An Integrated Production-distribution Problem of Perishable Items with Dynamic Pricing Consideration in a Three-echelon Supply Chain

Document Type : Original Article

Author

Department of Industrial Engineering, Faculty of Engineering Management, Kermanshah University of Technology, Kermanshah, Iran

Abstract

The importance of employing appropriate pricing strategies for perishable products within the supply chain cannot be overstated. Pricing is a cross-functional driver of each supply chain, playing an irrefutable role in the success and profitability of the supply chain alongside other factors such as inventory and production policies which has been investigated in this research. The research emphasizes the significant role of pricing in profitability, along with the interplay of production policies and inventory control, highlighting their collective influence on financial outcomes, the subject of dynamic pricing within a multi-product, multi-period problem in a three-level supply chain with perishable products has garnered relatively limited attention. The study focuses on optimizing an integrated production-distribution system with multiple producers and distribution centers serving specific customer groups. Direct shipments between production centers, distribution centers, and retailers are optimized using a vehicle routing problem approach. A mixed-integer programming model is formulated, and a genetic algorithm-based metaheuristic approach is proposed. The BARON solver was initially used to solve two simplified test problems, with results compared to a self-designed genetic algorithm implemented in C#. After confirming the efficiency and effectiveness of our genetic algorithm (GA), the investigation is further extended to encompass five distinct problems, each comprising nine sub-problems. The GA demonstrates its power and adaptability by providing high-quality solutions efficiently within a reasonable computational time.

Keywords

Main Subjects

References

  1. Moosavi, J., Fathollahi-Fard, A.M. and Dulebenets, M.A., "Supply chain disruption during the covid-19 pandemic: Recognizing potential disruption management strategies", International Journal of Disaster Risk Reduction, Vol. 75, (2022), 102983. https://doi.org/10.1016/j.ijdrr.2022.102983
  2. Simonetto, M., Sgarbossa, F., Battini, D. and Govindan, K., "Closed loop supply chains 4.0: From risks to benefits through advanced technologies. A literature review and research agenda", International Journal of Production Economics, (2022), 108582. https://doi.org/10.1016/j.ijpe.2022.108582
  3. Berlin, D., Feldmann, A. and Nuur, C., "The relatedness of open-and closed-loop supply chains in the context of the circular economy; framing a continuum", Cleaner Logistics and Supply Chain, Vol. 4, (2022), 100048. https://doi.org/10.1016/j.clscn.2022.100048
  4. Asghari, M., Afshari, H., Mirzapour Al-e-hashem, S.M.J., Fathollahi-Fard, A.M. and Dulebenets, M.A., "Pricing and advertising decisions in a direct-sales closed-loop supply chain", Computers & Industrial Engineering, Vol. 171, (2022), 108439. https://doi.org/10.1016/j.cie.2022.108439. https://www.sciencedirect.com/science/article/pii/S0360835222004740
  5. Fathollahi-Fard, A., Dulebenets, M., Hajiaghaei-Keshteli, M., Tavakkoli-Moghaddam, R., Safaeian, M. and Mirzahosseinian, H., "Two hybrid meta-heuristic algorithms for a dual-channel closed-loop supply chain network design problem in the tire industry under uncertainty", Advanced Engineering Informatics, Vol. 50, (2021), 101418. doi: 10.1016/j.aei.2021.101418.
  6. Chopra, S. and Meindl, P., "Supply chain management: Strategy, planning, and operation, Pearson, (2016).
  7. Farahani, R.Z., Rezapour, S., Drezner, T. and Fallah, S., "Competitive supply chain network design: An overview of classifications, models, solution techniques and applications", Omega, Vol. 45, (2014), 92-118. https://doi.org/10.1016/j.omega.2013.08.006
  8. Bilgen, B. and Günther, H.O., "Integrated production and distribution planning in the fast moving consumer goods industry: A block planning application", OR Spectrum, Vol. 32, No. 4, (2010), 927-955. doi: 10.1007/s00291-009-0177-4.
  9. Cóccola, M.E., Zamarripa, M., Méndez, C.A. and Espuña, A., "Toward integrated production and distribution management in multi-echelon supply chains", Computers & Chemical Engineering, Vol. 57, (2013), 78-94. https://doi.org/10.1016/j.compchemeng.2013.01.004.
  10. Nasiri, G.R., Zolfaghari, R. and Davoudpour, H., "An integrated supply chain production–distribution planning with stochastic demands", Computers & Industrial Engineering, Vol. 77, (2014), 35-45. doi: https://doi.org/10.1016/j.cie.2014.08.005.
  11. Marchetti, P.A., Gupta, V., Grossmann, I.E., Cook, L., Valton, P.-M., Singh, T., Li, T. and André, J., "Simultaneous production and distribution of industrial gas supply-chains", Computers & Chemical Engineering, Vol. 69, (2014), 39-58. https://doi.org/10.1016/j.compchemeng.2014.06.010.
  12. Sy, C., "A policy development model for reducing bullwhips in hybrid production-distribution systems", International Journal of Production Economics, Vol. 190, (2017), 67-79. https://doi.org/10.1016/j.ijpe.2016.09.005
  13. Devapriya, P., Ferrell, W. and Geismar, N., "Integrated production and distribution scheduling with a perishable product", European Journal of Operational Research, Vol. 259, No. 3, (2017), 906-916. https://doi.org/10.1016/j.ejor.2016.09.019
  14. Li, M. and Wang, Z., "An integrated robust replenishment/production/distribution policy under inventory inaccuracy", International Journal of Production Research, Vol. 56, No. 12, (2018), 4115-4131. doi: 10.1080/00207543.2018.1444808.
  15. Roostaei, A. and Nakhai Kamal Abadi, I., "Considering production planning in the multi-period inventory routing problem with transshipment between retailers", International Journal of Engineering, Transaction C: Aspects, Vol. 31, No. 9, (2018), 1568-1574. https://www.ije.ir/article_73294_56d823c2a4725045279477cd326ca693.pdf
  16. Izadi, L., Ahmadizar, F. and Arkat, J., "A hybrid genetic algorithm for integrated production and distribution scheduling problem with outsourcing allowed", International Journal of Engineering, Transaction B: Applications, Vol. 33, No. 11, (2020), 2285-2298. doi: 10.5829/ije.2020.33.11b.19.
  17. Aazami, A. and Saidi-Mehrabad, M., "A production and distribution planning of perishable products with a fixed lifetime under vertical competition in the seller-buyer systems: A real-world application", Journal of Manufacturing Systems, Vol. 58, (2021), 223-247. https://doi.org/10.1016/j.jmsy.2020.12.001
  18. Haghshenas, P., Sahraeian, R. and Golmohammadi, A.M., "A state-of-the-art model of location, inventory, and pricing problem in the closed-loop supply chain network", International Journal of Engineering, Transaction B: Applications Vol. 35, No. 8, (2022), 1558-1570. doi: 10.5829/ije.2022.35.08B.12.
  19. Ghomi-Avili, M., Akhavan Niaki, S.T. and Tavakkoli-Moghaddam, R., "A joint pricing and sustainable closed-loop supply chain network design problem using blockchain technology", Journal of Industrial and Systems Engineering, Vol. 14, No. 4, (2023), 121-137.
  20. Edalatpour, M.A., Mirzapour Al-e-Hashem, S.M.J. and Fathollahi-Fard, A.M., "Combination of pricing and inventory policies for deteriorating products with sustainability considerations", Environment, Development and Sustainability, (2023). doi: 10.1007/s10668-023-02988-6.
  21. Hashemi, Z. and Tari, F.G., "A prufer-based genetic algorithm for allocation of the vehicles in a discounted transportation cost system", International Journal of Systems Science: Operations & Logistics, Vol. 5, No. 1, (2018), 1-15. doi: 10.1080/23302674.2016.1226980.
  22. Abdi, A., Abdi, A., Fathollahi-Fard, A.M. and Hajiaghaei-Keshteli, M., "A set of calibrated metaheuristics to address a closed-loop supply chain network design problem under uncertainty", International journal of systems science: Operations & logistics, Vol. 8, No. 1, (2021), 23-40. doi: 10.1080/23302674.2019.1610197.
  23. Karimi-Mamaghan, M., Mohammadi, M., Pirayesh, A., Karimi-Mamaghan, A.M. and Irani, H., "Hub-and-spoke network design under congestion: A learning based metaheuristic", Transportation Research Part E: Logistics and Transportation Review, Vol. 142, (2020), 102069. https://doi.org/10.1016/j.tre.2020.102069
  24. Müller-Zhang, Z., Kuhn, T. and Antonino, P.O., "Towards live decision-making for service-based production: Integrated process planning and scheduling with digital twins and deep-q-learning", Computers in Industry, Vol. 149, (2023), 103933. doi. https://doi.org/10.1016/j.compind.2023.103933
  25. Gholizadeh, H., Fazlollahtabar, H., Fathollahi-Fard, A.M. and Dulebenets, M.A., "Preventive maintenance for the flexible flowshop scheduling under uncertainty: A waste-to-energy system", Environmental Science and Pollution Research, (2021). doi: 10.1007/s11356-021-16234-x.
  26. Zhao, H. and Zhang, C., "An online-learning-based evolutionary many-objective algorithm", Information Sciences, Vol. 509, No., (2020), 1-21. https://doi.org/10.1016/j.ins.2019.08.069
  27. Dulebenets, M.A., "An adaptive island evolutionary algorithm for the berth scheduling problem", Memetic Computing, Vol. 12, No. 1, (2020), 51-72. doi: 10.1007/s12293-019-00292-3.
  28. Tian, G., Zhang, X., Fathollahi-Fard, A.M., Jiang, Z., Zhang, C., Yuan, G. and Pham, D.T., "Hybrid evolutionary algorithm for stochastic multiobjective disassembly line balancing problem in remanufacturing", Environmental Science and Pollution Research, (2023). doi: 10.1007/s11356-023-27081-3.
  29. Zhang, X., Zhou, H., Fu, C., Mi, M., Zhan, C., Pham, D.T. and Fathollahi-Fard, A.M., "Application and planning of an energy-oriented stochastic disassembly line balancing problem", Environmental Science and Pollution Research, (2023). doi: 10.1007/s11356-023-27288-4.
International Journal of Engineering
Volume 36, Issue 11
TRANSACTIONS B: Applications
November 2023
Pages 2038-2051

Files

Share

How to cite

Statistics