نوع مقاله : مقاله پژوهشی

نویسندگان

1 استادیار گروه مهندسی صنایع،واحد سنندج، دانشگاه آزاد اسلامی ، سندج، ایران

2 مربی دانشکده مهندسی صنایع، دانشگاه علوم و فنون مازندران، بابل،ایران

3 دانشیار گروه مدیریت صنعتی ، دانشگاه علامه طباطبائی،تهران،ایران

4 استادیار گروه مهندسی صنایع،واحد سنندج، دانشگاه آزاد اسلامی، واحد سنندج،ایران

چکیده

هرچندکه صنعت ساخت‌و‌ساز، به ویژه به دلیل رابطه آن با سایر بخش‌های اقتصادی یکی از مهمترین شاخه‌هایی است که نقش کلیدی در رشد اقتصادی کشورها ایفا می‌کند، زنجیره تأمین ساخت و ساز کمتر مورد توجه محقیق قرار گرفته است. از این رو طراحی زنجیره تأمین ساخت و ساز نه تنها برای شرکت‌های عمرانی، بلکه برای دولت‌ها نیز از اهمیت زیادی برخوردار است. لذا، با ارائه یک مدل جدید برنامه-ریزی خطی مختلط عدد صحیح، این مقاله به معرفی یک چارچوب بهینه برای ساختاربندی شبکه زنجیره تأمین ساخت و ساز چند پروژه‌ای چند منبعی و دارای چند تأمین‌کننده برای شرکت‌های ساختمانی بزرگ دارای استراتژی تدارکات غیرمتمرکز می‌پردازد. هدف نهایی، طراحی یک مدل زنجیره تأمین با توجه به کیفیت و قابلیت اطمینان در بودجه پیش‌بینی شده، با در نظر داشتن کل زنجیره تأمین به عنوان یک موجودیت واحد است. فرمول‌بندی مسأله در یک چارچوب دو هدفه بوده و با استفاده از رویکرد "ال-پی متریک"سبب ایجاد یک چارچوب تک هدفه ساختارمند برای تبادل کیفیت-قابلیت اطمینان می‌شود. برای حل مسأله در ابعاد کوچک و متوسط از نرم‌افزار GAMS و در ابعاد بزرگ از یک الگوریتم ترکیبی شامل الگوریتم‌های ژنتیک و شبیه‌سازی تبرید استفاده می‌شود. نتایج حاصل از حل مدل نشان از این دارد که مدل امکان انتخاب اندازه مناسب برای زنجیره تأمین ساخت و ساز را به همراه تبادل کیفیت-قابلیت اطمینان به صورت توأمان فراهم می‌آورد و از این نظر با توجه به پیشینه تحقیق، نخستین پژوهش به شمار می‌رود. همچنین، نتایج مقایسه روشهای حل پیشنهادی نشان دهنده کارایی بالای الگوریتم حل پیشنهادی است.

کلیدواژه‌ها

عنوان مقاله [English]

Multi-project Optimal Scheduling Considering Reliability and Quality Within the Construction Supply Chain: A Hybrid Genetic Algorithm

نویسندگان [English]

  • Hêriş Golpîra 1
  • Erfan Babaee Tirkolaee 2
  • Mohammad Taghi Taghavifard 3
  • Fayegh Zaheri 4

1 Assistant Professor, Department of Industrial Engineering, Sanandaj Branch, Islamic Azad University, Sanandaj, Iran

2 Instructor, Department of Industrial Engineering Mazandaran University of Science and Technology, Babol, Iran

3 Associate Professor, Department of Industrial Management, Allameh Tabataba'i University, Tehran

4 Assistant Professor, Department of Industrial Engineering, Sanandaj Branch, Islamic Azad University, Sanandaj, Ira

چکیده [English]

Although the construction industry, especially because of its relationship with other economic sectors, is one of the most important sectors that plays a key role in a country's economic growth, the construction supply chain has been considered less attention. Therefore, construction supply chain network design is of great importance for not only the companies but also governments. Thus, presenting an original mixed integer linear programming model, this paper introduces an optimal framework for a multi-project multi-resource multi-supplier construction supply chain network design for large construction companies with a decentralized procurement strategy. The main objective is to design a reliable supply chain model based on the quality of projects under the certain predefined budget, considering the entire supply chain as a single entity. Using a bi-objective approach to formulate the chain and the Lp-metric approach to solve the problem, make it possible to obtain a single-objective structural framework to reliability-quality trade-off consideration. To solve the problem in small and medium scales, GAMS software is employed, and a hybrid algorithm based on Genetic Algorithm (GA) and Simulated Annealing (SA) algorithm is developed to solve the large-scaled problem. The results show the capability of the model to attain optimal size of the chain as well as the quality-reliability trade-off considering a pre-specified budget. And, to the best of authors knowledge this is the first to obtain such a structured integrated framework in the construction supply chain.

کلیدواژه‌ها [English]

  • Mixed integer linear programming
  • construction supply chain
  • multi-objective optimization
  • quantitative mathematical models
  • hybrid genetic algorithm
 
 
Behera, P., Mohanty, R., & Prakash, A. (2015). Understanding construction supply chain management. Production Planning & Control, 26(16), 1332-1350.
Chen, W., Lei, L., Wang, Z., Teng, M., & Liu, J. (2018). Coordinating supplier selection and project scheduling in resource-constrained construction supply chains. International Journal of Production Research, 56(19), 6512-6526.
Cheng, J. C., Law, K. H., Bjornsson, H., Jones, A., & Sriram, R. (2010). A service oriented framework for construction supply chain integration. Automation in Construction, 19(2), 245-260.
Choudhari, S., & Tindwani, A. (2017). Logistics optimisation in road construction project. Construction Innovation, 17(2), 158-179.
Dallasega, P., Rauch, E., & Linder, C. (2018). Industry 4.0 as an enabler of proximity for construction supply chains: A systematic literature review. Computers in Industry, 99, 205-225.
Donato, M., Ahsan, K., & Shee, H. (2015). Resource dependency and collaboration in construction supply chain: literature review and development of a conceptual framework. International Journal of Procurement Management, 8(3), 344-364.
Feng, C., Ma, Y., Zhou, G., & Ni, T. (2018). Stackelberg game optimization for integrated production-distribution-construction system in construction supply chain. Knowledge-Based Systems.
Golpîra, H. (2017). Supply chain network design optimization with risk-averse retailer. International Journal of Information Systems and Supply Chain Management (IJISSCM), 10(1), 16-28.
 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.
Golpîra, H., & Khan, S. A. R. (2019). A multi-objective risk-based robust optimization approach to energy management in smart residential buildings under combined demand and supply uncertainty. Energy, 170, 1113-1129.
Golpîra, H., Najafi, E., Zandieh, M., & Sadi-Nezhad, S. (2017). Robust bi-level optimization for green opportunistic supply chain network design problem against uncertainty and environmental risk. Computers & Industrial Engineering, 107, 301-312.
De Jong, K. A. (1975). An analysis of the behavior of a class of genetic adaptive systems Ph. D. Dthesis. Univ. Of Michigan. Ann Arbirmich.
Jaśkowski, P., Sobotka, A., & Czarnigowska, A. (2018). Decision model for planning material supply channels in construction. Automation in Construction, 90, 235-242.
Jiang, W., Lu, W., & Xu, Q. (2019). Profit Distribution Model for Construction Supply Chain with Cap-and-Trade Policy. Sustainability, 11(4), 1215.
Kirkpatrick, S., Gelatt, C. D., & Vecchi, M. P. (1983). Optimization by simulated annealing. Science, 220(4598), 671-680.
Lavikka, R. H., Smeds, R., & Jaatinen, M. (2015). Coordinating collaboration in contractually different complex construction projects. Supply chain management: an international journal, 20(2), 205-217.
Lin, Y.-q., Guo, C.-x., & Tan, Y. (2018). The incentive and coordination strategy of sustainable construction supply chain based on robust optimisation. Journal of Control and Decision, 1-34.
Liu, Q., Xu, J., & Qin, F. (2017). Optimization for the Integrated Operations in an Uncertain Construction Supply Chain. IEEE Transactions on Engineering Management, 64(3), 400-414.
Liu, Q., Xu, J., & Zhang, Z. (2015). Construction supply chain-based dynamic optimisation for the purchasing and inventory in a large scale construction project. European Journal of Industrial Engineering, 9(6), 839-865.
London, K., & Singh, V. (2013). Integrated construction supply chain design and delivery solutions. Architectural engineering and
design management, 9(3), 135-157.
Moon, S., Han, S., Zekavat, P. R., Bernold, L. E., & Wang, X. (2017). Process-waste reduction in the construction supply chain using proactive information network. Concurrent Engineering, 25(2), 123-135.
Nguyen, P. T., Nguyen, V. N., Pham, L. H., Nguyen, T. A., Le, Q., Nguyen, H. T. T., & Huynh, V. D. B. (2018). Application of Supply Chain Management in Construction Industry. Advances in Science and Technology-Research Journal, 12(2), 11-19.
Niu, Y., Lu, W., Liu, D., Chen, K., Anumba, C., & Huang, G. G. (2016). An SCO-Enabled Logistics and Supply Chain–Management System in Construction. Journal of construction engineering and management, 143(3), 04016103.
Rahimi, Y., Tavakkoli-Moghaddam, R., Shojaie, S., & Cheraghi, I. (2017). Design of an innovative construction model for supply chain management by measuring agility and cost of quality: An empirical study. Scientia Iranica, 24(5), 2515-2526.
Seth, D., Nemani, V. K., Pokharel, S., & Al Sayed, A. Y. (2018). Impact of competitive conditions on supplier evaluation: a construction supply chain case study. Production Planning & Control, 29(3), 217-235.
Shakantu, W., Tookey, J. E., & Bowen, P. A. (2003). The hidden cost of transportation of construction materials: an overview. Journal of Engineering, Design and Technology, 1(1), 103-118.
Simatupang, T. M., & Sridharan, R. (2016). A critical analysis of supply chain issues in construction heavy equipment. International Journal of Construction Management, 16(4), 326-338.
Thunberg, M., & Fredriksson, A. (2018). Bringing planning back into the picture–How can supply chain planning aid in dealing with supply chain-related problems in construction? Construction Management and Economics, 1-18.
Tserng, H. P., Yin, S. Y., & Li, S. (2006). Developing a resource supply chain planning system for construction projects. Journal of construction engineering and management, 132(4), 393-407.
Vidalakis, C., Tookey, J. E., & Sommerville, J. (2011). Logistics simulation modelling across construction supply chains. Construction innovation, 11(2), 212-228.
Vrijhoef, R., & Koskela, L. (2000). The four roles of supply chain management in construction. European Journal of Purchasing & Supply Management, 6(3-4), 169-178.
Wang, T.-K., Zhang, Q., Chong, H.-Y., & Wang, X. (2017). Integrated supplier selection framework in a resilient construction supply chain: An approach via analytic hierarchy process (AHP) and grey relational analysis (GRA). Sustainability, 9(2), 289.
Yang, Y., Pan, S., & Ballot, E. (2017). Innovative vendor-managed inventory strategy exploiting interconnected logistics services in the Physical Internet. International Journal of Production Research, 55(9), 2685-2702.
Yazdani, M., Chatterjee, P., Pamucar, D., & Abad, M. D. (2019). A risk-based integrated decision-making model for green supplier selection: A case study of a construction company in Spain. Kybernetes.
Zahiri, B., Torabi, S. A., Mohammadi, M., & Aghabegloo, M. (2018). A multi-stage stochastic programming approach for blood supply chain planning. Computers & Industrial Engineering, 122, 1-14.
Zainal Abidin, N. A., & Ingirige, B. (2018). The dynamics of vulnerabilities and capabilities in improving resilience within Malaysian construction supply chain. Construction Innovation.
Zhang, S., Fu, Y., & Kang, F. (2018). How to foster contractors' cooperative behavior in the Chinese construction industry: Direct and interaction effects of power and contract. International Journal of Project Management, 36(7), 940-953.
Zhou, P., Chen, D., & Wang, Q. (2013). Network design and operational modelling for construction green supply chain management. International Journal of Industrial Engineering Computations, 4(1), 13-28.