IJE TRANSACTIONS C: Aspects Vol. 31, No. 9 (September 2018) 1568-1574    Article in Press

PDF URL: http://www.ije.ir/Vol31/No9/C/13-2904.pdf  
downloaded Downloaded: 53   viewed Viewed: 444

A. Roostaei and I. Nakhai Kamal Abadi
( Received: December 27, 2017 – Accepted in Revised Form: April 26, 2018 )

Abstract    Generally, the inventory routing problem occurs in a supply chain where customers consider the supplier responsible for inventory replenishment. In this situation, the supplier finds the answer to questions regarding the time and quantity of delivery to the customer as well as the sequence of customers in the routes. Considering the effect of production decisions on answering these questions, the present paper examines the integrated decision making on production, routing and inventory in a two-echelon supply chain composed of a manufacturer and multiple retailers. Transshipment, as a policy in supply chain logistic which increase integration and decrease inventory cost, is also allowed between retailers. The mathematical formulation for the problem is developed and an adaptive large neighborhood search heuristic is proposed to solve this complicated problem. The results of numerical experiments showed that the solutions yielded by the heuristic method have high efficiency.


Keywords    Inventory Routing, Production Planning, Transshipment between Retailers, Adaptive Large Neighborhood Search



عموماً مسأله مسیریابی موجودی در شرایطی در زنجیره‌های تأمین رخ می‌دهد که در آن مشتریان مسئولیت بازپرسازی موجودی را به تأمین‌کننده می‌سپارند. در این شرایط تأمین‌کننده برای پرسش‌هایی مانند آن که زمان و میزان تحویل کالا به مشتری و همچنین توالی مشتریان در مسیرها چگونه باشد، پاسخ مناسب می‌یابد. با توجه به نقش تصمیمات مربوط به تولید در ارائه پاسخ به این پرسش‌ها، مقاله حاضر به بررسی تصمیم‌گیری یکپارچه در خصوص تولید، مسیریابی و موجودی در یک زنجیره تأمین دوسطحی که از یک تولیدکننده و تعدادی خرده‌فروش تشکیل شده است می‌پردازد. همچنین امکان جابجایی موجودی (تِرَنس‌شیپمِنت) بین خرده‌فروشان به عنوان یکی از ابزارهای مطرح در لجستیک زنجیره تأمین، که با هدف افزایش یکپارچگی و کاهش هزینه‌ها در مدیریت موجودی به کار برده می‌شود، مجاز درنظر گرفته شده است. در این تحقیق ابتدا مدل ریاضی مسأله ارائه شده و سپس یک روش ابتکاری در چارچوب روش جستجوی همسایگی بزرگ انطباقی توسعه یافته است. نتایج حاصل از آزمایشات عددی نشان می‌دهد جواب‌های ایجاد شده توسط روش ابتکاری از کارایی بالایی برخوردار هستند.


1. Bell, W. J., Dalberto, L., M. Fisher, M. L., Greenfield, A.J., Jaikumar, R., Kedia, P., Mack, R. G., & Prutzman, P.J. “Improving the distribution of industrial gases with an on-line computerized routing and scheduling optimizer”, Interfaces, Vol. 13, (1983), 4-23.
2. Andersson, H., Hoff, A., Christiansen, M., Hasle, G., & Lokketangen, A., “Industrial aspects and literature survey: Combined inventory management and routing”, Computers & Operations Research, Vol. 37, No. 9, (2010), 1515-1536.
3. Coelho, L., Cordeau J.F, Laporte G., “Thirty Years of Inventory Routing”, Transportation Science, Vol. 48, (2014), 1-19.
4. Ghorbani, A., Akbari Jokar, M., “A hybrid imperialist competitive-simulated annealing algorithm for a multisource multi-product location-routing-inventory problem”, Computers & Industrial Engineering, Vol. 101, (2016), pp. 116-127.
5. Cordeau, J., Laganà, D., Musmanno, R., Vocaturo, F., “A decomposition-based heuristic for the multiple-product inventory-routing problem”, Computers & Operations Research, Vol. 55, (2015), 153-166.
6. Etebari, F., Dabiri, N., “A hybrid heuristic for the inventory routing problem under dynamic regional pricing”, Computers & Chemical Engineering, Vol. 95, (2016), 231-239.
7. M. Moubed, M., Mehrjerdi, Y.Y., “A Hybrid Dynamic Programming for Inventory Routing Problem in Collaborative Reverse Supply Chains”, International Journal of Engineering, Transactions A: Basics, (2016), Vol. 29, No. 10, 1412-1420
8. Al-Ameri, T.A., Shah, N., & Papageorgiou, L.G., “Optimization of vendor-managed inventory systems in a rolling horizon framework”, Computers & Industrial Engineering, Vol. 54, (2008), 1019–1047.
9. Bard, J., & Nananukul, N., “A branch-and-price algorithm for an integrated production and inventory routing problem”, Computers & Industrial Engineering, Vol. 37, No. 12, (2010), 2202-2217.
10. Adulyasak, Y., Cordeau, J., Jans, R., “The production routing problem: A review of formulations and solution algorithms”, Computers & Operations Research, Vol. 55, (2016), 141-152.
11. Diaz, M., Peidro, D., Mula, J., “A review of tactical optimization models for integrated production and transport routing planning decisions” Computers & Industrial Engineering, Vol. 88, (2015), 518-535.
12. Paterson C, Kiesmller G, Teunter R, Glazebrook K., “Inventory models with lateral transshipments: a review”, European Journal of Operational Research, Vol. 210, No. 2, (2011), 125–136.
13. Mercer, A., Tao, X., “Alternative inventory and distribution policies of a food manufacturer”, Journal of the Operational Research Society, Vol. 47, (1996), 755-765.
14. Alvarez, E.M., Van Der Heijden, M.C., Vliegen, I.M.H., Zijm, W.H.M., “Service differentiation through selective lateral transshipments”, European Journal of Operational Research, Vol. 237, (2014), 824–835.
15. Turan, B., Minner, S., Hartl, R., “A VNS approach to multi-location inventory redistribution with vehicle routing”, Computers & Operations Research, No. 78, (2017), 526-536.
16. Coelho, L.C., Cordeau, J.F., Laporte, G., “The inventory-routing problem with transshipment”, Computers and Operations Research, No. 39, (2011), 2537-2548.
17. Tiacci, L., Saetta, S., “Reducing the mean supply delay of spare parts using lateral transshipments policies”, International Journal of Production Economics, No. 133, (2011), 182-191.
18. Nonas LM, Jornsten K., “Optimal solution in the multi-location inventory system with transshipments”, Journal of Mathematical Modeling and Algorithms, No. 6(1), (2007), 47–75.
19. Archetti, C., Bertazzi, L., Hertz, A., & Speranza, M.G., “A hybrid heuristic for an inventory routing problem”, INFORMS Journal on Computing, No. 24(1), (2012), 101-116.
20. Lenstra, J. K., & Rinnooy, K. A. H. G., “Complexity of vehicle routing and scheduling problems”, Networks, No. 11, (1981), 221–227.
21. Shaw, P., “Using constraint programming and local search methods to solve vehicle routing problems”, Principles and Practice of Constraint Programming, Lecture Notes in Computer Science, Vol. 1520, (1998), 417–431.
22. Ropke S, Pisinger D., “An adaptive large neighborhood search heuristic for the pickup and delivery problem with time windows”, Transportation Science, Vol. 40, No. 4, (2006), 455-72.
23. Aksen, D., Kaya, O., Salman, F., Tuncel, O., “An adaptive large neighborhood search algorithm for a selective and periodic inventory routing problem”, European Journal of Operational Research, Vol. 239, (2014), 413-426. 

Download PDF 

International Journal of Engineering
E-mail: office@ije.ir
Web Site: http://www.ije.ir