Designing a Construction Supply Chain Network for Resource Inventory Management Using Benders Decomposition Algorithm

Document Type : Research Paper

Authors

1 Ph.D. Student, Department of Industrial Engineering, Faculty of Engineering, University of Kurdistan, Sanandaj, Iran

2 Assistant Professor, Department of Industrial Engineering, Faculty of Engineering, University of Kurdistan, Sanandaj, Iran

3 Associate Professor, Department of Industrial Engineering, Faculty of Engineering, Sanandaj Branch, Islamic Azad University, Sanandaj, Iran

10.22084/ier.2024.5568

Abstract

Designing an efficient construction supply chain involves numerous complexities. Therefore, the imperative of designing an appropriate supply chain, considering the high diversity of resources (nonrenewable), holds significant importance.  Given the variable nature of the project environment, the dynamic progress of the project, and the risks associated with construction projects, the project may deviate from the scheduled timeline. On the other hand, the quality of resources plays a crucial role in the construction quality of construction projects. Therefore, in this study, a multi-objective mixed-integer programming model is proposed for the design of a two-echelon supply chain network in the construction industry. The objectives of the model include minimizing supply chain costs, minimizing deviation from resources time delivery, and maximizing the quality of resources. This framework is capable of dynamically scheduling resources in terms of timing and delivery, as well as selecting appropriate suppliers restricted to authorized facilities within a network. Both classical methods and the Benders Decomposition Algorithm are employed to solve the presented model. The problem was solved for three sizes. The Benders Decomposition Algorithm was able to efficiently solve the problem for all three sizes in a very short amount of time.

Keywords

Main Subjects


  • Ghahremani nahr, J., et al., (2019). Design of multi-objective multi-product multi period green supply chain network with considering discount under uncertainty, Journal of Industrial Engineering Research in Production Systems, 6(13), pp. 119-137.
  • Bashiri, M., and Sherafati, M., (2013). Advanced Bi-objective closed loop supply chain network design considering correlated criteria in fuzzy environment, Journal of Industrial Engineering Research in Production Systems, 1(1): pp. 25-36.
  • Abdi, F., et al., (2021). Location-inventory- redundancy allocation optimization problem in a multi-objective single- period supply chain network with stochastic demand, Journal of Industrial Engineering Research in Production Systems, 8(17): pp. 377-397.
  • Robinson, G., Leonard, J., and Whittington, T., (2021). Future of Construction. A Global Forecast for Construction to 2030, https://www.oxfordeconomics.com/resource/future-of-construction/(English).
  • Golpîra, H., Sadeghi, H., and Khan, S.A.R., (2021). Time –Cost Trade-off Optimal Approaches, in Application of Mathematics and Optimization in Construction Project Management, H. Golpîra, Editor, Springer International Publishing, pp. 119-140.
  • Simchi-Levi, D., Kaminsky, P., and Simchi-Levi., E., (2003). Designing & Managing the Supply Chain, McGraw-Hill Higher Education, New York.
  • Mozdgir Mobbarhan, A., Sadeghi, H.O. and Arbabi, S., (2022). Determining the Replenishment Policy and Supplier Selection in Integrated Supply Chain for Deteriorating Products, Journal of Industrial Engineering Research in Production Systems,. 20(10), pp. 133-151.
  • Nanaware, M., and Saharkar, U., (2017). Application of inventory control technique in construction, International Journal of Engineering Research and General Science, 5(4), pp.49-54.
  • Sadeghi, H., A. Mahmoodi, and Z. Rajabi, (2022). Economic Order Quantity with Discrete Demand and Delivery Orders, Journal of Industrial Management Perspective, 12(2): pp. 113-133.
  • فخرزاد، محمدباقر، مرادیان بروجنی، پگاه، صادقیه، احمد. (۱۳۹۳). "تولید و توزیع در زنجیره‌تامین سه‌سطحی براساس تفکر ناب با رویکرد GA" نشریه بین‌المللی مهندسی صنایع و مدیریت تولید، ۲۵(۳): ۳۶۵-۳۷۵.
  • Koskela, L., (1992). Application of the new production philosophy to construction, Vol. 72, Stanford university Stanford.
  • Obrien, W.J., and Fischer, M., (1993). Construction supply-chain management: a research framework.
  • Lu, H., et al., (2018). Study on construction material allocation policies: A simulation optimization method, Automation in Construction, 90, pp.201-212.
  • Vidalakis, C., Tookey, J.E. and Sommerville, J., (2013). Demand uncertainty in construction supply chains: a discrete event simulation study, Journal of the Operational Research Society, 64(8): pp. 1194-1204.
  • Zhang, X., Xiong, R., and Tao. S., (2019). Research on model algorithms of supply chain of material scheduling with elastic variables in construction site for giant projects, in Application of Intelligent Systems in Multi-modal Information Analytics, Springer.
  • Jaśkowski, P., Sobotka, A., and Czarnigowska, A., (2018). Decision model for planning material supply channels in construction. Automation in Construction, 90: pp. 235-242.
  • Hsu, P.Y., Angeloudis, P., and Aurisicchio, M., (2018). Optimal logistics planning for modular construction using two-stage stochastic programming. Automation in Construction, 94: pp. 47-61.
  • Mohammadnazari, Z., and Ghannadpour, S.F., (2021). Sustainable construction supply chain management with the spotlight of inventory optimization under uncertainty. Environment, Development and Sustainability, 23: pp. 10937-10972.
  • Fu, F., and Xing, W., (2021). An agent-based approach for project-driven supply chain problem under information asymmetry and decentralized decision-making. Computers & Industrial Engineering, 158: pp. 107410.
  • Said, H., and El-Rayes, K., (2013). Optimal utilization of interior building spaces for material procurement and storage in congested construction sites. Automation in construction, 31: pp. 292-306.
  • Said, H. and El-Rayes, k., (2014). Automated multi-objective construction logistics optimization system. Automation in Construction, 43: pp. 110-122.
  • Liu, Q., Xu, J., and Qin, F., (2017). Optimization for the integrated operations in an uncertain construction supply chain. IEEE transactions on engineering management, 64(3): pp. 400-414.
  • Hashim, M., Nazim, M., and Nadeem, A.H., (2013). Production-distribution planning in supply chain management under fuzzy environment for large-scale hydropower construction projects. in Proceedings of the Sixth International Conference on Management Science and Engineering Management: Focused on Electrical and Information Technology, Springer.
  • Liu, Q., and Tao. Z., (2015). A Multi-Objective Optimization Model for the Purchasing and Inventory in a Three-Echelon Construction Supply Chain, in Proceedings of the Ninth International Conference on Management Science and Engineering Management, Springer Berlin Heidelberg, Berlin.
  • Kulkarni, A., and Halder, S., (2020). A simulation-based decision-making framework for construction supply chain management (SCM), Asian Journal of Civil Engineering, 21(2): pp. 229-241.
  • Salari, S.A.S., et al., (2022). Off-Site construction Three-Echelon supply chain management with stochastic constraints: A modelling approach. Buildings, 12(2): pp. 119.
  • Said, H., and El-Rayes, k., (2011). Optimizing material procurement and storage on construction sites, Journal of Construction Engineering and Management,. 137(6): pp. 421-431.
  • Xue, X., et al., (2011). Comparing the value of information sharing under different inventory policies in construction supply chain, International Journal of Project Management, 29(7): pp. 867-876.
  • Golpîra, H., (2020). Optimal integration of the facility location problem into the multi-project multi-supplier multi-resource Construction Supply Chain network design under the vendor managed inventory strategy. Expert Systems with Applications, 139: pp. 112841.
  • Mohammadnazari, Z. and Ghannadpour, S.F., (2021). Sustainable construction supply chain management with the spotlight of inventory optimization under uncertainty. Environment, Development and Sustainability. 23(7): pp. 10937-10972.
  • Hashim, M., Nazim, M., and Nadeem, A.H., (2013). Production-Distribution Planning in Supply Chain Management Under Fuzzy Environment for Large-Scale Hydropower Construction Projects. in Proceedings of the Sixth International Conference on Management Science and Engineering Management, Springer London, London.
  • Babaei, M., and Omrani, H., (2017). Robust optimization approach for supplier selection under lean procurement. International journal of industrial engineering and production management, 28(3): pp. 459-469.
  • Rezaei, E., Paydar, M.M., and Safaei, A.S., (2020). Implementation of accelerating benders decomposition algorithm for supply chain considering new product development and customer relationship management, Journal of Industrial Mnagment Perspective, 10(1): pp. 41-63.