The Multi-Objective Locating Model for Cross-Docking Centers and Vehicle Routing Scheduling With Split Demands for Perishable Products

Document Type : Research Paper

Authors

1 Ph.D Candidate, Department of Industrial Management, Faculty of Administrative and Economics, University of Isfahan, Isfahan, Iran.

2 Associate Prof., Department of Industrial Management, Faculty of Administrative and Economics, University of Isfahan, Isfahan, Iran.

Abstract

Objective: This paper sought to develop a food supply chain model that integrates the operational decisions (vehicle routing and scheduling) with strategic decisions (cross-docking centers locating) in a hub network, considering life - real constraints and the perishable nature.
Methods: In this research, an integer Goal programming model for location, timing, and vehicle routing problems is proposed with the possibility of split demand for fresh items in which the impact of perishability is considered as the second objective besides the total cost. Accordingly, an augmented -constraint method was used to generate a Pareto optimal for these conflicting objectives. This model was implemented in CPLEX software, 20.1 version.
Results: Previous studies neither considered the perishable nature of the items in cross-docking locations nor the split delivery vehicle routing scheduling models. The most important aspect of innovation in this research was that the characteristics of split demand in improving the timing of vehicles were used and in addition to improving the cost function, the value of the second objective function (network accountability) was also increased dramatically. The results of sensitivity analysis on some parameters such as shelf life of products (SL), quality reduction point (QRP), and capacity of vehicles (Q), showed the efficiency of the proposed model.
Conclusion: Finally, the proposed model was utilized in random data and numerical results, and some managerial insights were provided. Comparing the results of the proposed model with the benchmark model in equal experimental conditions, the efficiency of the proposed model was confirmed. Cross-docking is nowadays used by many companies and industries and the provided model by this study can be applied especially for time-sensitive products.

Keywords


Agustina, D., Lee, C. K. M., & Piplani, R. (2014). Vehicle scheduling and routing at a cross docking center for food supply chains. Intern. Journal of Production Economics, 152, 29–41.
Apte, U. M., & Viswanathan, S. (2000). Effective Cross Docking for Improving Distribution Efficiencies. International Journal of Logistics Research and Applications, 3(3), 291–302.
Archetti, C., Bianchessi, N., & Speranza, M. G. (2011). A column generation approach for the split delivery vehicle routing problem. Networks, 58(4), 241–254.
Archetti, C., & Speranza, M. G. (2012). Vehicle routing problems with split deliveries. International Transactions in Operational Research, 19(1–2), 3–22.
Archetti, C., Speranza, M. G., & Hertz, A. (2006). A tabu search algorithm for the split delivery vehicle routing problem. Transportation Science, 40(1), 64–73.
Archetti, C., & Speranza, M. G. (2008). The split delivery vehicle routing problem: A survey. Operations Research/ Computer Science Interfaces Series, 43, 103–122.
Archetti, C., Bianchessi, N., & Speranza, M. G. (2014). Branch-and-cut algorithms for the split delivery vehicle routing problem. European Journal of Operational Research, 238(3), 685–698.
Belenguer, J. M., Martinez, M. C., & Mota, E. (2000). Lower bound for the split delivery vehicle routing problem. Operations Research, 48(5), 801–810.
Berbotto, L., García, S., & Nogales, F. J. (2013). A Randomized Granular Tabu Search heuristic for the split delivery vehicle routing problem. Annals of Operations Research 2013 222:1, 222(1), 153–173.
Bianchessi, N., & Irnich, S. (2019). Branch-and-Cut for the Split Delivery Vehicle Routing Problem with Time Windows. Transportation Science, 53(2), 442–462.
Bortolini, M., Faccio, M., Ferrari, E., Gamberi, M., & Pilati, F. (2016). Fresh food sustainable distribution: Cost, delivery time and carbon footprint three-objective optimization. Journal of Food Engineering, 174, 56–67.
Bruck, B. P., & Iori, M. (2017). Non-Elementary Formulations for Single Vehicle Routing Problems with Pickups and Deliveries. Operations Research, 65(6), 1597–1614.
Buakum, D., & Wisittipanich, W. (2019). A literature review and further research direction in cross-docking. Proceedings of the International Conference on Industrial Engineering and Operations Management, 2019(MAR), 471–481.
Buijs, P., Vis, I. F. A., & Carlo, H. J. (2014). Synchronization in cross-docking networks: A research classification and framework. In European Journal of Operational Research, 239(3), 593–608.
Davoudpour, H. (2014). Strategic Location: Case Studies in different industries. Amirkabir University of Technology (Tehran Polytechnic). (in Persian)
Dror, M., Laporte, G., & Trudeau, P. (1994). Vehicle routing with split deliveries. Discrete Applied Mathematics, 50(3), 239–254.
Dror, M., & Trudeau, P. (1989). Savings by Split Delivery Routing. Transportation Science, 23(2), 141–145.
Dror, M., & Trudeau, P. (1990). Split delivery routing. Naval Research Logistics (NRL), 37(3), 383–402.
Ganji, M., Kazemipoor, H., Hadji Molana, S. M., & Sajadi, S. M. (2020). Development of Integrated Multi-objective Green Supply Chain Scheduling Model: Production, Distribution and Heterogeneous Vehicle Routing with Customer Time Windows. Industrial Management Journal, 12(1), 47–81. (in Persian)
Gümüş, M., & Bookbinder, J. H. (2004). Cross-docking and its implications in location-distribution systems. Journal of Business Logistics, 25(2), 199–228.
Hajian, S., Afshar Kazemi, M. A., Seyed Hosseini, S. M., & Eshlaghy, A. (2019). Developing a Multi-Objective Model for Locating-Routing-Inventory Problem in a Multi-Period and Multi-Product Green Closed-Loop Supply Chain Network for Perishable Products. Industrial Management Journal, 11(1), 83–110. (in Persian)
Hasani-Goodarzi, A., & Tavakkoli-Moghaddam, R. (2012). Capacitated Vehicle Routing Problem for Multi-Product Cross- Docking with Split Deliveries and Pickups. Procedia - Social and Behavioral Sciences, 62, 1360–1365.
Hasani Goodarzi, A., & Zegordi, S. H. (2016). A location-routing problem for cross-docking networks: A biogeography-based optimization algorithm. Computers and Industrial Engineering, 102, 132–146.
Hasani Goodarzi, A., Tavakkoli-Moghaddam, R., & Amini, A. (2020). A new bi-objective vehicle routing-scheduling problem with cross-docking: Mathematical model and algorithms. Computers and Industrial Engineering, 149.
Hasani Goodarzi, A., Zegordi, S. H., Alpan, G., Nakhai Kamalabadi, I., & Husseinzadeh Kashan, A. (2021). Reliable cross-docking location problem under the risk of disruptions. In Operational Research (Vol. 21, Issue 3). Springer Berlin Heidelberg.
Hosseinabadi Rahmani, A. A., & Nad AliZade Chari, M. (2018). Vehicle routing problem (theories and aplications). Babol: New Technology.
Irnich, S., Schneider, M., & Vigo, D. (2014). Chapter 9: Four Variants of the Vehicle Routing Problem. MOS-SIAM Series on Optimization, 241–271.
Javanfar, E., Rezaeian, J., Shokofi, K., & Mahdavi, I. (2017). Multi product cross-docking location vehicle routing problem with capacity hetrogeneous vehicles and split pickup and delivery in multi level supply chain. Journal Transportation Engeneering, 603–627. (in Persian)
Jayaraman, V., & Ross, A. (2003). A simulated annealing methodology to distribution network design and management. European Journal of Operational Research, 144(3), 629–645.
Jelodari_Mamghani, E., & Setak, M. (2017). The bi-objective location-routing problem based on simultaneous pickup and delivery with soft time window. Journal of Optimization in Industrial Engineering, 22, 81–91.
Ladier, A.-L., & Alpan, G. (2016). Cross-docking operations : Current research versus industry practice $. Omega, 62, 145–162.
Moreno, L., De Aragão, M. P., & Uchoa, E. (2010). Improved lower bounds for the Split Delivery Vehicle Routing Problem. Operations Research Letters, 38(4), 302–306.
Mousavi, S. Meysam, & Tavakkoli-Moghaddam, R. (2013). A hybrid simulated annealing algorithm for location and routing scheduling problems with cross-docking in the supply chain. Journal of Manufacturing Systems, 32(2), 335–347.
Mousavi, S Meysam, Vahdani, B., Tavakkoli-moghaddam, R., & Hashemi, H. (2014). Location of cross-docking centers and vehicle routing scheduling under uncertainty : A fuzzy possibilistic – stochastic programming model. Applied Mathematical Modelling, 38, 2249–2264.
Mousavi, Seyed Meysam, Antuchevičienė, J., Zavadskas, E. K., Vahdani, B., & Hashemi, H. (2019). A new decision model for cross-docking center location in logistics networks under interval-valued intuitionistic fuzzy uncertainty. Transport, 34(1), 30–40.
Musa, R., Arnaout, J.-P., & Jung, H. (2010). Ant colony optimization algorithm to solve for the transportation problem of cross-docking network. Computers & Industrial Engineering, 59(1), 85–92.
Musavi, M. M., & Bozorgi-Amiri, A. (2017). A multi-objective sustainable hub location-scheduling problem for perishable food supply chain. Computers and Industrial Engineering, 113, 766–778.
Najjarbashi, A., & Lim, G. (2015). Using Augmented ɛ-constraint Method for Solving a Multi-objective Operating Theater Scheduling. Procedia Manufacturing, 3(Ahfe), 4448–4455.
Ozbaygin, G., Karasan, O., & Yaman, H. (2018). New exact solution approaches for the split delivery vehicle routing problem. EURO Journal on Computational Optimization, 6(1), 85–115.
Qiu, M., Fu, Z., Eglese, R., & Tang, Q. (2018). A Tabu Search algorithm for the vehicle routing problem with discrete split deliveries and pickups. Computers and Operations Research, 100, 102–116.
Rahbari, A., Nasiri, M. M., Werner, F., Musavi, M. M., & Jolai, F. (2019). The vehicle routing and scheduling problem with cross-docking for perishable products under uncertainty: Two robust bi-objective models. Applied Mathematical Modelling, 70, 605–625.
Rajappa, G. P., Wilck, J. H., & Bell, J. E. (2016). An Ant Colony Optimization and Hybrid Metaheuristics Algorithm to Solve the Split Delivery Vehicle Routing Problem. International Journal of Applied Industrial Engineering, 3(1), 55–73.
 
Ross, A., & Jayaraman, V. (2008). An evaluation of new heuristics for the location of cross-docks distribution centers in supply chain network design. Computers & Industrial Engineering, 55, 64–79. https://doi.org/10.1016/j.cie.2007.12.001
Sabouhi, F., & Ali Bozorgi Amiri. (2019). A bi-objective mathematical model for emergency evacuation considering heterogeneous fleet of vehicles. Journal of Modern Research in Decision Making, 4(1), 119–137. (in Persian)
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 and Industrial Engineering, 157(March 2020), 107299.
Shi, J., Zhang, J., Wang, K., & Fang, X. (2018). Particle Swarm Optimization for Split Delivery Vehicle Routing Problem.
Shuib, A., & Fatthi, W. N. A. W. A. (2012). A Review on Quantitative Approaches for Dock Door Assignment in Cross-Docking. International Journal on Advanced Science, Engineering and Information Technology, 2(5), 370.
Stephan, K., & Boysen, N. (2011). Cross-docking. Journal of Management Control, 22(1), 129–137.
Sung, C. S., & Song, S. H. (2003). Integrated service network design for a cross-docking supply chain network. Journal of the Operational Research Society, 54(12), 1283–1295.
Sung, C. S., & Yang, W. (2017). An exact algorithm for a cross-docking supply chain network design problem. Journal of the Operational Research Society, 5682.
Tavakkoli-Moghaddam, R., Safaei, N., Kah, M. M. O., & Rabbani, M. (2007). A New Capacitated Vehicle Routing Problem with Split Service for Minimizing Fleet Cost by Simulated Annealing. Journal of the Franklin Institute, 344(5), 406–425.
Theophilus, O., Dulebenets, M. A., Pasha, J., Abioye, O. F., & Kavoosi, M. (2019). Truck scheduling at cross-docking terminals: A follow-up state-of-the-art review. Sustainability (Switzerland), 11(19).
Tikani, H., Mostafa Setak, & Kebria, Z. S. (2020). Modeling And Solving The Locating-Routing Problem For Perishable Products In Multigraphs Considering Vehicle Pollution And Warehouses Failure. Journal of Industrial Engineering Research in Production Systems, 8(16), 171–183. (in Persian)
Van Belle, J., Valckenaers, P., & Cattrysse, D. (2012). Cross-docking: State of the art. Omega, 40(6), 827–846.
Webb, M. H. J. (1968). Cost Functions in the Location of Depots for Multiple-Delivery Journeys. Journal of the Operational Research Society, 19(3), 311–320.
Yu, V. F., Normasari, N. M. E., & Chen, W. H. (2021). Location-routing problem with time-dependent demands. Computers and Industrial Engineering, 151(2), 106936.