Big Data and Computing Visions

Quarterly Publication

About Journal

Aims and Scope

Open Access policy

Financial Policies

Crossmark Policy

Complaints Procedure

Peer Review Process

Journal Metrics

Related Links

FAQ

News

Current Issue

By Issue

By Author

By Subject

Author Index

Keyword Index

Optimizing Supplier Selection for a Construction Project by a Cash-Flow Approach Using a Hybrid Metaheuristic Algorithm

Document Type : Original Article

Authors

1 Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.

2 Department of Industrial Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran.

3 Department of Mathematic, Noor Branch, Islamic Azad University, Noor, Iran.

Abstract

Supplier selection is the practice of evaluating and selecting the best or most suitable supplier for the organization based on the candidates' qualities and qualifications. In large construction projects, supplier selection strongly impacts the quality of materials as well as the cash-flow and logistical support of the project. The issue becomes particularly important when a high number and volume of orders and a varied set of items are involved. If the procurement process is organized into several periods, the impact of Net Present Value (NPV) on the project's overall profit or loss becomes significant, as well. In this study, the solution to a multi-product multi-period supplier selection optimization problem is evaluated using a hybrid metaheuristic algorithm and considering the cash flow. Our analysis of the results shows that the algorithm is able to obtain the intended outcome within an appropriate timeframe and with high precision.

Keywords

References
  • Arani, H. V., & Torabi, S. A. (2018). Integrated material-financial supply chain master planning under mixed uncertainty. Information sciences, 423, 96-114.
  • Weber, C. A., Current, J. R., & Benton, W. C. (1991). Vendor selection criteria and methods. European journal of operational research, 50(1), 2-18.
  • Liu, S. S., & Wang, C. J. (2010). Profit optimization for multiproject scheduling problems considering cash flow. Journal of construction engineering and management, 136(12), 1268-1278.
  • Elazouni, A. M., & Metwally, F. G. (2007). Expanding finance-based scheduling to devise overall-optimized project schedules. Journal of construction engineering and management, 133(1), 86-90.
  • Zhang, X., Song, H., & Huang, G. Q. (2009). Tourism supply chain management: a new research agenda. Tourism management, 30(3), 345-358.
  • Nydick, R. L., & Hill, R. P. (1992). Using the analytic hierarchy process to structure the supplier selection procedure. International journal of purchasing and materials management, 28(2), 31-36.
  • Akarte, M. M., Surendra, N. V., Ravi, B., & Rangaraj, N. (2001). Web based casting supplier evaluation using analytical hierarchy process. Journal of the operational research society, 52(5), 511-522.‏
  • Bayazit, O. (2006). Use of analytic network process in vendor selection decisions. Benchmarking: an international journal, 13(5), 566-579. https://doi.org/10.1108/14635770610690410
  • Kahraman, C., Cebeci, U., & Ulukan, Z. (2003). Multi‐criteria supplier selection using fuzzy AHP. Logistics information management, ‏16(6), 382-394. https://doi.org/10.1108/09576050310503367
  • Weber, C. A., & Current, J. R. (1993). A multiobjective approach to vendor selection. European journal of operational research, 68(2), 173-184. https://doi.org/10.1016/0377-2217(93)90301-3
  • Weber, C. A., Current, J., & Desai, A. (2000). An optimization approach to determining the number of vendors to employ. Supply chain management: an international journal, 5(2), 90-98. https://doi.org/10.1108/13598540010320009
  • Ghodsypour, S. H., & O'Brien, C. (1998). A decision support system for supplier selection using an integrated analytic hierarchy process and linear programming. International journal of production economics, 56, 199-212. https://doi.org/10.1016/S0925-5273(97)00009-1
  • De Boer, L., Labro, E., & Morlacchi, P. (2001). A review of methods supporting supplier selection. European journal of purchasing & supply management, 7(2), 75-89.
  • Vokurka, R. J., Choobineh, J., & Vadi, L. (1996). A prototype expert system for the evaluation and selection of potential suppliers. International journal of operations & production management, 16(12), 106-127. https://doi.org/10.1108/01443579610151788
  • Weber, C. A. (1996). A data envelopment analysis approach to measuring vendor performance. Supply chain management: an international journal, 1(1), 28-39. https://doi.org/10.1108/13598549610155242
  • Liu, W. B., Meng, W., Li, X. X., & Zhang, D. Q. (2010). DEA models with undesirable inputs and outputs. Annals of operations research, 173(1), 177-194.
  • Ghodsypour, S. H., & O’brien, C. (2001). The total cost of logistics in supplier selection, under conditions of multiple sourcing, multiple criteria and capacity constraint. International journal of production economics, 73(1), 15-27. https://doi.org/10.1016/S0925-5273(01)00093-7
  • Bhutta, K. S., & Huq, F. (2002). Supplier selection problem: a comparison of the total cost of ownership and analytic hierarchy process approaches. Supply chain management: an international journal, 7(3), 126-135.
  • Singh, D. A., & Tiong, R. L. (2005). A fuzzy decision framework for contractor selection. Journal of construction engineering and management, 131(1), 62-70.
  • Lam, K. C., Palaneeswaran, E., & Yu, C. Y. (2009). A support vector machine model for contractor prequalification. Automation in construction, 18(3), 321-329.
  • Jaskowski, P., Biruk, S., & Bucon, R. (2010). Assessing contractor selection criteria weights with fuzzy AHP method application in group decision environment. Automation in construction, 19(2), 120-126. https://doi.org/10.1016/j.autcon.2009.12.014
  • Lam, K. C., & Yu, C. Y. (2011). A multiple kernel learning-based decision support model for contractor pre-qualification. Automation in construction, 20(5), 531-536. https://doi.org/10.1016/j.autcon.2010.11.019
  • Plebankiewicz, E. (2012). A fuzzy sets based contractor prequalification procedure. Automation in construction, 22, 433-443.
  • San Cristóbal, J. R. (2012). Contractor selection using multicriteria decision-making methods. Journal of construction engineering and management, 138(6), 751-758.
  • Elazouni, A. M., & Gab-Allah, A. A. (2004). Finance-based scheduling of construction projects using integer programming. Journal of construction engineering and management, 130(1), 15-24.
  • Ali, M. M., & Elazouni, A. (2009). Finance‐based CPM/LOB scheduling of projects with repetitive non‐serial activities. Construction management and economics, 27(9), 839-856.
  • Abido, M. A., & Elazouni, A. M. (2011). Multiobjective evolutionary finance-based scheduling: Entire projects' portfolio. Journal of computing in civil engineering, 25(1), 85-91.
  • Kelley Jr, J. E. (1961). Critical-path planning and scheduling: Mathematical basis. Operations research, 9(3), 296-320.
  • Hendrickson, C., Hendrickson, C. T., & Au, T. (1989). Project management for construction: Fundamental concepts for owners, engineers, architects, and builders. Chris Hendrickson.‏
  • Pagnoni, A. (1990). Project engineering: computer oriented planning and operational decision making. Springer-Verlag KG, Berlin. http://digilib.ub.ac.id/opac/detail-opac?id=26024
  • Fondahl, J. W. (1962). A non-computer approach to the critical path method for the construction industry. Retrieved from https://trid.trb.org/view/99661
  • Prager, W. (1963). A structural method of computing project cost polygons. Management science, 9(3), 394-404.
  • Siemens, N. (1971). A simple CPM time-cost tradeoff algorithm. Management science, 17(6), B-354.
  • Moselhi, O. (1993). Schedule compression using the direct stiffness method. Canadian journal of civil engineering, 20(1), 65-72.
  • El-Rayes, K., & Moselhi, O. (1998). Resource-driven scheduling of repetitive activities. Construction management & economics, 16(4), 433-446.
  • Leu, S. S., & Yang, C. H. (1999). GA-based multicriteria optimal model for construction scheduling. Journal of construction engineering and management, 125(6), 420-427.
  • El-Rayes, K., & Jun, D. H. (2009). Optimizing resource leveling in construction projects. Journal of construction engineering and management, 135(11), 1172-1180.
  • Hegazy, T. (1999). Optimization of resource allocation and leveling using genetic algorithms. Journal of construction engineering and management, 125(3), 167-175.
  • Chan, W. T., Chua, D. K., & Kannan, G. (1996). Construction resource scheduling with genetic algorithms. Journal of construction engineering and management, 122(2), 125-132.
  • Hartmann, S. (2001). Project scheduling with multiple modes: a genetic algorithm. Annals of operations research, 102(1), 111-135.
  • Zhang, H., Tam, C. M., & Li, H. (2006). Multimode project scheduling based on particle swarm optimization. Computer‐aided civil and infrastructure engineering, 21(2), 93-103.
  • El-Rayes, K., & Kandil, A. (2005). Time-cost-quality trade-off analysis for highway construction. Journal of construction engineering and management, 131(4), 477-486.
  • El-Abbasy, M. S., Zayed, T., & Elazouni, A. (2012). Finance-based scheduling for multiple projects with multimode activities. C
  • Arani, H. V., & Torabi, S. A. (2018). Integrated material-financial supply chain master planning under mixed uncertainty. Information sciences, 423, 96-114.
  • Weber, C. A., Current, J. R., & Benton, W. C. (1991). Vendor selection criteria and methods. European journal of operational research, 50(1), 2-18.
  • Liu, S. S., & Wang, C. J. (2010). Profit optimization for multiproject scheduling problems considering cash flow. Journal of construction engineering and management, 136(12), 1268-1278.
  • Elazouni, A. M., & Metwally, F. G. (2007). Expanding finance-based scheduling to devise overall-optimized project schedules. Journal of construction engineering and management, 133(1), 86-90.
  • Zhang, X., Song, H., & Huang, G. Q. (2009). Tourism supply chain management: a new research agenda. Tourism management, 30(3), 345-358.
  • Nydick, R. L., & Hill, R. P. (1992). Using the analytic hierarchy process to structure the supplier selection procedure. International journal of purchasing and materials management, 28(2), 31-36.
  • Akarte, M. M., Surendra, N. V., Ravi, B., & Rangaraj, N. (2001). Web based casting supplier evaluation using analytical hierarchy process. Journal of the operational research society, 52(5), 511-522.‏
  • Bayazit, O. (2006). Use of analytic network process in vendor selection decisions. Benchmarking: an international journal, 13(5), 566-579. https://doi.org/10.1108/14635770610690410
  • Kahraman, C., Cebeci, U., & Ulukan, Z. (2003). Multi‐criteria supplier selection using fuzzy AHP. Logistics information management, ‏16(6), 382-394. https://doi.org/10.1108/09576050310503367
  • Weber, C. A., & Current, J. R. (1993). A multiobjective approach to vendor selection. European journal of operational research, 68(2), 173-184. https://doi.org/10.1016/0377-2217(93)90301-3
  • Weber, C. A., Current, J., & Desai, A. (2000). An optimization approach to determining the number of vendors to employ. Supply chain management: an international journal, 5(2), 90-98. https://doi.org/10.1108/13598540010320009
  • Ghodsypour, S. H., & O'Brien, C. (1998). A decision support system for supplier selection using an integrated analytic hierarchy process and linear programming. International journal of production economics, 56, 199-212. https://doi.org/10.1016/S0925-5273(97)00009-1
  • De Boer, L., Labro, E., & Morlacchi, P. (2001). A review of methods supporting supplier selection. European journal of purchasing & supply management, 7(2), 75-89.
  • Vokurka, R. J., Choobineh, J., & Vadi, L. (1996). A prototype expert system for the evaluation and selection of potential suppliers. International journal of operations & production management, 16(12), 106-127. https://doi.org/10.1108/01443579610151788
  • Weber, C. A. (1996). A data envelopment analysis approach to measuring vendor performance. Supply chain management: an international journal, 1(1), 28-39. https://doi.org/10.1108/13598549610155242
  • Liu, W. B., Meng, W., Li, X. X., & Zhang, D. Q. (2010). DEA models with undesirable inputs and outputs. Annals of operations research, 173(1), 177-194.
  • Ghodsypour, S. H., & O’brien, C. (2001). The total cost of logistics in supplier selection, under conditions of multiple sourcing, multiple criteria and capacity constraint. International journal of production economics, 73(1), 15-27. https://doi.org/10.1016/S0925-5273(01)00093-7
  • Bhutta, K. S., & Huq, F. (2002). Supplier selection problem: a comparison of the total cost of ownership and analytic hierarchy process approaches. Supply chain management: an international journal, 7(3), 126-135.
  • Singh, D. A., & Tiong, R. L. (2005). A fuzzy decision framework for contractor selection. Journal of construction engineering and management, 131(1), 62-70.
  • Lam, K. C., Palaneeswaran, E., & Yu, C. Y. (2009). A support vector machine model for contractor prequalification. Automation in construction, 18(3), 321-329.
  • Jaskowski, P., Biruk, S., & Bucon, R. (2010). Assessing contractor selection criteria weights with fuzzy AHP method application in group decision environment. Automation in construction, 19(2), 120-126. https://doi.org/10.1016/j.autcon.2009.12.014
  • Lam, K. C., & Yu, C. Y. (2011). A multiple kernel learning-based decision support model for contractor pre-qualification. Automation in construction, 20(5), 531-536. https://doi.org/10.1016/j.autcon.2010.11.019
  • Plebankiewicz, E. (2012). A fuzzy sets based contractor prequalification procedure. Automation in construction, 22, 433-443.
  • San Cristóbal, J. R. (2012). Contractor selection using multicriteria decision-making methods. Journal of construction engineering and management, 138(6), 751-758.
  • Elazouni, A. M., & Gab-Allah, A. A. (2004). Finance-based scheduling of construction projects using integer programming. Journal of construction engineering and management, 130(1), 15-24.
  • Ali, M. M., & Elazouni, A. (2009). Finance‐based CPM/LOB scheduling of projects with repetitive non‐serial activities. Construction management and economics, 27(9), 839-856.
  • Abido, M. A., & Elazouni, A. M. (2011). Multiobjective evolutionary finance-based scheduling: Entire projects' portfolio. Journal of computing in civil engineering, 25(1), 85-91.
  • Kelley Jr, J. E. (1961). Critical-path planning and scheduling: Mathematical basis. Operations research, 9(3), 296-320.
  • Hendrickson, C., Hendrickson, C. T., & Au, T. (1989). Project management for construction: Fundamental concepts for owners, engineers, architects, and builders. Chris Hendrickson.‏
  • Pagnoni, A. (1990). Project engineering: computer oriented planning and operational decision making. Springer-Verlag KG, Berlin. http://digilib.ub.ac.id/opac/detail-opac?id=26024
  • Fondahl, J. W. (1962). A non-computer approach to the critical path method for the construction industry. Retrieved from https://trid.trb.org/view/99661
  • Prager, W. (1963). A structural method of computing project cost polygons. Management science, 9(3), 394-404.
  • Siemens, N. (1971). A simple CPM time-cost tradeoff algorithm. Management science, 17(6), B-354.
  • Moselhi, O. (1993). Schedule compression using the direct stiffness method. Canadian journal of civil engineering, 20(1), 65-72.
  • El-Rayes, K., & Moselhi, O. (1998). Resource-driven scheduling of repetitive activities. Construction management & economics, 16(4), 433-446.
  • Leu, S. S., & Yang, C. H. (1999). GA-based multicriteria optimal model for construction scheduling. Journal of construction engineering and management, 125(6), 420-427.
  • El-Rayes, K., & Jun, D. H. (2009). Optimizing resource leveling in construction projects. Journal of construction engineering and management, 135(11), 1172-1180.
  • Hegazy, T. (1999). Optimization of resource allocation and leveling using genetic algorithms. Journal of construction engineering and management, 125(3), 167-175.
  • Chan, W. T., Chua, D. K., & Kannan, G. (1996). Construction resource scheduling with genetic algorithms. Journal of construction engineering and management, 122(2), 125-132.
  • Hartmann, S. (2001). Project scheduling with multiple modes: a genetic algorithm. Annals of operations research, 102(1), 111-135.
  • Zhang, H., Tam, C. M., & Li, H. (2006). Multimode project scheduling based on particle swarm optimization. Computer‐aided civil and infrastructure engineering, 21(2), 93-103.
  • El-Rayes, K., & Kandil, A. (2005). Time-cost-quality trade-off analysis for highway construction. Journal of construction engineering and management, 131(4), 477-486.
  • El-Abbasy, M. S., Zayed, T., & Elazouni, A. (2012). Finance-based scheduling for multiple projects with multimode activities. Construction research congress 2012: construction challenges in a flat world(pp. 386-396). https://ascelibrary.org/doi/epdf/10.1061/9780784412329.039
  • Houlihan, J. B. (1988). International supply chains: a new approach. Management decision, 26(3), 13-19.
  • Elazouni, A. M., & Metwally, F. G. (2005). Finance-based scheduling: Tool to maximize project profit using improved genetic algorithms. Journal of construction engineering and management, 131(4), 400-412.
  • onstruction research congress 2012: construction challenges in a flat world(pp. 386-396). https://ascelibrary.org/doi/epdf/10.1061/9780784412329.039
  • Houlihan, J. B. (1988). International supply chains: a new approach. Management decision, 26(3), 13-19.
  • Elazouni, A. M., & Metwally, F. G. (2005). Finance-based scheduling: Tool to maximize project profit using improved genetic algorithms. Journal of construction engineering and management, 131(4), 400-412.
Big Data and Computing Visions
Volume 2, Issue 2
June 2022
Pages 69-79
Files
History
  • Receive Date: 16 October 2021
  • Revise Date: 19 January 2022
  • Accept Date: 02 April 2022
Share
How to cite
Statistics