یک مدل برنامه‌ریزی امکانی دوهدفه برای زمان‌بندی کامیون در یک سیستم انبار متقاطع با درهای منعطف با درنظر گرفتن زمان حمل‌ونقل درون انبار

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری، گروه مهندسی صنایع، دانشکدۀ فنی و مهندسی، دانشگاه شاهد، تهران، ایران

2 استاد، گروه مهندسی صنایع، دانشکدۀ فنی و مهندسی، دانشگاه شاهد، تهران، ایران

چکیده

استفاده از انبارهای متقاطع یک استراتژی لجستیکی است که در آن کالاها از کامیون‌های ورودی تخلیه شده و با حداقل ذخیره‌سازی در کامیون‌های خروجی بارگیری می‌شوند. یکی از مهم‌ترین چالش‌ها در مدیریت انبارهای متقاطع، مدیریت تجهیزات و نیروی انسانی دخیل در فرآیندهای تخلیه کالاها، جابجایی آن‌ها در داخل ترمینال و بارگیری مجدد آن‌ها در کامیون‌های خروجی است. در این مقاله یک مدل جدید دوهدفه برنامه‌ریزی خطی آمیخته با اعداد صحیح برای زمان‌بندی کامیون‌های ورودی و خروجی در یک ترمینال انبار متقاطع با درهای منعطف ارائه می‌شود که در آن فاصله بین درها و زمان لازم برای جابجایی کامیون‌ها در داخل انبار متقاطع نیز در مدل درنظر گرفته می­شود. هدف اول در مدل پیشنهادی حداقل کردن زمان کل عملیات و هدف دوم مدیریت تجهیزات و نیروی انسانی لازم در ترمینال انبار متقاطع از طریق حداقل کردن تعداد درهای درگیر در عملیات تخلیه و بارگیری است. باتوجه ‌به عدم ‌قطعیت موجود در پارامترهای مسأله، از اعداد فازی مثلثی برای مواجهه با عدم ‌قطعیت در پارامترها استفاده می­شود و یک رویکرد حل فازی ترکیبی جدید نیز برای حل مسائل برنامه‌ریزی چندهدفه امکانی ارائه می‌گردد. مدل و رویکرد حل پیشنهادی برای زمان‌بندی کامیون‌های ورودی و خروجی در یک ترمینال انبار متقاطع در یک گروه فعال در صنعت غذا و نوشیدنی مورد استفاده قرار می­گیرد و نتایج حاصل با دو روش موجود مقایسه می­شود. نتایج به‌دست ‌آمده نشان می­دهد رویکرد حل پیشنهادی کارکرد بهتری در مقایسه با روش‌های موجود دارد. 

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

A Bi-Objective Possiblistic Programming Model for Truck Scheduling in a Cross-Docking System with Flexible Dock Doors Considering Transshipment Time

نویسندگان [English]

  • Mohsen Rajabzadeh 1
  • Seyed Misam Mousavi 2
1 PhD student, Department of Industrial Engineering, Faculty of Engineering, Shahed University, Tehran, Iran
2 Professor, Department of Industrial Engineering, Faculty of Engineering, Shahed University, Tehran, Iran
چکیده [English]

Through a cross-docking strategy in logistics, goods are unloaded from inbound trucks and loaded onto outbound trucks with minimal storage. The management of equipment and manpower involved in unloading goods, moving them within the terminal, and reloading them on outgoing trucks is one of the most challenging aspects of cross-docking management. In this paper, a new bi-objective mixed-integer linear programming model is presented for scheduling incoming and outgoing trucks in a cross-docking terminal with flexible doors, where the distance between doors and the time for moving trucks inside the cross-dock are also taken into account. As a first objective, the proposed model attempts to minimize the total operation time, and as a second objective, it aims to manage the equipment and manpower required in the cross-docking terminal by minimizing the number of doors involved in unloading and loading operations. Considering the uncertainty of the parameters, triangular fuzzy numbers are used to deal with the uncertainty, and a hybrid solution approach is developed for solving multi-objective possibilistic programming problems. The proposed model and solving approach are used for scheduling incoming and outgoing trucks at a cross-docking terminal as part of a food and beverage-producing group, and the results are compared with two existing methods. The results show that the proposed method performs better compared to existing methods

کلیدواژه‌ها [English]

  • Cross-Docking
  • Truck Scheduling
  • Multi-Objective Possibilistic Programming
  • Compromise Programming
  • Food and Beverage Industry

مراجع

  • Shahabi-Shahmiri, R., Asian, S., Tavakkoli-Moghaddam, R., Mousavi, S. M., & Rajabzadeh, M. (2021). A routing and scheduling problem for cross-docking networks with perishable products, heterogeneous vehicles and split delivery. Computers & Industrial Engineering, 157, 107299.
  • Rijal, A., Bijvank, M., & de Koster, R. (2019). Integrated scheduling and assignment of trucks at unit-load cross-dock terminals with mixed service mode dock doors. European Journal of Operational Research, 278(3), 752-771.
  • Boysen, N., & Fliedner, M. (2010). Cross dock scheduling: Classification, literature review and research agenda. Omega, 38(6), 413-422.
  • Bartholdi, J. J., & Gue, K. R. (2004). The best shape for a crossdock. Transportation science, 38(2), 235-244.
  • Berghman, L., Briand, C., Leus, R., & Lopez, P. (2015, January). The truck scheduling problem at crossdocking terminals-exclusive versus mixed mode. In 4th international conference on operations research and enterprise systems (ICORES 2015) (pp. pp-247).
  • Bodnar, P., de Koster, R., & Azadeh, K. (2017). Scheduling trucks in a cross-dock with mixed service mode dock doors. Transportation Science, 51(1), 112-131.
  • Yu, W., & Egbelu, P. J. (2008). Scheduling of inbound and outbound trucks in cross docking systems with temporary storage. European journal of operational research, 184(1), 377-396.
  • Chen, F., & Lee, C. Y. (2009). Minimizing the makespan in a two-machine cross-docking flow shop problem. European Journal of Operational Research, 193(1), 59-72.
  • Boysen, N., Fliedner, M., & Scholl, A. (2010). Scheduling inbound and outbound trucks at cross docking terminals. OR spectrum, 32(1), 135-161.
  • Vahdani, B., & Zandieh, M. (2010). Scheduling trucks in cross-docking systems: Robust meta-heuristics. Computers & Industrial Engineering, 58(1), 12-24.
  • Liao, T. W., Egbelu, P. J., & Chang, P. C. (2012). Two hybrid differential evolution algorithms for optimal inbound and outbound truck sequencing in cross docking operations. Applied Soft Computing, 12(11), 3683-3697.
  • Chen, F., & Song, K. (2009). Minimizing makespan in two-stage hybrid cross docking scheduling problem. Computers & Operations Research, 36(6), 2066-2073.
  • Van Belle, J., Valckenaers, P., Berghe, G. V., & Cattrysse, D. (2013). A tabu search approach to the truck scheduling problem with multiple docks and time windows. Computers & Industrial Engineering, 66(4), 818-826.
  • Bellanger, A., Hanafi, S., & Wilbaut, C. (2013). Three-stage hybrid-flowshop model for cross-docking. Computers & Operations Research, 40(4), 1109-1121.
  • [Gelareh, S., Glover, F., Guemri, O., Hanafi, S., Nduwayo, P., & Todosijević, R. (2020). A comparative study of formulations for a cross-dock door assignment problem. Omega, 91, 102015.
  • Correa Issi, G., Linfati, R., & Escobar, J. W. (2020). Mathematical optimization model for truck scheduling in a distribution center with a mixed service-mode dock area. Journal of Advanced Transportation, 2020.
  • Shahmardan, A., & Sajadieh, M. S. (2020). Truck scheduling in a multi-door cross-docking center with partial unloading–Reinforcement learning-based simulated annealing approaches. Computers & Industrial Engineering, 139, 106134.
  • Sayed, S. I., Contreras, I., Diaz, J. A., & Luna, D. E. (2020). Integrated cross-dock door assignment and truck scheduling with handling times. Top, 28(3), 705-727.
  • Mirzaei, E. & Mousavi, S. M. (2020). A Bi-Objective Mathematical Programming Model for Truck Scheduling Problem in A Cross-Dock System Considering the Sequencing and Outsourcing Of Products Under Interval-Valued Fuzzy Uncertainty Conditions. Journal of Industrial Engineering Research in Production Systems, 8(16), 137-157.
  • Buakum, D., & Wisittipanich, W. (2020). Stochastic internal task scheduling in cross docking using chance-constrained programming. International Journal of Management Science and Engineering Management, 15(4), 258-264.
  • Afsharpour, B., & Rbani, M. (2021). Open Vehicle Routing Problem with Cross-Docking and Split Deliveries. Journal of Industrial Engineering Research in Production Systems, 8(17), 311-319.
  • Azimi, F., Mousavi, S. M., & Rajabzadeh, M. (2019). A Grey Mathematical Programming Model to Salvage or Re-Commercialize Commodities in Reverse Logistics Management with Consideration of Cross Dock. Journal of Industrial Engineering Research in Production Systems, 7(14), 163-177.
  • Essghaier, F., Allaoui, H., & Goncalves, G. (2021). Truck to door assignment in a shared cross-dock under uncertainty. Expert Systems with Applications, 182, 114889.
  • Castellucci, P. B., Costa, A. M., & Toledo, F. (2021). Network scheduling problem with cross-docking and loading constraints. Computers & Operations Research, 132, 105271.
  • Resat, H. G., Berten, P., Kilek, Z., & Kalay, M. B. (2021). Design and Development of Robust Optimization Model for Sustainable Cross-Docking Systems: A Case Study in Electrical Devices Manufacturing Company. In Sustainable Packaging (pp. 203-224). Springer, Singapore.
  • Dulebenets, M. A. (2021). An Adaptive Polyploid Memetic Algorithm for scheduling trucks at a cross-docking terminal. Information Sciences, 565, 390-421.
  • Gaudioso, M., Monaco, M. F., & Sammarra, M. (2021). A Lagrangian heuristics for the truck scheduling problem in multi-door, multi-product Cross-Docking with constant processing time. Omega, 101, 102255.
  • Theophilus, O., Dulebenets, M. A., Pasha, J., Lau, Y. Y., Fathollahi-Fard, A. M., & Mazaheri, A. (2021). Truck scheduling optimization at a cold-chain cross-docking terminal with product perishability considerations. Computers & Industrial Engineering, 156, 107240.
  • Wu, G. H., Chen, Y. T., & Chen, K. H. (2022). Hybrid Algorithms for Inbound and Outbound Truck Scheduling in Cross-Docking Systems. Applied Sciences, 12(21), 10931.
  • Meidute-Kavaliauskiene, I., Sütütemiz, N., Yıldırım, F., Ghorbani, S., & Činčikaitė, R. (2022). Optimizing Multi Cross-Docking Systems with a Multi-Objective Green Location Routing Problem Considering Carbon Emission and Energy Consumption. Energies, 15(4), 1530.
  • Tavana, M., Kian, H., Nasr, A. K., Govindan, K., & Mina, H. (2022). A comprehensive framework for sustainable closed-loop supply chain network design. Journal of Cleaner Production, 332, 129777.
  • J. Lai, and C. L. Hwang, Fuzzy Mathematical Programming: Methods and Applications, Springer-Verlag (1992).
  • Jiménez, M. Arenas, A. Bilbao, M. V. Rodrı, Linear programming with fuzzy parameters: An interactive method resolution, European Journal of Operational Research, 177(3) (2007), 1599-609.
  • J. Zimmermann, Fuzzy programming and linear programming with several objective functions, Fuzzy sets and systems, 1(1) (1978), 45-55.
  • Ozgen, B. Gulsun, Combining possibilistic linear programming and fuzzy AHP for solving the multi-objective capacitated multi-facility location problem, Information Sciences, 268 (2014), 185-201.
  • J. Lai, C. L. Hwang, Possibilistic linear programming for managing interest rate risk, Fuzzy Sets and Systems, 54(2) (1993), 135-146.
  • H. Alavidoost, H. Babazadeh, S. T. Sayyari, An interactive fuzzy programming approach for bi-objective straight and U-shaped assembly line balancing problem, Applied soft computing, 40 (2016), 221-235.
نشریه پژوهش های مهندسی صنایع در سیستم های تولید
دوره 10، شماره 21
اسفند 1401
صفحه 119-133

فایل ها

هم رسانی

ارجاع به این مقاله

آمار