Simultaneous multi-criteria optimization for scheduling linear infrastructure projects

References

• Ammar MA. 2013. LOB and CPM integrated method for scheduling repetitive projects. J Constr Eng Manag. 139(1):44–50.
   Web of Science ®Google Scholar
• Beradi L, Giustolisi O, Savic D, Kapelan Z. 2009. An effective mulit-objective approach to prioritization of sewer pipe inspection. J Water Sci Technol. 60(4):841–850.
   PubMed Web of Science ®Google Scholar
• Chan W, Chua D, Kannan G. 1996. Construction resource scheduling with genetic algorithms. J Constr Eng Manag. 122(2):125–132.
   Web of Science ®Google Scholar
• Cole LJR. 1991. Construction scheduling: principles, practices, and six case studies. J Constr Eng Manag. 117(4):579–588.
   Web of Science ®Google Scholar
• Dolabi HAZ, Afshar A. 2016. Cost optimization of repetitive projects with varying production rates using a max-min ant system. Construction Research Congress Reston, Virginia, U.S.A.: American Society for Civil Engineering.
   Google Scholar
• Duffy G, Oberlender G, Jeong D. 2011. Linear scheduling model with varying production rates. J Constr Eng Manag. 137(8):574–582.
   Web of Science ®Google Scholar
• Eid M, El-Adaway I. 2017a. Integrating the social vulnerability of host communities and the objective functions of associated stakeholders during disaster recovery processes using agent-based modeling. J Manag Eng. 31(5):1–15.
   Google Scholar
• Eid M, El-Adaway I. 2017b. Sustainable disaster recovery decision-making support tool: integrating economic vulnerability into the objective functions of the associated stakeholders. J Manag Eng. 33(2):04016041–04016019.
   Web of Science ®Google Scholar
• Eid M, El-Adaway I. 2017c. Sustainable disaster recovery: multi-agent based model for integrating environmental vulnerability into decision making processes of the associated stakeholders. J Urban Plan Dev. 143(1):04016022.
   Web of Science ®Google Scholar
• Eid M, El-Adaway I, Coatney K. 2015. Evolutionary stable strategy for postdisaster insurance: game theory approach. J Manag Eng. 31(6):04015005. doi:10.1061/(ASCE)ME.1943-5479.0000357.
   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
• Elbelatgi E, ElKassas EM. 2008. Cost optimization of projects with repetitive activities using genetic algorithms. In Papadrakakis M, Topping BHV, editors. The sixth international conference on engineering computational technology. Stirlingshire, Scotland: Civil-Comp Press, Paper Ref. 66, Sep. 2-5, 2008, Athens, Greece; p. 15.
   Google Scholar
• Elbeltagi E, Hegazy E, Grierson D. 2010. A new evolutionary strategy for Pareto multi-objective optimization. In: Topping BHV, Adam JM, Pallares FJ, Bru R, Romero ML, editors. The seventh international conference on engineering computational technology. Stirlingshire, Scotland: Civil-Comp Press, Paper Ref. 19, Sep. 14-17, 2010, Valencia, Spain; p. 17.
   Google Scholar
• El-Rayes K, Moselhi S. 1998. Resource-driven scheduling of repetitive activities. Constr Manag Econ. 16(4):433–446.
   Google Scholar
• El-Rayes K, Moselhi O. 2001. Optimizing resource utilization for repetitive construction projects. J Constr Eng Manag. 127(1):18–27.
   Web of Science ®Google Scholar
• Fan S, Lin Y. 2007. Time-cost trade-off in repetitive projects with soft logic. Comp in Civil Eng. ASCE. 83–90.
   Google Scholar
• Feng C, Liu L, Burns S. 1997. Using genetic algorithms to solve construction time-cost trade-off problems. J Comput Civil Eng. 11(3):184–189.
   Web of Science ®Google Scholar
• Grierson DE. 2008. Pareto multi-criteria decision making. Adv Eng Inf, Elsevier, 22(3), 371–384.
   Web of Science ®Google Scholar
• Harmelink DJ. 1995. Linear scheduling model: the development of a linear scheduling model with micro computer applications for highway construction control. PhD thesis. Ames, Iowa: Iowa State Univ.
   Google Scholar
• Hegazy T, Ayed A. 1999. Simplified spreadsheet solutions: models for critical path method and Time–cost trade-off analysis. Cost Eng. 41(7):26–33.
   Google Scholar
• Hegazy T, Elhakeem A, Elbeltagi E. 2004. Distributed scheduling model for infrastructure networks. J Constr Eng Manag. 130(2):160–167.
   Web of Science ®Google Scholar
• Hegazy T, Kamarah E. 2008. Efficient repetitive scheduling for high-rise construction. J Constr Eng Manag. 134(4):253–264.
   Web of Science ®Google Scholar
• Hegazy T, Wassef N. 2001. Cost optimization in projects with repetitive non-serial activities. J Constr Eng Manag. 127(3):183–191.
   Web of Science ®Google Scholar
• Hsie M, Chang C-J, Yang I-T, Huang C-Y. 2009. Resource-constrained scheduling for continuous repetitive projects with time-based production units. Autom Constr. 18(7):942–949.
   Web of Science ®Google Scholar
• Holland JH. 1975. Adaptation in natural and artificial systems. Ann Arbor, Mich.: University of Michigan Press.
   Google Scholar
• Huang R, Sun K. 2006. Non-unit-based planning and scheduling of repetitive construction projects. J Constr Eng Manage. 132(6):585–597.
   Web of Science ®Google Scholar
• Huang Y, Zou X, Zhang L. 2016. Genetic algorithm–based method for the deadline problem in repetitive construction projects considering soft logic. J Manag Eng. 32(4):04016002. doi:10.1061/(ASCE)ME.1943-5479.0000426,
   Web of Science ®Google Scholar
• Hyari K, El-Rayes K. 2006. Optimal planning and scheduling for repetitive construction projects. J Manag Eng. 22(1):11–19.
   Web of Science ®Google Scholar
• Ioannou Photios G., and Yang I-Tung (2016). Repetitive scheduling method: requirements, modeling, and implementation. J Constr Eng Manag. 142, 04016002.
   Web of Science ®Google Scholar
• Ipsilandis PG. 2007. Multiobjective linear programming model for scheduling linear repetitive projects. J Constr Eng Manag. 133(6):417–424.
   Web of Science ®Google Scholar
• Leu SS, Hwang ST. 2001. Optimal repetitive scheduling model with shareable resource constraint. J Constr Eng Manag. 127(4):270–280.
   Web of Science ®Google Scholar
• Li H, Love P. 1997. Using improved genetic algorithms to facilitate time-cost optimization. J Constr Eng Manag. 123(3):233–237.
   Web of Science ®Google Scholar
• Li H, Zhang Q. 2009. Multiobjective optimization problems with complicated Pareto sets, MOEA/D and NSGA-IIO. IEEE Trans Evol Comput. 13(2):284–302.
   Web of Science ®Google Scholar
• Lim SM, Sultan ABM, Sulaiman MN, Mustapha A, Leong KY. 2017. Crossover and mutation operators of genetic algorithms. Int J Mach Learn Comput. 7(1):9–12.
   Google Scholar
• Lucko G. 2011. Optimizing cash flows for linear schedules modeled with singularity functions by simulated annealing. J Constr Eng Manag . 137(7):523–535.
   Web of Science ®Google Scholar
• Maravas A, Pantouvakis J-P. 2011. Fuzzy repetitive scheduling method for projects with repeating activities. J Constr Eng Manag. 137(7):561–564.
   Web of Science ®Google Scholar
• Mattila K, Park A. 2003. Comparison of linear scheduling model and repetitive scheduling model. J Constr Eng Manag. 129(1):56–64.
   Web of Science ®Google Scholar
• Moon H, Kim H, Kamat VR, Kang L. 2015. BIM-based construction scheduling method using optimization theory for reducing activity overlaps. J Comput Civil Eng. 29(3):04014048.
   Web of Science ®Google Scholar
• Moselhi O, Hassanein A. 2003. Optimized scheduling of linear projects. J Constr Eng Manag. 129(6):664–673.
   Web of Science ®Google Scholar
• Rahbar FF, Rowings JE. 1992. Repetitive activity scheduling process. Trans Am Assn Cost Eng. 2, O.5.1-O.5.8.
   Google Scholar
• Reda RM. 1990. RPM: repetitive project modeling. J Constr Eng Manag. 116(2):316–330. ASCE.
   Web of Science ®Google Scholar
• Roofigari-Esfahan N, Paez A, N.Razavi S. 2015. Location-aware scheduling and control of linear projects: introducing space-time float prisms. J Constr Eng Manag. 141(1):06014008.
   Web of Science ®Google Scholar
• Sacks R, Seppänen R, Priven V, Savosnick J. 2017. Construction flow index: a metric of production flow quality in construction. Constr Manag Econ. 35(1-2):45–63.
   Web of Science ®Google Scholar
• Senouci A, Al-Derham HR. 2008. Genetic algorithm-based multi-objective model for scheduling of linear construction projects. Adv Eng Softw J. 39(12):1023–1028.
   Web of Science ®Google Scholar
• Stradel O, Cacha J. 1982. Time space scheduling method. J Constr Div, ASCE. 108(3):445–457.
   Google Scholar
• Suhail SA, Neale RH. 1994. CPM/LOB: new methodology to integrate CPM and line of balance. J Constr Eng Manag. 120(3):667–684.
   Web of Science ®Google Scholar
• Vanhoucke M. 2006. Work continuity constraints in project scheduling. J Constr Eng Manag . 132(1):14–25.
   Web of Science ®Google Scholar
• Yamin R, Harmelink D. 2001. Comparison of linear scheduling model (LSM) and critical path method (CPM). J Constr Eng Manag. 127(5):374–381.
   Web of Science ®Google Scholar
• Zhang L, Pan C, Zou X. 2013. Criticality comparison between the repetitive scheduling method and the network model. J Constr Eng Manag. 139(10):06013004.
   Web of Science ®Google Scholar