IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v9y2021i4p379-d499384.html
   My bibliography  Save this article

Multi-Objective Optimization Models for Sustainable Perishable Intermodal Multi-Product Networks with Delivery Time Window

Author

Listed:
  • Chia-Nan Wang

    (Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung 80778, Taiwan)

  • Nhat-Luong Nhieu

    (Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung 80778, Taiwan)

  • Yu-Chi Chung

    (Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung 80778, Taiwan)

  • Huynh-Tram Pham

    (School of Industrial Engineering and Management, International University—Vietnam National University HCMC, Ho Chi Minh 71300, Vietnam)

Abstract

Supply chain network design problem is increasingly showing its importance, especially the perishable supply chain. This research develops a multi-objective mathematical model to design four-echelon intermodal multi-product perishable supply chain configuration in order to ensure a balance of the three pillars of sustainable development: economy, environment, and society. The optimization objective functions of the model are, respectively, minimizing costs, delivery time, emissions, and the supply-demand mismatch in time. The model addresses particular problems in the supply chain of fresh fruits, which is more challenging compared to other types of perishable products due to its seasonal characteristics. The study proposes a new approach that combines and standardizes the above objective functions into a single weighted objective function. The solution from the model supports the decision-making process at both strategic and tactical levels. Strategically, the model supports decisions about the location, size of facilities, product flows, and workforce level. Tactically, the decision variables provide information on harvest time, delivery time, the delivery route, and mode of transport. To demonstrate its practical applicability, the model is applied to Mekong Delta region, Vietnam, where a variety of fruit types, large yields, and high distribution demand in this region make designing a shared supply chain desirable for its overall economic, environmental, and social concerns. Moreover, sensitivity analysis regarding weights of different objectives is performed to assess possible changes in supply chain configurations. Application of this model to other perishable products, the addition of modes of transport, social policy, and uncertainty parameters may be suggested for future research.

Suggested Citation

  • Chia-Nan Wang & Nhat-Luong Nhieu & Yu-Chi Chung & Huynh-Tram Pham, 2021. "Multi-Objective Optimization Models for Sustainable Perishable Intermodal Multi-Product Networks with Delivery Time Window," Mathematics, MDPI, vol. 9(4), pages 1-25, February.
  • Handle: RePEc:gam:jmathe:v:9:y:2021:i:4:p:379-:d:499384
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/9/4/379/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/9/4/379/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Eskandarpour, Majid & Dejax, Pierre & Miemczyk, Joe & Péton, Olivier, 2015. "Sustainable supply chain network design: An optimization-oriented review," Omega, Elsevier, vol. 54(C), pages 11-32.
    2. Etemadnia, Hamideh & Goetz, Stephan J. & Canning, Patrick & Tavallali, Mohammad Sadegh, 2015. "Optimal wholesale facilities location within the fruit and vegetables supply chain with bimodal transportation options: An LP-MIP heuristic approach," European Journal of Operational Research, Elsevier, vol. 244(2), pages 648-661.
    3. Chia-Nan Wang & Han-Khanh Nguyen, 2017. "Enhancing Urban Development Quality Based on the Results of Appraising Efficient Performance of Investors—A Case Study in Vietnam," Sustainability, MDPI, vol. 9(8), pages 1-22, August.
    4. Min-Chun Yu & Chia-Nan Wang & Nguyen-Nhu-Y Ho, 2016. "A Grey Forecasting Approach for the Sustainability Performance of Logistics Companies," Sustainability, MDPI, vol. 8(9), pages 1-18, August.
    5. Jody Harris & Phuong Hong Nguyen & Lan Mai Tran & Phuong Nam Huynh, 2020. "Nutrition transition in Vietnam: changing food supply, food prices, household expenditure, diet and nutrition outcomes," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 12(5), pages 1141-1155, October.
    6. Govindan, K. & Jafarian, A. & Khodaverdi, R. & Devika, K., 2014. "Two-echelon multiple-vehicle location–routing problem with time windows for optimization of sustainable supply chain network of perishable food," International Journal of Production Economics, Elsevier, vol. 152(C), pages 9-28.
    7. Chia-Nan Wang & Hong-Xuyen Thi Ho & Shih-Hsiung Luo & Tsung-Fu Lin, 2017. "An Integrated Approach to Evaluating and Selecting Green Logistics Providers for Sustainable Development," Sustainability, MDPI, vol. 9(2), pages 1-21, February.
    8. Rohmer, S.U.K. & Gerdessen, J.C. & Claassen, G.D.H., 2019. "Sustainable supply chain design in the food system with dietary considerations: A multi-objective analysis," European Journal of Operational Research, Elsevier, vol. 273(3), pages 1149-1164.
    9. Mohammed, Ahmed & Wang, Qian, 2017. "The fuzzy multi-objective distribution planner for a green meat supply chain," International Journal of Production Economics, Elsevier, vol. 184(C), pages 47-58.
    10. Bushuev, Maxim A. & Guiffrida, Alfred L., 2012. "Optimal position of supply chain delivery window: Concepts and general conditions," International Journal of Production Economics, Elsevier, vol. 137(2), pages 226-234.
    11. Petchprakai Sirilertsuwan & Sébastien Thomassey & Xianyi Zeng, 2020. "A Strategic Location Decision-Making Approach for Multi-Tier Supply Chain Sustainability," Sustainability, MDPI, vol. 12(20), pages 1-37, October.
    12. Rong, Aiying & Akkerman, Renzo & Grunow, Martin, 2011. "An optimization approach for managing fresh food quality throughout the supply chain," International Journal of Production Economics, Elsevier, vol. 131(1), pages 421-429, May.
    13. Farahani, Reza Zanjirani & Rezapour, Shabnam & Drezner, Tammy & Fallah, Samira, 2014. "Competitive supply chain network design: An overview of classifications, models, solution techniques and applications," Omega, Elsevier, vol. 45(C), pages 92-118.
    14. Yue Jiang & Yang Zhao & Mengyuan Dong & Shuihua Han, 2019. "Sustainable Supply Chain Network Design with Carbon Footprint Consideration: A Case Study in China," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-19, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    2. Monica Aureliana Petcu & Liliana Ionescu-Feleaga & Bogdan-Ștefan Ionescu & Dumitru-Florin Moise, 2023. "A Decade for the Mathematics : Bibliometric Analysis of Mathematical Modeling in Economics, Ecology, and Environment," Mathematics, MDPI, vol. 11(2), pages 1-30, January.
    3. Ieva Meidute-Kavaliauskiene & Figen Yıldırım & Shahryar Ghorbani & Renata Činčikaitė, 2022. "The Design of a Multi-Period and Multi-Echelon Perishable Goods Supply Network under Uncertainty," Sustainability, MDPI, vol. 14(4), pages 1-18, February.
    4. Bing Han & Shanshan Shi & Haotian Gao & Yan Hu, 2022. "A Sustainable Intermodal Location-Routing Optimization Approach: A Case Study of the Bohai Rim Region," Sustainability, MDPI, vol. 14(7), pages 1-27, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Volha Yakavenka & Ioannis Mallidis & Dimitrios Vlachos & Eleftherios Iakovou & Zafeiriou Eleni, 2020. "Development of a multi-objective model for the design of sustainable supply chains: the case of perishable food products," Annals of Operations Research, Springer, vol. 294(1), pages 593-621, November.
    2. D. G. Mogale & Sri Krishna Kumar & Manoj Kumar Tiwari, 2020. "Green food supply chain design considering risk and post-harvest losses: a case study," Annals of Operations Research, Springer, vol. 295(1), pages 257-284, December.
    3. Soto-Silva, Wladimir E. & Nadal-Roig, Esteve & González-Araya, Marcela C. & Pla-Aragones, Lluis M., 2016. "Operational research models applied to the fresh fruit supply chain," European Journal of Operational Research, Elsevier, vol. 251(2), pages 345-355.
    4. Mogale, D.G. & Kumar, Mukesh & Kumar, Sri Krishna & Tiwari, Manoj Kumar, 2018. "Grain silo location-allocation problem with dwell time for optimization of food grain supply chain network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 111(C), pages 40-69.
    5. Masoud Rabbani & Ali Sabbaghnia & Mahdi Mobini & Jafar Razmi, 2020. "A graph theory-based algorithm for a multi-echelon multi-period responsive supply chain network design with lateral-transshipments," Operational Research, Springer, vol. 20(4), pages 2497-2517, December.
    6. Chamari Pamoshika Jayarathna & Duzgun Agdas & Les Dawes & Tan Yigitcanlar, 2021. "Multi-Objective Optimization for Sustainable Supply Chain and Logistics: A Review," Sustainability, MDPI, vol. 13(24), pages 1-31, December.
    7. Wang, Haiyan & Zhan, Sha-lei & Ng, Chi To & Cheng, T.C.E., 2020. "Coordinating quality, time, and carbon emissions in perishable food production: A new technology integrating GERT and the Bayesian approach," International Journal of Production Economics, Elsevier, vol. 225(C).
    8. Sahar Validi & Arijit Bhattacharya & P. J. Byrne, 2020. "Sustainable distribution system design: a two-phase DoE-guided meta-heuristic solution approach for a three-echelon bi-objective AHP-integrated location-routing model," Annals of Operations Research, Springer, vol. 290(1), pages 191-222, July.
    9. Cannella, Salvatore & Bruccoleri, Manfredi & Framinan, Jose M., 2016. "Closed-loop supply chains: What reverse logistics factors influence performance?," International Journal of Production Economics, Elsevier, vol. 175(C), pages 35-49.
    10. Tricoire, Fabien & Parragh, Sophie N., 2017. "Investing in logistics facilities today to reduce routing emissions tomorrow," Transportation Research Part B: Methodological, Elsevier, vol. 103(C), pages 56-67.
    11. Jyoti Dhingra Darbari & Devika Kannan & Vernika Agarwal & P. C. Jha, 2019. "Fuzzy criteria programming approach for optimising the TBL performance of closed loop supply chain network design problem," Annals of Operations Research, Springer, vol. 273(1), pages 693-738, February.
    12. Ali Saeed Almuflih & Janpriy Sharma & Mohit Tyagi & Arvind Bhardwaj & Mohamed Rafik Noor Mohamed Qureshi & Nawaf Khan, 2022. "Leveraging the Dynamics of Food Supply Chains towards Avenues of Sustainability," Sustainability, MDPI, vol. 14(12), pages 1-15, June.
    13. Lejarza, Fernando & Pistikopoulos, Ioannis & Baldea, Michael, 2021. "A scalable real-time solution strategy for supply chain management of fresh produce: A Mexico-to-United States cross border study," International Journal of Production Economics, Elsevier, vol. 240(C).
    14. Zhalechian, M. & Tavakkoli-Moghaddam, R. & Zahiri, B. & Mohammadi, M., 2016. "Sustainable design of a closed-loop location-routing-inventory supply chain network under mixed uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 89(C), pages 182-214.
    15. Lejarza, Fernando & Baldea, Michael, 2022. "An efficient optimization framework for tracking multiple quality attributes in supply chains of perishable products," European Journal of Operational Research, Elsevier, vol. 297(3), pages 890-903.
    16. Ludmiła Filina-Dawidowicz & Anna Wiktorowska-Jasik, 2022. "Contemporary problems and challenges of sustainable distribution of perishable cargoes: Case study of Polish cold port stores," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(3), pages 4434-4450, March.
    17. Martins, C. L. & Melo, Teresa & Pato, Margarida Vaz, 2016. "Redesigning a food bank supply chain network, Part I: Background and mathematical formulation," Technical Reports on Logistics of the Saarland Business School 10, Saarland University of Applied Sciences (htw saar), Saarland Business School.
    18. Gilani, Hani & Sahebi, Hadi, 2022. "A data-driven robust optimization model by cutting hyperplanes on vaccine access uncertainty in COVID-19 vaccine supply chain," Omega, Elsevier, vol. 110(C).
    19. Ozden Tozanli & Gazi Murat Duman & Elif Kongar & Surendra M. Gupta, 2017. "Environmentally Concerned Logistics Operations in Fuzzy Environment: A Literature Survey," Logistics, MDPI, vol. 1(1), pages 1-42, June.
    20. Van Engeland, Jens & Beliën, Jeroen & De Boeck, Liesje & De Jaeger, Simon, 2020. "Literature review: Strategic network optimization models in waste reverse supply chains," Omega, Elsevier, vol. 91(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:9:y:2021:i:4:p:379-:d:499384. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.