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Dynamic construction material layout planning optimization model by integrating 4D BIM

  • Min-Yuan Cheng
  • Nai-Wen Chang
Original Article
  • 20 Downloads

Abstract

Construction material layout planning is a key project in temporary facility layouts. When allocating materials without effective resource consolidation and planning in advance, construction managers usually have difficulties in comprehensively determining resource demand to optimize material layout. This also leads to reduced efficiency, increased cost, and unnecessary loss of time. This study proposed the dynamic construction material layout planning optimization model to investigate the optimization of material layout from the perspective of dynamic task scheduling. In addition to the variables of schedule advancement and evolution, dynamic material requirements, and changes in storage sites and areas, task float times were analyzed to account for the changes in three-dimensional travel distances between material supply and demand sites concurrently with changes in task schedules and ensure that the observations conformed to real-time conditions. First, schedule and building information modeling techniques as well as the procedures for quantity take-off and construction materials and quantity analysis were consolidated to produce dynamic material requirements data for construction layout planning. Second, the symbiotic organisms search algorithm was applied to derive the optimized construction site material layout plan. Finally, the proposed model was applied to a construction project. The required total distance for the dynamic material layout plan was 954,736 m, which saved roughly half of the required distance compared with the fixed material layout plan of 1,659,457 m. This greatly reduced material transportation costs and validated the effectiveness of the proposed model.

Keywords

Layout optimization Dynamic material site layout planning Building information model Artificial intelligence Symbiotic organism search 

Notes

Acknowledgements

The work that is described in this paper has been carried out with the support of the Ministry of Science and Technology, ROC (Project No. 102-2221-E-011-076-MY3).

References

  1. 1.
    Hegazy T, Elbeltagi E (1999) EvoSite: evolution-based model for site layout planning. J Comput Civ Eng 13(3):198–206CrossRefGoogle Scholar
  2. 2.
    Cheng MY, O’Connor JT (1996) Site layout of construction temporary facilities using enhanced-geographical information system (GIS). J Constr Eng Manag ASCE 112(4):329–336CrossRefGoogle Scholar
  3. 3.
    Hamiani A (1987) CONSITE: a knowledge-based expert system framework for construction site layout. University of Texas, AustinGoogle Scholar
  4. 4.
    Hegazy TM, Elbeltagi E (2000) Simplified spreadsheet solutions: a model for site layout planning. J Cost Eng 42(1):24–30Google Scholar
  5. 5.
    Lee RC, Moore JM (1967) CORELAP: computerized relationship layout planning. J Ind Eng 8(3):195–200Google Scholar
  6. 6.
    Smith DM (1987) An investigation of the space constraint problem in construction planning. Virginia Polytechnic Institute and State University, BlacksburgGoogle Scholar
  7. 7.
    Tommelein ID, Zouein PP (1993) Interactive dynamic layout planning. J Constr Eng Manag ASCE 119(2):266–287CrossRefGoogle Scholar
  8. 8.
    Yeh I-C (1995) Construction-site layout using annealed neural network. J Comput Civ Eng 9(3):201–208CrossRefGoogle Scholar
  9. 9.
    Zouein PP (1996) MoveSchedule: a planning tool for scheduling space use on construction sites. Civil and Environmental Engineering Dept., University of Michigan, Ann ArborGoogle Scholar
  10. 10.
    Abdou G, Dutta SP (1990) An integrated approach to facilities layout using expert systems. Int J Prod Res 28(4):685–708CrossRefGoogle Scholar
  11. 11.
    Baykasoğlu A, Gindy NNZ (2001) A simulated annealing algorithm for dynamic layout problem. Comput Oper Res 28(14):1403–1426MathSciNetCrossRefMATHGoogle Scholar
  12. 12.
    Heragu SS, Kusiak A (1990) Machine layout: an optimization and knowledge-based approach. Int J Prod Res 28(4):615–635CrossRefGoogle Scholar
  13. 13.
    Preas BT, Lorenzetti MJ, Ackland BD (1988) Physical design automation of VLSI systems. Benjamin/Cummings Pub. Co., San FranciscoGoogle Scholar
  14. 14.
    Riedel R (2011) Facilities planning—4th edition by JA Tompkins, JA White, YA Bozer, JMA Tanchoco. Int J Prod Res 49(24):7519–7520CrossRefGoogle Scholar
  15. 15.
    Cheng M-Y, Yang S-C (2001) GIS-based cost estimates integrating with material layout planning. J Constr Eng Manag 127(4):291–299CrossRefGoogle Scholar
  16. 16.
    Said H, El-Rayes K (2012) Optimal material logistics planning in congested construction sites, construction research congress 2012, West Lafayette, Indiana, United States, pp 1580–1589Google Scholar
  17. 17.
    Lee H-Y, Yang IT, Lin Y-C (2012) Laying out the occupant flows in public buildings for operating efficiency. Build Environ 51:231–242CrossRefGoogle Scholar
  18. 18.
    Lien L-C, Cheng M-Y (2012) A hybrid swarm intelligence based particle-bee algorithm for construction site layout optimization. Expert Syst Appl 39(10):9642–9650CrossRefGoogle Scholar
  19. 19.
    Mawdesley MJ, Al-jibouri SH, Yang H (2002) Genetic algorithms for construction site layout in project planning. J Constr Eng Manag 128(5):418–426CrossRefGoogle Scholar
  20. 20.
    Succar B (2009) Building information modelling framework: a research and delivery foundation for industry stakeholders. Autom Constr 18(3):357–375CrossRefGoogle Scholar
  21. 21.
    Eastman C, Teicholz P, Sacks R, Liston K (2011) BIM handbook: a guide to building information modeling for owners, managers, designery, engineers, and contractors. Wiley, HobokenGoogle Scholar
  22. 22.
    Cheng MY, Prayogo D (2014) Symbiotic organisms search: a new metaheuristic optimization algorithm. Comput Struct 139:98–112CrossRefGoogle Scholar
  23. 23.
    U.o.T.a.A.C.I. Institute (1987) U.o.T.a.A.B.o.E. Research, Constructability Concepts File. Institute, Bureau of Engineering Research, University of Texas at Austin, AustinGoogle Scholar
  24. 24.
    Kaming PF, Holt GD, Kometa ST, Olomolaiye PO (1998) Severity diagnosis of productivity problems—a reliability analysis. Int J Proj Manag 16(2):107–113CrossRefGoogle Scholar
  25. 25.
    Tatum CB, Harris JA (1981) Construction plant requirements for nuclear sites. J Constr Div 107(4):543–550Google Scholar
  26. 26.
    Rad PF, James BM (1983) The layout of temporary construction facilities. Cost Eng 25(2):19–26Google Scholar
  27. 27.
    Warszawski (1990) Expert systems for crane selection. Constr Manag Econ 8(2):179–190CrossRefGoogle Scholar
  28. 28.
    Rodriguez-Ramos WE, Francis RL (1983) Single crane location optimization. J Constr Eng Manag 109(4):387–397CrossRefGoogle Scholar
  29. 29.
    Tommelein ID, Levitt RE, Hayes-Roth B (1989) SightPlan: an artificial intelligence tool to assist construction manager with site layout. In: 6th international symposium on automation and robotics in construction, San Francisco, USA, pp 340–347Google Scholar
  30. 30.
    Deshpande SD, Krishnamoorthy S, Deshpande VB (1987) Computer-aided site layout for construction projects. Omega 15(2):167–174CrossRefGoogle Scholar
  31. 31.
    Sadeghpour O, Moselhi ST, Alkass (2006) Computer-aided site layout planning. J Constr Eng Manag 132(2):143–151CrossRefGoogle Scholar
  32. 32.
    Jang H, Lee S, Choi S (2007) Optimization of floor-level construction material layout using genetic algorithms. Autom Constr 16(4):531–545CrossRefGoogle Scholar
  33. 33.
    Cheng M-Y, Lien L-C (2012) A hybrid AI-based particle bee algorithm for facility layout optimization. Eng Comput 28(1):57–69CrossRefGoogle Scholar
  34. 34.
    Huang C, Wong CK (2015) Optimisation of site layout planning for multiple construction stages with safety considerations and requirements. Autom Constr 53:58–68CrossRefGoogle Scholar
  35. 35.
    Volk R, Stengel J, Schultmann F (2014) Building information modeling (BIM) for existing buildings—literature review and future needs. Autom Constr 38:109–127CrossRefGoogle Scholar
  36. 36.
    Kiviniemi A, Karlshøj J, Tarandi V, Bell H, Karud OJ (2008) Review of the development and implementation of IFC compatible BIMGoogle Scholar
  37. 37.
    Choi J, Kim H, Kim I (2015) Open BIM-based quantity take-off system for schematic estimation of building frame in early design stage. J Comput Des Eng 2(1):16–25Google Scholar
  38. 38.
    Hartmann T, van Meerveld H, Vossebeld N, Adriaanse A (2012) Aligning building information model tools and construction management methods. Autom Constr 22(Supplement C):605–613CrossRefGoogle Scholar
  39. 39.
    Nicolle C, Cruz C (2011) Semantic building information model and multimedia for facility management. In: Filipe J, Cordeiro J (eds) Web information systems and technologies: 6th international conference, WEBIST 2010, Valencia, Spain, April 7–10, 2010, Revised Selected Papers. Springer, Berlin, pp 14–29CrossRefGoogle Scholar
  40. 40.
    Popescu C (1981) Managing temporary facilities for large projects. In: Proceeding of the project management institute and INTERNET joint symposium, Boston, MA, pp 170–173Google Scholar

Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Civil and Construction EngineeringNational Taiwan University of Science and TechnologyTaipeiTaiwan, ROC

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