A decision support model for civil engineering projects based on multi-criteria and various data
Abstract
This paper develops a model, introduced in software, namely Multi-Criteria Decision-Making Model (MCDMM). The model helps decision makers selecting the most suitable alternative based on the customer requirements and preferences. Analytic Hierarchy Process (AHP) and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) form a package that covers most available data types in construction projects. In MCDMM, AHP produces criteria relative weights according to their influence on the discussed problem, while Fuzzy TOPSIS is applied to rank the available alternatives. The model consists of two modules, first one uses AHP only to deal with precise, qualitative alongside quantitative data, while the other module combines AHP with Fuzzy TOPSIS due to the importance of linguistic variables to cover undocumented data. MCDMM is verified using two real case studies. The model is applied to a real case project for constructing solar power plants at Saudi Arabia. A decision required to select the most suitable surveying technique for producing Digital Terrain Model (DTM) among four alternatives (Total Station, Remote Sensing, Photogrammetry, and Global Positioning Systems). This issue is studied and key points are identified for prioritizing among them. Total Station is selected based on the model results.
Keyword : multi-criteria decision-making, AHP, Fuzzy TOPSIS, civil engineering projects, solar power plants, surveying techniques
How to Cite
Issa, U. H., Miky, Y. H., & Abdel-Malak, F. F. (2019). A decision support model for civil engineering projects based on multi-criteria and various data. Journal of Civil Engineering and Management, 25(2), 100-113. https://doi.org/10.3846/jcem.2019.7551
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Abdel-malak, F. F., Issa, U. H., Miky, Y. H., & Osman, E. A. (2017). Applying decision-making techniques to civil engineering projects. Beni-Suef University Journal of Basic and Applied Sciences, 6(4), 326-331. https://doi.org/10.1016/j.bjbas.2017.05.004
Albayrak, E., & Erensal, Y. C. (2004). Using analytic hierarchy process (AHP) to improve human performance: An application of multiple criteria decision making problem. Journal of Intelligent Manufacturing, 15(4), 491-503. https://doi.org/10.1023/B:JIMS.0000034112.00652.4c
Al-Harbi, K. M. A.-S. (2001). Application of the AHP in project management. International Journal of Project Management, 19(1), 19-27. https://doi.org/10.1016/S0263-7863(99)00038-1
Almasoud, A. H., & Gandayh, H. M. (2015). Future of solar energy in Saudi Arabia. Journal of King Saud University – Engineering Sciences, 27(2), 153-157. https://doi.org/10.1016/j.jksues.2014.03.007
Alwetaishi, M., Gadi, M., & Issa, U. H. (2017). Reliance of building energy in various climatic regions using multi criteria. International Journal of Sustainable Built Environment, 6(2), 555-564. https://doi.org/10.1016/j.ijsbe.2017.12.002
Awasthi, A., & Chauhan, S. S. (2012). A hybrid approach integrating Affinity Diagram, AHP and fuzzy TOPSIS for sustainable city logistics planning. Applied Mathematical Modelling, 36(2), 573-584. https://doi.org/10.1016/j.apm.2011.07.033
Borshchev, A., & Filippov, A. (2004). From system dynamics and discrete event to practical agent-based modeling: Reasons, techniques, tools. In Proceedings of the 22nd International Conference of the System Dynamics Society, Oxford, England.
Bruno, G., Esposito, E., Genovese, A., & Simpson, M. (2016). Applying supplier selection methodologies in a multi-stakeholder environment: A case study and a critical assessment. Expert Systems with Applications, 43, 271-285. https://doi.org/10.1016/j.eswa.2015.07.016
Duguay, C. R. (1993). Radiation modeling in mountainous terrain – Review and status. Mountain Research and Development, 13(4), 339. https://doi.org/10.2307/3673761
Ebrahimnejad, S., Gitinavard, H., & Sohrabvandi, S. (2017). A new extended Analytical Hierarchy Process technique with incomplete intervalvalued information for risk assessment in IT outsourcing. IJE Transactions B: Applications, 30(5), 739-748.
El Chanati, H., El-Abbasy, M. S., Mosleh, F., & Senouci, A. (2016). Multi-criteria decision making models for water pipelines. Journal of Performance of Constructed Facilities, 30(4), 04015090. https://doi.org/10.1061/(ASCE)CF.1943-5509.0000842
Erdoğan, M., & Kaya, İ. (2016). A combined fuzzy approach to determine the best region for a nuclear power plant in Turkey. Applied Soft Computing, 39, 84-93. https://doi.org/10.1016/j.asoc.2015.11.013
Forman, E. H., & Selly, M. A. (2001). Decision by objectives. How to convince others that you are right. World Scientific. https://doi.org/10.1142/4281
Gitinavard, H., Pishvaee, M. S., & Jalalvand, F. (2017). A hierarchical multi-criteria group decision-making method based on TOPSIS and hesitant fuzzy information. International Journal of Applied Decision Sciences, 10(3), 213. https://doi.org/10.1504/IJADS.2017.085084
Hassan, A., & Issa, U. H. (2015). Developing a decision-making model for reinforced concrete columns strengthening. International Journal of GEOMATE, 9(1), 1333-1341. https://doi.org/10.21660/2015.17.77814
Issa, U. H., & Ahmed, A. (2014). On the quality of driven piles construction based on risk analysis. International Journal of Civil Engineering, 12(2), 121-129.
Issa, U. H., & Salama, I. M. (2018). Improving productivity in Saudi Arabian construction projects: An analysis based on Lean techniques. International Journal of Applied Engineering Research, 13(10), 8669-8678.
Jahan, A., Edwards, K. L., & Bahraminasab, M. (2016). Multi-criteria decision analysis for supporting the selection of engineering materials in product design (2nd ed.). Butterworth-Heinemann.
Karahalios, H. (2017). The application of the AHP-TOPSIS for evaluating ballast water treatment systems by ship operators. Transportation Research Part D: Transport and Environment, 52(Part A), 172-184. https://doi.org/10.1016/j.trd.2017.03.001
Mohammad, R., Nima, G. S., & Aminah, R. F. (2016). Overview of Fuzzy simulation techniques in construction engineering and management. In Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS), El Paso, TX, USA. https://doi.org/10.1109/NAFIPS.2016.7851610
Mosaad, S. A. A., Issa, U. H., & Hassan, M. S. (2018). Risks affecting the delivery of HVAC systems: Identifying and analysis. Journal of Building Engineering, 16, 20-30. https://doi.org/10.1016/j.jobe.2017.12.004
Mousavi, S., Gitinavard, H., & Siadat, A. (2014). A new hesitant fuzzy analytical hierarchy process method for decision-making problems under uncertainty. In IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) (pp. 622-626). Bandar Sunway, Malaysia.
Özat, S. T. (2013). Determination of criterion that affects supplier selection in public administration software tenders and selection of supplier (Doctoral dissertation, Çankaya University).
Pacheco, F., Cerrada, M., Sánchez, R.-V., Cabrera, D., Li, C., & de Oliveira, J. V. (2017). Attribute clustering using rough set theory for feature selection in fault severity classification of rotating machinery. Expert Systems with Applications, 71, 69-86. https://doi.org/10.1016/j.eswa.2016.11.024
Plebankiewicz, E., & Kubek, D. (2016). Multicriteria selection of the building material supplier using AHP and Fuzzy AHP. Journal of Construction Engineering and Management, 142(1), 04015057. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001033
Saaty, T. L. (1980). The analytic hierarchy process. New York: McGraw-Hill.
Sadeghi, N., Fayek, A. R., & Seresht, N. G. (2015). Queue performance measures in construction simulation models containing subjective uncertainty. Automation in Construction, 60, 1-11. https://doi.org/10.1016/j.autcon.2015.07.023
Samuel, O. W., Asogbon, G. M., Sangaiah, A. K., Fang, P., & Li, G. (2017). An integrated decision support system based on ANN and Fuzzy_AHP for heart failure risk prediction. Expert Systems with Applications, 68, 163-172. https://doi.org/10.1016/j.eswa.2016.10.020
Tavakkoli-Moghaddam, R., Gitinavard, H., Mousavi, S. M., & Siadat, S. (2015). An interval-valued hesitant fuzzy TOPSIS method to determine the criteria weights. In International Conference on Group Decision and Negotiation GDN 2015: Outlooks and Insights on Group Decision and Negotiation, Lecture Notes in Business Information Processing (pp. 157-169). Springer. https://doi.org/10.1007/978-3-319-19515-5_13
Torfi, F., & Rashidi, A. (2011). Selection of project managers in construction firms using Analytic Hierarchy Process (AHP) and Fuzzy Topsis: A case study. Journal of Construction in Developing Countries, 16(1), 69-89.
Wang, Y.-J., & Lee, H.-S. (2007). Generalizing TOPSIS for fuzzy multiple-criteria group decision-making. Computers & Mathematics with Applications, 53(11), 1762-1772. https://doi.org/10.1016/j.camwa.2006.08.037
Zyoud, S. H., Kaufmann, L. G., Shaheen, H., Samhan, S., & Fuchs-Hanusch, D. (2016). A framework for water loss management in developing countries under fuzzy environment: Integration of Fuzzy AHP with Fuzzy TOPSIS. Expert Systems with Applications, 61, 86-105. https://doi.org/10.1016/j.eswa.2016.05.016
Albayrak, E., & Erensal, Y. C. (2004). Using analytic hierarchy process (AHP) to improve human performance: An application of multiple criteria decision making problem. Journal of Intelligent Manufacturing, 15(4), 491-503. https://doi.org/10.1023/B:JIMS.0000034112.00652.4c
Al-Harbi, K. M. A.-S. (2001). Application of the AHP in project management. International Journal of Project Management, 19(1), 19-27. https://doi.org/10.1016/S0263-7863(99)00038-1
Almasoud, A. H., & Gandayh, H. M. (2015). Future of solar energy in Saudi Arabia. Journal of King Saud University – Engineering Sciences, 27(2), 153-157. https://doi.org/10.1016/j.jksues.2014.03.007
Alwetaishi, M., Gadi, M., & Issa, U. H. (2017). Reliance of building energy in various climatic regions using multi criteria. International Journal of Sustainable Built Environment, 6(2), 555-564. https://doi.org/10.1016/j.ijsbe.2017.12.002
Awasthi, A., & Chauhan, S. S. (2012). A hybrid approach integrating Affinity Diagram, AHP and fuzzy TOPSIS for sustainable city logistics planning. Applied Mathematical Modelling, 36(2), 573-584. https://doi.org/10.1016/j.apm.2011.07.033
Borshchev, A., & Filippov, A. (2004). From system dynamics and discrete event to practical agent-based modeling: Reasons, techniques, tools. In Proceedings of the 22nd International Conference of the System Dynamics Society, Oxford, England.
Bruno, G., Esposito, E., Genovese, A., & Simpson, M. (2016). Applying supplier selection methodologies in a multi-stakeholder environment: A case study and a critical assessment. Expert Systems with Applications, 43, 271-285. https://doi.org/10.1016/j.eswa.2015.07.016
Duguay, C. R. (1993). Radiation modeling in mountainous terrain – Review and status. Mountain Research and Development, 13(4), 339. https://doi.org/10.2307/3673761
Ebrahimnejad, S., Gitinavard, H., & Sohrabvandi, S. (2017). A new extended Analytical Hierarchy Process technique with incomplete intervalvalued information for risk assessment in IT outsourcing. IJE Transactions B: Applications, 30(5), 739-748.
El Chanati, H., El-Abbasy, M. S., Mosleh, F., & Senouci, A. (2016). Multi-criteria decision making models for water pipelines. Journal of Performance of Constructed Facilities, 30(4), 04015090. https://doi.org/10.1061/(ASCE)CF.1943-5509.0000842
Erdoğan, M., & Kaya, İ. (2016). A combined fuzzy approach to determine the best region for a nuclear power plant in Turkey. Applied Soft Computing, 39, 84-93. https://doi.org/10.1016/j.asoc.2015.11.013
Forman, E. H., & Selly, M. A. (2001). Decision by objectives. How to convince others that you are right. World Scientific. https://doi.org/10.1142/4281
Gitinavard, H., Pishvaee, M. S., & Jalalvand, F. (2017). A hierarchical multi-criteria group decision-making method based on TOPSIS and hesitant fuzzy information. International Journal of Applied Decision Sciences, 10(3), 213. https://doi.org/10.1504/IJADS.2017.085084
Hassan, A., & Issa, U. H. (2015). Developing a decision-making model for reinforced concrete columns strengthening. International Journal of GEOMATE, 9(1), 1333-1341. https://doi.org/10.21660/2015.17.77814
Issa, U. H., & Ahmed, A. (2014). On the quality of driven piles construction based on risk analysis. International Journal of Civil Engineering, 12(2), 121-129.
Issa, U. H., & Salama, I. M. (2018). Improving productivity in Saudi Arabian construction projects: An analysis based on Lean techniques. International Journal of Applied Engineering Research, 13(10), 8669-8678.
Jahan, A., Edwards, K. L., & Bahraminasab, M. (2016). Multi-criteria decision analysis for supporting the selection of engineering materials in product design (2nd ed.). Butterworth-Heinemann.
Karahalios, H. (2017). The application of the AHP-TOPSIS for evaluating ballast water treatment systems by ship operators. Transportation Research Part D: Transport and Environment, 52(Part A), 172-184. https://doi.org/10.1016/j.trd.2017.03.001
Mohammad, R., Nima, G. S., & Aminah, R. F. (2016). Overview of Fuzzy simulation techniques in construction engineering and management. In Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS), El Paso, TX, USA. https://doi.org/10.1109/NAFIPS.2016.7851610
Mosaad, S. A. A., Issa, U. H., & Hassan, M. S. (2018). Risks affecting the delivery of HVAC systems: Identifying and analysis. Journal of Building Engineering, 16, 20-30. https://doi.org/10.1016/j.jobe.2017.12.004
Mousavi, S., Gitinavard, H., & Siadat, A. (2014). A new hesitant fuzzy analytical hierarchy process method for decision-making problems under uncertainty. In IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) (pp. 622-626). Bandar Sunway, Malaysia.
Özat, S. T. (2013). Determination of criterion that affects supplier selection in public administration software tenders and selection of supplier (Doctoral dissertation, Çankaya University).
Pacheco, F., Cerrada, M., Sánchez, R.-V., Cabrera, D., Li, C., & de Oliveira, J. V. (2017). Attribute clustering using rough set theory for feature selection in fault severity classification of rotating machinery. Expert Systems with Applications, 71, 69-86. https://doi.org/10.1016/j.eswa.2016.11.024
Plebankiewicz, E., & Kubek, D. (2016). Multicriteria selection of the building material supplier using AHP and Fuzzy AHP. Journal of Construction Engineering and Management, 142(1), 04015057. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001033
Saaty, T. L. (1980). The analytic hierarchy process. New York: McGraw-Hill.
Sadeghi, N., Fayek, A. R., & Seresht, N. G. (2015). Queue performance measures in construction simulation models containing subjective uncertainty. Automation in Construction, 60, 1-11. https://doi.org/10.1016/j.autcon.2015.07.023
Samuel, O. W., Asogbon, G. M., Sangaiah, A. K., Fang, P., & Li, G. (2017). An integrated decision support system based on ANN and Fuzzy_AHP for heart failure risk prediction. Expert Systems with Applications, 68, 163-172. https://doi.org/10.1016/j.eswa.2016.10.020
Tavakkoli-Moghaddam, R., Gitinavard, H., Mousavi, S. M., & Siadat, S. (2015). An interval-valued hesitant fuzzy TOPSIS method to determine the criteria weights. In International Conference on Group Decision and Negotiation GDN 2015: Outlooks and Insights on Group Decision and Negotiation, Lecture Notes in Business Information Processing (pp. 157-169). Springer. https://doi.org/10.1007/978-3-319-19515-5_13
Torfi, F., & Rashidi, A. (2011). Selection of project managers in construction firms using Analytic Hierarchy Process (AHP) and Fuzzy Topsis: A case study. Journal of Construction in Developing Countries, 16(1), 69-89.
Wang, Y.-J., & Lee, H.-S. (2007). Generalizing TOPSIS for fuzzy multiple-criteria group decision-making. Computers & Mathematics with Applications, 53(11), 1762-1772. https://doi.org/10.1016/j.camwa.2006.08.037
Zyoud, S. H., Kaufmann, L. G., Shaheen, H., Samhan, S., & Fuchs-Hanusch, D. (2016). A framework for water loss management in developing countries under fuzzy environment: Integration of Fuzzy AHP with Fuzzy TOPSIS. Expert Systems with Applications, 61, 86-105. https://doi.org/10.1016/j.eswa.2016.05.016