پیوندهای مفید
آمار
| تعداد نشریات | 31 |
| تعداد شماره‌ها | 805 |
| تعداد مقالات | 7,710 |
| تعداد مشاهده مقاله | 35,384,713 |
| تعداد دریافت فایل اصل مقاله | 7,830,214 |
An Integrated Multi-Objective MILP Model for Rebar Delivery Scheduling and Vehicle Routing: A Case Study | ||
| Computational Sciences and Engineering | ||
| مقاله 3، دوره 4، شماره 2، آذر 2024، صفحه 217-236 اصل مقاله (495.58 K) | ||
| نوع مقاله: Original Article | ||
| شناسه دیجیتال (DOI): 10.22124/cse.2025.31203.1113 | ||
| نویسندگان | ||
| Seyed Amin Badri* 1؛ Mehdi Yaghoobi2 | ||
| 1University of Guilan | ||
| 2Amirkabir Khazar Steel Company, Lakan Industrial Town, Rasht, Iran | ||
| چکیده | ||
| This study addresses the critical challenge of optimizing rebar delivery in heavy logistics industries by proposing an integrated multi-objective mixed-integer linear programming (MILP) model for simultaneous delivery scheduling and vehicle routing. The model aims to minimize three conflicting objectives: the overall makespan of deliveries, the weighted customer dissatisfaction from delivery time windows based on customer priority, and the total transportation costs. A fuzzy multi-objective optimization approach, based on the principles of Bellman and Zadeh and Zimmermann’s method, is employed to transform this complex problem into a single-objective maximization problem of an overall satisfaction level. The efficacy and practical applicability of the proposed model are validated through a real-world case study from Amir Kabir Khazar Steel Company in Gilan province, Iran. The case study involves 51 customer orders to be delivered over a three-day planning horizon, incorporating realistic constraints such as specific time windows and customer priority levels. Computational results, obtained using GAMS with the CPLEX solver, demonstrate that the model successfully achieves a high overall satisfaction level of λ =0.841. The findings offer significant managerial insights for balancing operational efficiency, cost reduction, and customer satisfaction in rebar supply chains. | ||
| کلیدواژه‌ها | ||
| Rebar Supply Chain؛ Delivery Scheduling؛ Vehicle Routing Problem (VRP)؛ Multi-Objective Optimization؛ Mixed-Integer Linear Programming (MILP)؛ Fuzzy Programming | ||
| مراجع | ||
|
[1] Toth, P., & Vigo, D. (Eds.). (2014). Vehicle routing: problems, methods, and applications. Society for industrial and applied mathematics.
[2] Dantzig, G. B., & Ramser, J. H. (1959). The truck dispatching problem. Management Science, 6(1), 80-91.
[3] Laporte, G. (1992). The vehicle routing problem: An overview of exact and approximate algorithms. European journal of operational research, 59(3), 345-358.
[4] Solomon, M. M. (1987). Algorithms for the vehicle routing and scheduling problems with time window constraints. Operations research, 35(2), 254-265.
[5] Rincon-Garcia, N., Waterson, B. J., & Cherrett, T. J. (2018). Requirements from vehicle routing software: Perspectives from literature, developers and the freight industry. Transport Reviews, 38(1), 117-138.
[6] Vidal, T., Laporte, G., & Matl, P. (2020). A concise guide to existing and emerging vehicle routing problem variants. European Journal of Operational Research, 286(2), 401-416.
[7] Pinedo, M. L. (2016). Scheduling: Theory, algorithms, and systems. Springer.
[8] Fu, L. L., Aloulou, M. A., & Triki, C. (2017). Integrated production scheduling and vehicle routing problem with job splitting and delivery time windows. International Journal of Production Research, 55(20), 5942-5957.
[9] Mohamed Alshabibi, N., Matar, A. H., & H. Abdelati, M. (2025). Multi-Objective Mixed-Integer Linear Programming for Dynamic Fleet Scheduling, Multi-Modal Transport Optimization, and Risk-Aware Logistics. Sustainability, 17(10), 4707.
[10] Yang, C., Lee, Y., & Lee, C. (2025). Data-Driven Order Consolidation with Vehicle Routing Optimization. Sustainability, 17(3), 848.
[11] Deb, K. (2001). Multi-objective optimization using evolutionary algorithms. John Wiley & Sons.
[12] Song, X., Jones, D., Asgari, N., & Pigden, T. (2020). Multi-objective vehicle routing and loading with time window constraints: a real-life application. Annals of Operations Research, 291(1), 799-825.
[13] Wang, Y., Zheng, Z., Guo, L., Yang, Y., Zhang, S., Liu, X., & Gao, X. (2025). Production planning and scheduling in steel manufacturing process: a review and its intelligent development. International Journal of Minerals, Metallurgy and Materials.
[14] Khant, L. P., Widjaja, D. D., Kim, D., Rachmawati, T. S. N., & Kim, S. (2025). Optimizing Rebar Process and Supply Chain Management for Minimized Cutting Waste: A Building Information Modeling-Based Data-Driven Approach. Buildings, 15(6), 844.
[15] Fu, X., Ji, K., Zhang, Y., Xie, Q., & Huang, J. (2025). Intelligent Optimization Method for Rebar Cutting in Pump Stations Based on Genetic Algorithm and BIM. Buildings, 15(11), 1790.
[16] de Matos Sousa, J. G. (2018). Vehicle Routing Problem with Time Windows in the Distribution of Steel Products (Master's thesis, Universidade do Porto (Portugal)).
[17] Li, J., Guo, H., Zhou, Q., & Yang, B. (2019). Vehicle routing and scheduling optimization of ship steel distribution center under green shipbuilding mode. Sustainability, 11(15), 4248.
[18] Bellman, R. E., & Zadeh, L. A. (1970). Decision-making in a fuzzy environment. Management science, 17(4), B-141.
[19] Zimmermann, H. J. (1978). Fuzzy programming and linear programming with several objective functions. Fuzzy sets and systems, 1(1), 45-55.
[20] Badri, S. A., Daghbandan, A., Aghabeiginiyay Fatalaki, Z., & Mirzazadeh, M. (2021). Flow shop scheduling under Time-Of-Use electricity tariffs using fuzzy multi-objective linear programming approach. Journal of mathematical modeling, 9(2), 215-227. | ||
|
آمار تعداد مشاهده مقاله: 51 تعداد دریافت فایل اصل مقاله: 15 |
||