The Impacts of VRP Model to Reduce Spare Parts Distribution Cost between Roadside assistance Cars

Document Type : Research Paper

Authors

1 PhD student, Faculty of Industrial Engineering, Sharif University of Technology, Tehran, Iran

2 Professor, Department of Industrial Engineering, Faculty of Industrial Engineering, Sharif University of Technology, Tehran, Iran

3 Associate Professor, Department of Industrial Engineering, Faculty of Industrial Engineering, Sharif University of Technology, Tehran, Iran

Abstract

After-sale service is one of the most important competitive factors in the automotive industry. Roadside assistance is a crucial function that affects customers’ satisfaction. Subsequently, having a cost-effective spare part supply strategy for Roadside Assistance Vehicles (RAV) is vital to sustaining the competitiveness and profitability of every car manufacturer. A proper manner to supply spare parts for RAV has a significant effect on roadside assistance costs. In this article, we suggested a direct spare part supply strategy instead of the actual practice of delivering spare parts at the warehouses. By applying the VRP modeling, showed that this new strategy decreases the supply costs of spare parts

Keywords


 
[1]        OICA, “SALES OF NEW VEHICLES 2005-2019”, (2020). [online], Available: http://www.oica.net/.
[2]        P. Gaiardelli, N. Saccani and L. Songini, (2007). “Performance measurement of the after-sales service network—Evidence from the automotive industry”, Computers in Industry, Vol. 2007, No. 58, p. 698–708.
[3]        R. G. Bundschuh and M. D. Theodore, (2003). “How to make after-sales services pay off”, McKinsey Quarterly, Vol. 2003, No. 4, pp. 116-127.
[4]        G. Dantzig and J. Ramser, (1959). “The truck dispatching Problem,” Management Science, pp. 80-91.
[5]        P. Toth and D. Vigo, (2014). “Vehicle routing problems, methods, and applications”, Society for Industrial and Applied Mathematics.
[6]        G. Laporte, H. Mercure and Y. Nober,(1986). “An exact algorithm for the asymmetrical capacitated vehicle routing problem”, NETWORKS, Vol. 16, No. 1, pp. 33-46.
[7]        G. Laporte, F. V. Louveaux and L. V. Hamme, (2003). “An integer  L-shaped algorithm for the  capacitated vehicle routing problem with stochastic demands”, Operations Research, Vol. 50, No. 3, p. 415–423.
[8]        G. Laporte and M. Desrochers, (1984). “Two exact algorithms for the distance-constrained vehicle routing problem”, Networks, Vol. 14, No. 1, pp. 161-172.
[9]        G. Kim, Y. S. Ong, C. K. Heng, P. S. Tan and N. A. Zhang, (2015). “City vehicle routing problem (City VRP): A review”, IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, Vol. 16, No. 4, pp. 1654-1666.
[10]      A. W. J. Kolen, A. H. G. Rinnooy Kan and H. W. J. M. Trienekens, (1987). “Vehicle routing with time windows”, Operations Research, Vol. 35, No. 2, pp. 266-273.
[11]      M. Schneider, A. Stenger and D. Goeke, (2014). “The electric vehicle-routing problem with time windows and recharging stations”, Transportation Science, Vol. 48, No. 4, pp. 500-520.
[12]      M. Kargari and M. M. Sepehri, (2012). “Stores clustering using a data mining approach for distributing automotive spare-parts to reduce transportation costs”, Expert Systems with Applications, Vol. 39, No. 5, pp. 4740-4748.
[13]      J. C. García-Benito and M. L. Martín-Peña, (2021). “A redistribution model with minimum backorders of spare parts: A proposal for the defence sector”, European Journal of Operational Research, Vol. 291, No. 1, pp. 178-193.
[14]      A. Sleptchenko, M. C. van der Heijden and A. van Harten, (2005).  “Using repair priorities to reduce stock investment in spare part networks”, European Journal of Operational Research, Vol. 163, No. 3, pp. 733-750, 2005.
[15]      A. M. Campbell, D. Vandenbussche and W. Hermann, (2008). “Routing for Relief Efforts”, Transportation Science, Vol. 42, No. 2, p. 127–145.
[16]      S. M. R. Davoodi and A. Goli, (2019). “An integrated disaster relief model based on covering tour using hybrid Benders decomposition and variable neighborhood search: Application in the Iranian context”, Computers & Industrial Engineering, No. 130, p. 370–380.
[17]      M.-S. Chang, Y.-L. Tseng and J.-W. Chen, (2007) “A scenario planning approach for the flood emergency logistics preparation problem under uncertainty”, Transportation  Research Part E, No. 43, p. 737–754.
[18]      L. C. Coelho, J.-F. Cordeau and G. Laporte, (2014).  “Thirty Years of Inventory Routing”, Transportation Science, Vol. 48, No. 1, pp. 1-19.
[19]      S. Anily, (1994). “The general multi-retailer EOQ problem with vehicle routing costs”, European Journal of Operational Research, No. 79, pp. 451-473.
[20]      J. F. Bard, (1998). “A Decomposition Approach to the Inventory Routing Problem with Satellite Facilities”, Transportation Science, Vol. 32, No. 2, pp. 189-203.
[21]      A. Prutsakul, (1998). “Integrated inventory problem and vehicle routing problem in one warehouse and multi-retailer distribution system”, Texas Tech University.
[22]      A. M. Campbell and M. W. P. Savelsbergh, (2004). “A Decomposition Approach for the Inventory-Routing Problem”, Transportation Science, Vol. 38, No. 4, pp. 488-502, 2004.
[23]      A. J. Kleywegt, V. S. Nori and M. W. P. Savelsbergh, (2004). “Dynamic Programming Approximations for a Stochastic Inventory Routing Problem”, Transportation Science, Vol. 38, No. 1, pp. 42-70.
[24] ف. جعفرخان و س. یعقوبی، (1395) “ارائه مدل ریاضی استوار و الگوریتم حل ابتکاری برای مسأله یکپارچه تولید-مسیریابی-موجودی محصولات فاسد شدنی با انتقال جانبی،” نشریه پژوهشهای مهندسی صنایع در سیستم‌های تولید، جلد 4، شماره 2، صفحه  195-211. 
[25] م. محجوب‌نیا، ن. دبیری و ع. بزرگی امیری، (1396) “ارائه مدل جدید مکان‌یابی-مسیریابی-موجودی سبز تحت عدم قطعیت”، نشریه پژوهشهای مهندسی صنایع در سیستم‌های تولید، جلد 5، شماره 1، صفحه 99-115.
[26]      A. Ekici, O. Ö. Özener and G. Kuyzu, (2015). “Cyclic Delivery Schedules for an Inventory Routing Problem”, Transportation Science, Vol. 49, No. 4, pp. 817-829.
[27]      G. Widyadana and T. Irohara, (2019) “Modelling multi-tour inventory routing problem for deteriorating items with time windows”, Scientia Iranica E, Vol. 26, No. 2, p. 932-941.
[28]      L. C. Coelho, A. De Maio and D. Laganà, (2020). “A variable MIP neighborhood descent for the multi-attribute inventory routing problem”, Transportation Research Part E, Vol. 144, No. 1, p. 102137.