method,” Comput Struct., vol 139, pp.18–27, 2014.

https://doi.org/10.1016/j.compstruc.2014.04.005

  1. A. Kaveh, A. Shakouri Mahmoud Abady, and S. Zolfaghari Moghaddam, “An adapted harmony search based algorithm for facility layout optimization,” Int. J. Civil. Eng, IUST., vol 10(1), pp. 37–42 , 2012.
  2. A. Kaveh, M. Ilchi Ghazaan, “Enhanced colliding bodies optimization for design problems with continuous and discrete variables,” Adv. Eng. Softw., vol 77, pp. 66–75, 2014.

https://doi.org/10.1016/j.advengsoft.2014.08.003

  1. Kaveh, A., (2014). Advances in metaheuristic algorithms for optimal design of structures. Springer International Publishing, Latest edition, Switzerland.

https://doi.org/10.1007/978-3-030-59392-6

  1. S.E. Abtahi, R. Kalhor, and M. Mirzaebrahimtehrani, “Improving the Level of Safety and Reducing the Vulnerability of the Transport Infrastructures of the Border Provinces with the Aim of Increasing Resilience),” Journal of passive deffense., vol 14, pp. 37-53, 2023, (in persion).

DOR: 20.1001.1.20086849.1402.14.1.4.4.

  1. S. Samadi Gharehveran, M. Nasiri, “Resilient Planning Against Disturbances and Optimal Location Determination for Mobile Energy Storage Systems in Smart Microgrids,” Journal of passive deffense., vol 16, pp. 69-80, 2025, (in persion).

 DOR: 20.1001.1.20086849.1404.16.2.6.2.

  1. SMR. Taheri, MA. Beheshtinia, “A Genetic Algorithm Developed for a Supply Chain Scheduling Problem,” Iranian Journal of Management Studies (IJMS)., vol 12(2), pp.281-306, 2019.
  2. C.M. Tam, KL. Tong, and KW., Chan, “Genetic algorithm for optimizing supply locations around tower crane,” Construct. Eng. Manag., vol 127(4), pp.315–321, 2001.

https://doi.org/10.1061/(ASCE)0733-9364(2001)127:4(315).

  1. PP. Zouein, ID. Tommelein, “Dynamic layout planning using a hybrid incremental solution method,” J. Constr. Eng. Manag., vol 5(1), pp. 1–16, 1999.

http://dx.doi.org/10.1061/(ASCE)0733-9364(1999)125:6(400)

  1. T. Hegazy, E. Elbeltagi, “EvoSite: evolution-based model for site layout planning,” J. Comput. Civ. Eng., vol 13(3), pp. 198-206, (1999).

https://doi.org/10.1061/(ASCE)0887-3801(1999)13:3(198)

  1. LY. Liang, WC. Chao, “The strategies of tabu search technique for facility layout optimization,” Automat Construct., vol 17(6), pp.657–669, 2008.

https://doi.org/10.1016/j.autcon.2008.01.001

  1. D. Sedaghat Shayegan, M. Mashayekhi, “Solving the prolem of locating construction sites based on a combination of weeding algorithm and forbidden search algorithm,” Amirkabir. J. of civil eng. Vol 16(8), pp. 1365–1382, 2025.

http://dx.doi.org/10.22060/ceej.2025.23469.8168

 

Passive Defense
Volume 17, Issue 1 - Serial Number 65
Serial number 65. Spring 2026
May 2026
Pages 193-211

Files

History

  • Receive Date: 01 November 2025
  • Revise Date: 07 December 2025
  • Accept Date: 17 December 2025
  • Publish Date: 22 May 2026

Share

How to cite

Statistics