Balance of Cost, Time, and Quality Related to Construction Projects Regarding the Reinforced Concrete of Underground Structures using a Meta-Heuristic Algorithm

  • 1 Islamic Azad University, , Roudehen
  • 2 Islamic Azad University, Department of Civil Engineering, Tehran
  • 3 Islamic Azad University, Department of Civil Engineering, Roudehen
  • 4 Islamic Azad University, Department of Civil Engineering, Roudehen


Underground spaces having features such as stability, resistance, and being undetected can play a key role in reducing vulnerability by relocating infrastructures and manpower. In recent years, the competitive business environment and limited resources have mostly focused on the importance of project management in order to achieve its objectives. In this research, in order to find the best balance among cost, time, and quality related to construction projects using reinforced concrete in underground structures, a multi-objective mathematical model is proposed. Several executive approaches have been considered for project activities and these approaches are analyzed via several factors. It is assumed that cost, time, and quality of activities in every defined approach can vary between compact and normal values, and the goal is to find the best execution for activities, achieving minimum cost and the maximum quality for the project. To solve the proposed multi-objective model, the genetic algorithm NSGA-II is used.

If the inline PDF is not rendering correctly, you can download the PDF file here.

  • [1] G. Jalali and S. J. Hashemi Fesharaki, “passive defense in terms of laws and regulations,” ed. Passive Defense Organization, Tehran, 2010.

  • [2] A. Asgharian Jedi, “ architectural requirements in sustainable civil defense,” ed. martyr Beheshti University, 2007.

  • [3] A. Ghani, “patterns of passive defense of industrial and research centers according to the terms of war and peace and land use,” ed: Aerospace Industries Organization, Institute of martyr Chamran doctor, Tehran, 2006.

  • [4] M. T. Nouroozi, “ defensive security culture, Tehran,” ed, 2006.

  • [5] J. Movahedinia, “The fundamentals of passive defense,” ed: Third Edition, Tehran’s Malek Ashtar University, 2009.

  • [6] R. L. Sterling and J. Carmody, “The experience with innovative underground structures at the University of Minnesota. Proc.,” presented at the Int. Symp. On Unique Underground Structures, Denver, Colo, Golden, Colo: CSM Press, Colorado School of Mines,, 1990.

  • [7] R. Burke, “Project management: planning and control techniques,” ed. New Jersey, USA, 2013.

  • [8] J. P. Clements and J. Gido, “Effective project management,” ed: Evans Publishing Group 2008.

  • [9] X. Zheng and Q. Mao, “Construction time-cost-cost trade-off based on genetic algorithms under resource restriction. In Communication Systems, Networks and Applications (ICCSNA),” in Second International Conference on IEEE, 2010, pp. 188-191.

  • [10] M. Vanhoucke and D. Debels, “The discrete time/cost trade-off problem: extensions and heuristic procedures,” Journal of Scheduling, vol. 10, pp. 311-326, 2007.

  • [11] L. Shuquan and Z. Kongguo, “Research on multi-objective Optimization of lean construction project. In MultiMedia and Information Technology,” in MMIT’08, International Conference on IEEE, 2008, pp. 480-483.

  • [12] G. Assadipour and H. Iranmanesh, “The discreet time, cost and cost trade-off problem in project scheduling: an efficient solution method based on CellDE algorithm: general articles,” South African Journal of Industrial Engineering, vol. 21, pp. 93-101, 2010.

  • [13] K. Deb, A. Pratap, S. Agarwal, and T. A. M. T. Meyarivan, “A fast and elitist multiobjective genetic algorithm: NSGA-II.,” IEEE Transactions vol. 6, pp. 182-197, 2002.

  • [14] J. W. Fondahl, “A non-computer approach to the critical path method for the construction industry,” 1962.

  • [15] W. Prager, “A structural method of computing project cost polygons,” Management Science, vol. 9, pp. 394-404, 1963.

  • [16] O. Moselhi, “Schedule compression using the direct stiffness method,” Canadian Journal of Civil Engineering, vol. 20, pp. 65-72, 1993.

  • [17] J. E. Kelley Jr, “Critical-path planning and scheduling: Mathematical basis.,” Operations research, vol. 9, pp. 296-320, 1961.

  • [18] C. Hendrickson and T. Au, “Project management for construction: Fundamental concepts for owners, engineers, architects, and builders,” Chris Hendrickson, 1989.

  • [19] A. Pagnoni, “Project engineering: computer-oriented planning and operational decision making,” Springer Science & Business Media, 2012.

  • [20] J. H. Patterson and W. D. Huber, “A horizon-varying, zero-one approach to project scheduling,” Management Science, vol. 20, pp. 990-998, 1974.

  • [21] J. Liu and F. Rahbar, “Project time-cost trade-off optimization by maximal flow theory,” Journal of construction engineering and management, vol. 130, pp. 607-609, 2004.

  • [22] C. W. Feng, L. Liu, and S. A. Burns, “Stochastic construction time-cost trade-off analysis,” Journal of Computing in Civil Engineering, vol. 14, pp. 117-126, 2000.

  • [23] I. T. Yang, “Using elitist particle swarm optimization to facilitate bicriterion time-cost trade-off analysis,” Journal of construction engineering and management, vol. 133, pp. 498-505, 2007.

  • [24] L. Hong-mei, W. Zhuo-fu, and L. Hui-min, “Artificial bee colony algorithm for real estate portfolio optimization based on cost preference coefficient,” in In Management Science and Engineering (ICMSE), International Conference on IEEE, 2010.

  • [25] F. Jolai and G. Assadipour, “A hybrid cellular genetic algorithm for multi-objective crew scheduling problem,” In Hybrid Artificial Intelligence Systems, Springer Berlin Heidelberg, pp. 359-367, 2010.

  • [26] R. Shrivastava, S. Singh, and G. C. Dubey, “Multi objective optimization of time cost cost quantity using multi colony ant algorithm,” International Journal of Contemporary Mathematical Sciences, vol. 7, pp. 773-784, 2012.


Journal + Issues