Developing an optimization financing cost-scheduling trade-off model in construction project

References

• Abido M, Elazouni AM. 2010. Precedence-preserving GAs operators for scheduling problems with activities’ start times encoding. J Comput Civ Eng. 24(4):345–356.
   Web of Science ®Google Scholar
• Abido M, Elazouni AM. 2011. Multiobjective evolutionary finance-based scheduling: Entire projects’ portfolio. J Comput Civ Eng. 25(1):85–97.
   Web of Science ®Google Scholar
• Ahmed T, Hossain SM, Hossain MA. 2018. Reducing completion time and optimizing resource use of resource-constrained construction operation by means of simulation modeling. Int J Constr Manag. 1–12. DOI: https://doi.org/10.1080/15623599.2018.1543109.
   Google Scholar
• Alavipour SR, Arditi D. 2018. Optimizing financing cost in construction projects with fixed project duration. J Constr Eng Manage. 144(4):04018012.
   Web of Science ®Google Scholar
• Alghazi A, Elazouni A, Selim S. 2013. Improved genetic algorithm for finance-based scheduling. J Comput Civ Eng. 27(4):379–394.
   Web of Science ®Google Scholar
• Ali MM, Elazouni A. 2009. Finance‐based CPM/LOB scheduling of projects with repetitive non‐serial activities. Constr Manag Econ. 27(9):839–856.
   Google Scholar
• Ammar MA. 2005. Discussion of “Flexible Model for Time/Cost Tradeoff Problem” by John Moussourakis and Cengiz Haksever. J Constr Eng Manage. 131(8):942–942.
   Web of Science ®Google Scholar
• Arditi D, Pattanakitchamroon T. 2008. Analysis methods in time-based claims. J Constr Eng Manage. 134(4):242–252.
   Web of Science ®Google Scholar
• Ashuri B, Tavakolan M. 2013. Shuffled frog-leaping model for solving time-cost-resource optimization problems in construction project planning. J Comput Civ Eng. 29(1):04014026.
   Web of Science ®Google Scholar
• Au T, Hendrickson C. 1986. Profit measures for construction projects. J Constr Eng Manag. 112(2):273–286.
   Web of Science ®Google Scholar
• Chan W-T, Chua DK, Kannan G. 1996. Construction resource scheduling with genetic algorithms. J Constr Eng Manag. 122(2):125–132.
   Web of Science ®Google Scholar
• Clough RH, Sears GA, Sears SK, Segner RO, Rounds JL. 2015. Construction contracting: A practical guide to company management. Hoboken, NJ: Wiley.
   Google Scholar
• Dixit V, Chaudhuri A, Srivastava RK. 2018. Procurement scheduling in engineer procure construct projects: a comparison of three fuzzy modelling approaches. Int J Constr Manag. 18(3):189–206.
   Google Scholar
• Eid MS, Elbeltagi EE, El-Adaway IH. 2018. Simultaneous multi-criteria optimization for scheduling linear infrastructure projects. Int J Constr Manag. 1–15. DOI: https://doi.org/10.1080/15623599.2018.1505027.
   Google Scholar
• El-Abbasy MS, Zayed T, Elazouni A. 2012. Finance-based scheduling for multiple projects with multimode activities. Construction Research Congress 2012: Construction Challenges in a Flat World.
   Google Scholar
• El-Rayes K, Jun DH. 2009. Optimizing resource leveling in construction projects. J Constr Eng Manage. 135(11):1172–1180.
   Web of Science ®Google Scholar
• El-Rayes K, Moselhi O. 1998. Resource-driven scheduling of repetitive activities. Constr Manag Econ. 16(4):433–446.
   Google Scholar
• Elazouni A, Abido M. 2011. Multiobjective evolutionary finance-based scheduling: individual projects within a portfolio. Autom Constr. 20(7):755–766.
   Web of Science ®Google Scholar
• Elazouni AM, Gab-Allah AA. 2004. Finance-based scheduling of construction projects using integer programming. J Constr Eng Manag. 130(1):15–24.
   Web of Science ®Google Scholar
• Elazouni AM, Metwally FG. 2005. Finance-based scheduling: tool to maximize project profit using improved genetic algorithms. J Constr Eng Manage. 131(4):400–412.
   Web of Science ®Google Scholar
• Elazouni AM, Metwally FG. 2007. Expanding finance-based scheduling to devise overall-optimized project schedules. J Constr Eng Manage. 133(1):86–90.
   Web of Science ®Google Scholar
• Elbeltagi E, Hegazy T, Grierson D. 2005. Comparison among five evolutionary-based optimization algorithms. Adv Eng Inf. 19(1):43–53.
   Web of Science ®Google Scholar
• Eusuff MM, Lansey KE. 2003. Optimization of water distribution network design using the shuffled frog leaping algorithm. J Water Resour Plan Manag. 129(3):210–225.
   Web of Science ®Google Scholar
• Fathi H, Afshar A. 2010. GA-based multi-objective optimization of finance-based construction project scheduling. KSCE J Civ Eng. 14(5):627–638.
   Web of Science ®Google Scholar
• Fondahl JW. 1962. A non-computer approach to the critical path method for the construction industry. Stanford: Dept. of Civil Engineering, Stanford University.
   Google Scholar
• Gajpal Y, Elazouni A. 2015. Enhanced heuristic for finance-based scheduling of construction projects. Constr Manag Econ. 33(7):531–553.
   Web of Science ®Google Scholar
• Harmon KM. 2003. Conflicts between owner and contractors: proposed intervention process. Journal of Management in Engineering. 19(3):121–125.
   Web of Science ®Google Scholar
• Hegazy T. 1999. Optimization of resource allocation and leveling using genetic algorithms. J Constr Eng Manag. 125(3):167–175.
   Web of Science ®Google Scholar
• Hendrickson C, Au T. 1989. Project management for construction. Upper Saddle River, NJ: Prentice Hall.
   Google Scholar
• Hindelang TJ, Muth JF. 1979. A dynamic programming algorithm for decision CPM networks. Oper Res. 27(2):225–241.
   Web of Science ®Google Scholar
• Hinze JW. 2012. Construction planning and scheduling. Two-dimentional encoding schema and genetic operators. 9th Joint International Conference on Information Sciences (JCIS-06); 2006: Atlantis Press.
   Google Scholar
• Hossein Hashemi Doulabi S, Seifi A, Shariat SY. 2011. Efficient hybrid genetic algorithm for resource leveling via activity splitting. J Constr Eng Manage. 137(2):137–146.
   Web of Science ®Google Scholar
• Kandil A, El-Rayes K. 2006. Parallel genetic algorithms for optimizing resource utilization in large-scale construction projects. J Constr Eng Manage. 132(5):491–498.
   Web of Science ®Google Scholar
• Karshenas S, Haber D. 2006. Economic optimization of construction project scheduling. Constr Manag Econ. 8(2):135–146.
   Google Scholar
• Kelley Jr JE. 1961. Critical-path planning and scheduling: mathematical basis. Oper Res. 9(3):296–320.
   Web of Science ®Google Scholar
• Khalafallah A, Abdel-Raheem M. 2011. Electimize: new evolutionary algorithm for optimization with application in construction engineering. J Comput Civ Eng. 25(3):192–201.
   Web of Science ®Google Scholar
• Leu S-S, Yang C-H. 1999. GA-based multicriteria optimal model for construction scheduling. J Constr Eng Manag. 125(6):420–427.
   Web of Science ®Google Scholar
• Liu S-S, Wang C-J. 2008. Resource-constrained construction project scheduling model for profit maximization considering cash flow. Autom Constr. 17(8):966–974.
   Web of Science ®Google Scholar
• Liu S-S, Wang C-J. 2010. Profit optimization for multiproject scheduling problems considering cash flow. J Constr Eng Manage. 136(12):1268–1278.
   Web of Science ®Google Scholar
• Luong D-L, Tran D-H, Nguyen PT. 2018. Optimizing multi-mode time-cost-quality trade-off of construction project using opposition multiple objective difference evolution. Int J Constr Manag. 1–13. DOI: https://doi.org/10.1080/15623599.2018.1526630.
   Google Scholar
• Moselhi O. 1993. Schedule compression using the direct stiffness method. Can J Civ Eng. 20(1):65–72.
   Web of Science ®Google Scholar
• Ng ST, Zhang Y. 2008. Optimizing construction time and cost using ant colony optimization approach. J Constr Eng Manage. 134(9):721–728.
   Web of Science ®Google Scholar
• Ock J-H, Park HK. 2016. A study on the algorithm of cash flow forecasting model in the planning stage of a construction project. KSCE J Civ Eng. 20(6):2170–2176.
   Web of Science ®Google Scholar
• Pagnoni A. 2012. Project engineering: computer-oriented planning and operational decision making. Berlin: Springer.
   Google Scholar
• Pareek P, Han S, Misra S. 2016. Application of Bayesian updating for real-time schedule estimation in a concreting operation. Int J Constr Manag. 16(1):54–66.
   Google Scholar
• Park H-K. 2004. Cash flow forecasting in construction project. KSCE J Civ Eng. 8(3):265–271.
   Google Scholar
• Peterson SJ. 2013. Construction accounting and financial management. Upper Saddle River, NJ: Prentice Hall.
   Google Scholar
• Prager W. 1963. A structural method of computing project cost polygons. Manage Sci. 9(3):394–404.
   Web of Science ®Google Scholar
• Russell JS. 1991. Construction contract bonds. J Manag Eng. 7(3):299–313.
   Google Scholar
• Shadrokh S, Kianfar F. 2007. A genetic algorithm for resource investment project scheduling problem, tardiness permitted with penalty. Eur J Oper Res. 181(1):86–101.
   Web of Science ®Google Scholar
• Sonmez R, Bettemir ÖH. 2012. A hybrid genetic algorithm for the discrete time–cost trade-off problem. Exp Syst Appl. 39(13):11428–11434.
   Web of Science ®Google Scholar
• Sonmez R, Uysal F. 2015. Backward-forward hybrid genetic algorithm for resource-constrained multiproject scheduling problem. J Comput Civ Eng. 29(5):04014072.
   Web of Science ®Google Scholar
• Tavakolan M, Share MAM. 2013. Applying magnetic charged system search algorithm to construction project planning problems. Comput Civil Eng. 733–740. DOI: https://doi.org/10.1061/9780784413029.092.
   Google Scholar
• Valls V, Ballestin F, Quintanilla S. 2008. A hybrid genetic algorithm for the resource-constrained project scheduling problem. Eur J Oper Res. 185(2):495–508.
   Web of Science ®Google Scholar
• Yang X, Yuan J, Yuan J, Mao H. 2007. A modified particle swarm optimizer with dynamic adaptation. Appl Math Comput. 189(2):1205–1213.
   Web of Science ®Google Scholar
• Zheng DX, Ng ST. 2005. Stochastic time–cost optimization model incorporating fuzzy sets theory and nonreplaceable front. J Constr Eng Manage. 131(2):176–186.
   Web of Science ®Google Scholar
• Zheng DX, Ng ST, Kumaraswamy MM. 2004. Applying a genetic algorithm-based multiobjective approach for time-cost optimization. J Constr Eng Manag. 130(2):168–176.
   Web of Science ®Google Scholar