A Hybrid Methodology based on heuristic algorithms for a production distribution system with routing decisions

Authors

  • Mohamed Bensakhria University of Batna 2, Fesdis, Algeria
  • Samir Abdelhamid University of Batna 2, Fesdis, Algeria

DOI:

https://doi.org/10.5937/bizinfo2102001B

Keywords:

optimization, production-distribution systems, routing decision, mathematical modeling, genetic algorithms

Abstract

In this paper, we address the integration of a two-level supply chain with multiple items. This two-level production-distribution system features a capacitated production facility supplying several retailers located in the same region. If production does occur, this process incurs a fixed setup cost and unit production costs. Besides, deliveries are made from the plant to the retailers by a limited number of capacitated vehicles, routing costs incurred. This work aims to implement a minimization solution that reduces the total costs in both the production facility and retailers. The methodology adopted based on a hybrid heuristic, greedy and genetic algorithm uses strong formulation to provide a suitable solution of a guaranteed quality that is as good or better than those provided by the MIP optimizer. The results demonstrate that the proposed heuristics are effective and performs impressively in terms of computational efficiency and solution quality.

Downloads

Download data is not yet available.

References

Ahmadizar, F., Zeynivand, M., & Arkat, J. (2015). Two-level vehicle routing with cross-docking in a three-echelon supply chain: A genetic algorithm approach. Applied Mathematical Modelling, 39(22), 7065–7081. https://doi.org/10.1016/j.apm.2015.03.005

Archetti, C., Bertazzi, L., Laporte, G., & Speranza, M. G. (2007). A Branch-and-Cut Algorithm for a Vendor-Managed Inventory-Routing Problem. Transportation Science, 41(3), 382–391. https://doi.org/10.1287/trsc.1060.0188

Archetti, C., Bertazzi, L., Paletta, G., & Speranza, M. G. (2011). Analysis of the maximum level policy in a production-distribution system. Computers & Operations Research, 38(12), 1731–1746. https://doi.org/10.1016/j.cor.2011.03.002

Arkin, E., Joneja, D., & Roundy, R. (1989). Computational complexity of uncapacitated multi-echelon production planning problems. Operations Research Letters, 8(2), 61–66. https://doi.org/10.1016/0167-6377(89)90001-1

Axsäter, S. (2001). A Note on Stock Replenishment and Shipment Scheduling for Vendor-Managed Inventory Systems. Management Science, 47(9), 1306–1310. https://doi.org/10.1287/mnsc.47.9.1306.9782

Bard, J. F., & Nananukul, N. (2009). Heuristics for a multiperiod inventory routing problem with production decisions. Computers & Industrial Engineering, 57(3), 713–723. https://doi.org/10.1016/j.cie.2009.01.020

Bell, W. J., Dalberto, L. M., Fisher, M. L., Greenfield, A. J., Jaikumar, R., Kedia, P., Mack, R. G., & Prutzman, P. J. (1983). Improving the Distribution of Industrial Gases with an On-Line Computerized Routing and Scheduling Optimizer. Interfaces, 13(6), 4–23. https://doi.org/10.1287/inte.13.6.4

Bhatnagar, R., Chandra, P., & Goyal, S. K. (1993). Models for multi-plant coordination. European Journal of Operational Research, 67(2), 141–160. https://doi.org/10.1016/0377-2217(93)90058-u

Bilgen, B., & Günther, H. O. (2009). Integrated production and distribution planning in the fast moving consumer goods industry: a block planning application. OR Spectrum, 32(4), 927–955. https://doi.org/10.1007/s00291-009-0177-4

Boudia, M., & Prins, C. (2009). A memetic algorithm with dynamic population management for an integrated production–distribution problem. European Journal of Operational Research, 195(3), 703–715. https://doi.org/10.1016/j.ejor.2007.07.034

Cárdenas-Barrón, L. E., González-Velarde, J. L., Treviño-Garza, G., & Garza-Nuñez, D. (2019). Heuristic algorithm based on reduce and optimize approach for a selective and periodic inventory routing problem in a waste vegetable oil collection environment. International Journal of Production Economics, 211, 44–59. https://doi.org/10.1016/j.ijpe.2019.01.026

Chandra, P., & Fisher, M. L. (1994). Coordination of production and distribution planning. European Journal of Operational Research, 72(3), 503–517. https://doi.org/10.1016/0377-2217(94)90419-7

Chang, K. H., & Lu, Y. S. (2011). Inventory management in a base-stock controlled serial production system with finite storage space. Mathematical and Computer Modelling, 54(11–12), 2750–2759. https://doi.org/10.1016/j.mcm.2011.06.063

Chitsaz, M., Cordeau, J. F., & Jans, R. (2019). A Unified Decomposition Matheuristic for Assembly, Production, and Inventory Routing. INFORMS Journal on Computing, 31(1), 134–152. https://doi.org/10.1287/ijoc.2018.0817

Duc, D. N., & Nananukul, N. (2020). A Hybrid Methodology Based on Machine Learning for a Supply Chain Optimization Problem. Journal of Physics: Conference Series, 1624, 052022. https://doi.org/10.1088/1742-6596/1624/5/052022

Federgruen, A., & Tzur, M. (1999). Time-partitioning heuristics: Application to one warehouse, multiitem, multiretailer lot-sizing problems. Naval Research Logistics, 46(5), 463–486. https://doi.org/10.1002/(SICI)1520-6750(199908)46:5%3C463::AID-NAV2%3E3.0.CO;2-S

Gen, M., & Syarif, A. (2005). Hybrid genetic algorithm for multi-time period production/distribution planning. Computers & Industrial Engineering, 48(4), 799–809. https://doi.org/10.1016/j.cie.2004.12.012

Geoffrion, A. M., & Powers, R. F. (1995). Twenty Years of Strategic Distribution System Design: An Evolutionary Perspective. Interfaces, 25(5), 105–127. https://doi.org/10.1287/inte.25.5.105

Golden, B., Assad, A., Levy, L., & Gheysens, F. (1984). The fleet size and mix vehicle routing problem. Computers & Operations Research, 11(1), 49–66. https://doi.org/10.1016/0305-0548(84)90007-8

Gong, W., & Fu, Z. (2010, December). ABC-ACO for perishable food vehicle routing problem with time windows. In 2010 international conference on computational and information sciences (pp. 1261-1264). IEEE. https://doi.org/10.1109/ICCIS.2010.311

Hemmati, M., & Smith, J. C. (2016). A mixed-integer bilevel programming approach for a competitive prioritized set covering problem. Discrete Optimization, 20, 105–134. https://doi.org/10.1016/j.disopt.2016.04.001

Iassinovskaia, G., Limbourg, S., & Riane, F. (2017). The inventory-routing problem of returnable transport items with time windows and simultaneous pickup and delivery in closed-loop supply chains. International Journal of Production Economics, 183, 570–582. https://doi.org/10.1016/j.ijpe.2016.06.024

Infante, D., Paletta, G., & Vocaturo, F. (2009). A ship-truck intermodal transportation problem. Maritime Economics & Logistics, 11(3), 247–259. https://doi.org/10.1057/mel.2009.6

Jie, L., Sava, A., & Xie, X. (2005). Performance Evaluation and Optimization of a Two-Stage Production-Distribution System with Batch Orders and Finite Transportation Time. IFAC Proceedings Volumes, 38(1), 331–336. https://doi.org/10.3182/20050703-6-cz-1902.01477

Lee, C. Y., ÇEtinkaya, S., & Jaruphongsa, W. (2003). A Dynamic Model for Inventory Lot Sizing and Outbound Shipment Scheduling at a Third-Party Warehouse. Operations Research, 51(5), 735–747. https://doi.org/10.1287/opre.51.5.735.16752

Melo, R. A., & Wolsey, L. A. (2012). MIP formulations and heuristics for two-level production-transportation problems. Computers & Operations Research, 39(11), 2776–2786. https://doi.org/10.1016/j.cor.2012.02.011

Min, H., & Zhou, G. (2002). Supply chain modeling: past, present and future. Computers & Industrial Engineering, 43(1–2), 231–249. https://doi.org/10.1016/s0360-8352(02)00066-9

Miranda, P. L., Morabito, R., & Ferreira, D. (2019). Mixed integer formulations for a coupled lot-scheduling and vehicle routing problem in furniture settings. INFOR: Information Systems and Operational Research, 57(4), 563–596. https://doi.org/10.1080/03155986.2019.1575686

Patiño Chirva, J. A., Daza Cruz, Y. X., & Lopez-Santana, E. R. (2016). A Hybrid Mixed-Integer Optimization and Clustering Approach to Selective Collection Services Problem of Domestic SolidWaste. Ingeniería, 21(2), 235-257. https://doi.org/10.14483/udistrital.jour.reving.2016.2.a09

Rafie-Majd, Z., Pasandideh, S. H. R., & Naderi, B. (2018). Modelling and solving the integrated inventory-location-routing problem in a multi-period and multi-perishable product supply chain with uncertainty: Lagrangian relaxation algorithm. Computers & Chemical Engineering, 109, 9–22. https://doi.org/10.1016/j.compchemeng.2017.10.013

Rizk, N., Martel, A., & Ramudhin, A. (2006). A Lagrangean relaxation algorithm for multi-item lot-sizing problems with joint piecewise linear resource costs. International Journal of Production Economics, 102(2), 344–357. https://doi.org/10.1016/j.ijpe.2005.02.015

Sun, L., Rangarajan, A., Karwan, M. H., & Pinto, J. M. (2015). Transportation cost allocation on a fixed route. Computers & Industrial Engineering, 83, 61–73. https://doi.org/10.1016/j.cie.2015.02.004

Swenseth, S. R., & Godfrey, M. R. (2002). Incorporating transportation costs into inventory replenishment decisions. International Journal of Production Economics, 77(2), 113–130. https://doi.org/10.1016/S0925-5273(01)00230-4

Tarantilis, C. D., & Kiranoudis, C. T. (2001). A meta-heuristic algorithm for the efficient distribution of perishable foods. Journal of food Engineering, 50(1), 1-9. https://doi.org/10.1016/S0260-8774(00)00187-4

Thomas, D. J., & Griffin, P. M. (1996). Coordinated supply chain management. European Journal of Operational Research, 94(1), 1–15. https://doi.org/10.1016/0377-2217(96)00098-7

Wang, Y., Ma, X., Xu, M., Wang, L., Wang, Y., & Liu, Y. (2015). A Methodology to Exploit Profit Allocation in Logistics Joint Distribution Network Optimization. Mathematical Problems in Engineering, 2015, 1–15. https://doi.org/10.1155/2015/827021

Xu, Y., & Jiang, W. (2014). An Improved Variable Neighborhood Search Algorithm for Multi Depot Heterogeneous Vehicle Routing Problem based on Hybrid Operators. International Journal of Control and Automation, 7(3), 299–316. https://doi.org/10.14257/ijca.2014.7.3.29

Downloads

Published

2021-12-31

How to Cite

Bensakhria, M., & Abdelhamid, S. (2021). A Hybrid Methodology based on heuristic algorithms for a production distribution system with routing decisions. BizInfo (Blace) Journal of Economics, Management and Informatics, 12(2), 1–22. https://doi.org/10.5937/bizinfo2102001B