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compromise programming model in site selection for construction temporary facilities

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Abstract

One of the important project resources that have been overlooked during the planning phases of most construction projects is site selection of temporary facilities. In some projects, site selection can be as crucial as any other construction resource. Researchers have attempted to put together models that perform or assist planners in site selection. The aim of this paper is to present a framework for utilizing compromise programming (CP) for site selection of Construction Temporary Facilities (CTF) Compromise programming is used as a comprehensive tool that enables comparison between CTF alternatives. The CTF to be located concerns a site selection study conducted to evaluate locations for an onsite concrete batch plant to support the construction of the proposed facilities at the Savannah River Site. A comparison between the proposed model and Analytical Hierarchy Programming (AHP) models recently appeared in the literature is presented. As a construction management tool the proposed methodology describes better the trade-off between engineering performance (engineering, geoscience) and environmental performance (ecology, human health). However, the decision-making is project specific and relies on technical characteristics effectively limited the CTF site selection process criteria and the relative importance (weights) of the different factors involved.

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References

  • Brown, S., Schreier, H., Thompson, W.A. and Vertinsky, I. (1994). Linking multiple accounts with GIS as decision support system to resolve forestry/wildlife conflicts, Journal of Environmental Management,42, pp. 349–364.

    Article  Google Scholar 

  • Campbell, J. C., Radke, J., Gless, J. T. and Wirtshafter, R. M. (1992). An application of linear programming and geographic information systems: cropland allocation in Antigua, Environment and Planning A,24(4), pp. 535–549.

    Article  Google Scholar 

  • Chen, C.F. (2006). Applying the Analytical Hierarchy Process (AHP) approach to convention site selection. Journal of Travel Research,45(2), pp. 167–174.

    Article  Google Scholar 

  • Cheng, M.Y. and O’Connor, J.T. (1996). ArcSite: Enhanced GIS for construction site layout, Journal of Construction Engineering and Management, ASCE,122(4), pp. 329–336.

    Article  Google Scholar 

  • Chi, S. and Kuo, S. (2001). Examination of the influence of fuzzy analytic hierarchy process in the development of an intelligent location selection support system of convenience store IFSA World Congress and 20th NAFIPS International Conference,3, pp. 1312–1316.

    Article  Google Scholar 

  • Djokic, D. (1991). Urban stormwater drainage network assessment using an expert geographical information system, Ph.D. dissertation, University of Texas at Austin.

  • Duckstein, L., and Opricovic, S. (1980). Multiobjective optimization in River Basin development, Water Resources Research,16(1), pp. 14–20.

    Article  Google Scholar 

  • Elbeltagi, E. and Hegazy, T. (2001). A hybrid AI-Based system for site layout planning in construction” Computer-Aided Civil and Infrastructure Engineering, Blackwell Publishers,16(2), pp. 79–93.

    Google Scholar 

  • Environmental Protection Agency EPA(2007). Available at www.epa.gov

  • Evans, T. A., D. Djokic and Maidment, R. (1993). Development and application of expert geographic information system, Journal of Computing in Civil Engineering,7(3), pp. 339–353.

    Article  Google Scholar 

  • Fisher, P. F. (1991). Modelling soil map-unit inclusions by Monte Carlo simulation, International Journal of Geographical Information Systems,5(2), pp. 193–208.

    Article  Google Scholar 

  • Harris S.P. (2007) Sensitivity Analyses of Site Selection for a Concrete Batch Plant at the Savannah River Site Westinghouse Savannah River Company Contract No. DE-AC09-96SR18500 with the U.S. Department of Energy available at ∼HYPERLINK “http://www.osti.gov/bridge/”∼

  • Hegazy, T. and Elbeltagi, E. (1999). EvoSite: Evolution based model for site layout planning, Journal of Computing in Civil Engineering, ASCE,13(3), pp. 198–206.

    Google Scholar 

  • Koundinya, S., Chattopadhyay, D. and Ramanathan, R. (1994). Incorporating qualitative objectives in integrated resource planning: An AHP -compromise programming model, at Twenty-Seventh Convention of the Operational Research Society of India (ORSI), Indian Institute of Management, Calcutta, December.

  • Li, H. and Love, P.E. (1998). Site level facilities using genetic algorithms, Journal of Computing in Civil Engineering, ASCE,12(4), pp. 227–231.

    Article  Google Scholar 

  • Malczewski, J. (1999). GIS and Multicriteria Decision Analysis, John Wiley & Sons, New York.

    Google Scholar 

  • Manoliadis, O., Baronos, A. Tsolas, I. and Sawides, S. (2001). A multicriteria decision support system for landfill site selection, Journal of Environmental Protection and Ecology,2(2), pp. 273–278.

    Google Scholar 

  • Miller, D. (1994). Coupling of process-based vegetation models to GIS and knowledge-based systems with reference to vegetation change. In Worboys, M. F. (Ed.), Innovations in GIS, Taylor & Francis, London, pp. 241–250

    Google Scholar 

  • Osman, M. (2005) Cad-Based Dynamic Layout Planning Construction Sites Using Genetic Algorithms, MSc Thesis University of Toronto available at http://individual.utoronto.ca/hesham/Documents/MyPapers/THESIS.pdf

  • Ramanathan, R. (2006). Data envelopment analysis for weight derivation and aggregation in the analytic hierarchy process, Computers and Operations Research,33(5), pp. 1289- 1307.

    Article  Google Scholar 

  • Ramanathan, R. (1995)., “Combining qualitative objectives in integrated resource planning: A combined AHP - compromise programming model”, Energy Sources,17(5), pp. 565–581.

    Article  Google Scholar 

  • Romero, C. and Rehman, T. (1989). Multiple Criteria Analysis for Agricultural Decisions. New York, Elsevier Science Publishing Company Inc.

    Google Scholar 

  • Saaty, T.L. (1977). Multicriteria Decision Making: The Analytic Hierarchy Process, McGraw-Hill, New York.

    Google Scholar 

  • Saaty, T.L. (1980a). Multicriteria Decision Making: The Analytic Hierarchy Process. McGraw-Hill. New York.

    Google Scholar 

  • Saaty, T.L. (1980b). A Scaling Method for Priorities in Hierarchial Structures. Journal of Math Psychology,15(6), pp. 234–281.

    Google Scholar 

  • Tecle, A., andYitayew, M. (1990). Preference Ranking of Alternative Irrigation Technologies Via a Multicriterion Decision Making Procedure, American Society of Agricultural Engineers,33(5), pp. 1509–1517.

    Google Scholar 

  • Tommelien, I.D., Levit, R.E., and Hayes-Roth, B. (1992). SitePlan model for site layout, Journal of Construction Engineering and Management, ASCE,118(4), pp. 749–766.

    Google Scholar 

  • Tommelien, I.D. and Zouein, P.P. (1993). Interactive dynamic layout planning, Journal of Construction Engineering and Management, ASCE,119(2), pp. 266–287.

    Google Scholar 

  • Wike, L.D., et. al. (2001), Site Selection for Concrete Batch Plant to Support Surplus Plutonium Disposition Facilities at the Savannah River Site, WSRC-RP-2001-00673.

  • Xiang, W. (1993). A GIS/MMP-based coordination model and its application to distributed environmental planning, Environment and Planning B,20(2), pp. 195–220.

    Article  Google Scholar 

  • Yeh, I-C. (1995). Construction-site layout using annealed neural network, Journal of Computing in Civil Engineering, ASCE,9(3), pp. 201–208.

    Article  Google Scholar 

  • Zeleny, M. (1982). Multiple Criteria Decision Making. McGraw - Hill, New York.

    Google Scholar 

  • Zouein, P.P. and Tommelien, I.D. (2001). Improvement algorithm for limited space scheduling, Journal of Construction Engineering and Management, ASCE,127(2), pp. 116–124.

    Article  Google Scholar 

  • Zouein, P.P. and Tommelien, I.D. (1999). Dynamic layout planning using a hybrid incremental solution method, Journal of Construction Engineering and Management, ASCE,125(6), pp. 400–407.

    Article  Google Scholar 

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Correspondence to Odysseus G. Manoliadis.

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Manoliadis, O.G., Pantouvakis, J.P. & Tsolas, I.E. compromise programming model in site selection for construction temporary facilities. Oper Res Int J 7, 381–400 (2007). https://doi.org/10.1007/BF03024854

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