IDEAS home Printed from https://ideas.repec.org/a/spr/snopef/v2y2021i3d10.1007_s43069-021-00087-8.html
   My bibliography  Save this article

A Comparison between Memetic Algorithm and Genetic Algorithm for an Integrated Logistics Network with Flexible Delivery Path

Author

Listed:
  • Elham Behmanesh

    (University of Bremen)

  • Jürgen Pannek

    (University of Bremen)

Abstract

The distribution/allocation problem is known as one of the most comprehensive strategic decision. In real-world cases, it is impossible to solve a distribution/allocation problem in traditional ways with acceptable time. Hence researchers develop efficient non-traditional techniques for the large-term operation of the whole supply chain. These techniques provide near optimal solutions particularly for large-scale test problems. This paper presents an integrated supply chain model which is flexible in the delivery path. As the solution methodology, we apply a memetic algorithm with a neighborhood search mechanism and novelty in population presentation method called “extended random path direct encoding method.” To illustrate the performance of the proposed memetic algorithm, LINGO optimization software serves as comparison basis for small size problems. In large-size cases that we are dealing with in real world, a classical genetic algorithm as the second metaheuristic algorithm is considered to compare the results and show the efficiency of the memetic algorithm.

Suggested Citation

  • Elham Behmanesh & Jürgen Pannek, 2021. "A Comparison between Memetic Algorithm and Genetic Algorithm for an Integrated Logistics Network with Flexible Delivery Path," SN Operations Research Forum, Springer, vol. 2(3), pages 1-24, September.
    • Handle: RePEc:spr:snopef:v:2:y:2021:i:3:d:10.1007_s43069-021-00087-8
    DOI: 10.1007/s43069-021-00087-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s43069-021-00087-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s43069-021-00087-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Gen, Mitsuo & Kumar, Anup & Ryul Kim, Jong, 2005. "Recent network design techniques using evolutionary algorithms," International Journal of Production Economics, Elsevier, vol. 98(2), pages 251-261, November.
    2. Aras, Necati & Aksen, Deniz & Gönül Tanugur, Ayse, 2008. "Locating collection centers for incentive-dependent returns under a pick-up policy with capacitated vehicles," European Journal of Operational Research, Elsevier, vol. 191(3), pages 1223-1240, December.
    3. Masoud Zarei & Saeed Mansour & Ali Husseinzadeh Kashan & Behrooz Karimi, 2010. "Designing a Reverse Logistics Network for End-of-Life Vehicles Recovery," Mathematical Problems in Engineering, Hindawi, vol. 2010, pages 1-16, March.
    4. Melo, M.T. & Nickel, S. & Saldanha-da-Gama, F., 2009. "Facility location and supply chain management - A review," European Journal of Operational Research, Elsevier, vol. 196(2), pages 401-412, July.
    5. Alumur, Sibel A. & Nickel, Stefan & Saldanha-da-Gama, Francisco & Verter, Vedat, 2012. "Multi-period reverse logistics network design," European Journal of Operational Research, Elsevier, vol. 220(1), pages 67-78.
    6. Ehsan Yadegari & Mostafa Ekhtiari & Mostafa Zandieh & Akbar Alem-Tabriz, 2014. "An Artificial Immune Algorithm for a Closed-Loop Supply Chain Network Design Problem with Different Delivery Paths," International Journal of Strategic Decision Sciences (IJSDS), IGI Global, vol. 5(3), pages 27-46, July.
    7. Klibi, Walid & Martel, Alain & Guitouni, Adel, 2010. "The design of robust value-creating supply chain networks: A critical review," European Journal of Operational Research, Elsevier, vol. 203(2), pages 283-293, June.
    8. Wang, Yong & Peng, Shouguo & Zhou, Xuesong & Mahmoudi, Monirehalsadat & Zhen, Lu, 2020. "Green logistics location-routing problem with eco-packages," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 143(C).
    9. Jayaraman, Vaidyanathan & Patterson, Raymond A. & Rolland, Erik, 2003. "The design of reverse distribution networks: Models and solution procedures," European Journal of Operational Research, Elsevier, vol. 150(1), pages 128-149, October.
    Full references (including those not matched with items on IDEAS)

    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. Keyvanshokooh, Esmaeil & Ryan, Sarah M. & Kabir, Elnaz, 2016. "Hybrid robust and stochastic optimization for closed-loop supply chain network design using accelerated Benders decomposition," European Journal of Operational Research, Elsevier, vol. 249(1), pages 76-92.
    2. Longinidis, Pantelis & Georgiadis, Michael C., 2014. "Integration of sale and leaseback in the optimal design of supply chain networks," Omega, Elsevier, vol. 47(C), pages 73-89.
    3. Diabat, Ali & Jebali, Aida, 2021. "Multi-product and multi-period closed loop supply chain network design under take-back legislation," International Journal of Production Economics, Elsevier, vol. 231(C).
    4. Toso, Eli Angela V. & Alem, Douglas, 2014. "Effective location models for sorting recyclables in public management," European Journal of Operational Research, Elsevier, vol. 234(3), pages 839-860.
    5. Cardoso, Sónia R. & Barbosa-Póvoa, Ana Paula F.D. & Relvas, Susana, 2013. "Design and planning of supply chains with integration of reverse logistics activities under demand uncertainty," European Journal of Operational Research, Elsevier, vol. 226(3), pages 436-451.
    6. Diabat, Ali & Kannan, Devika & Kaliyan, Mathiyazhagan & Svetinovic, Davor, 2013. "An optimization model for product returns using genetic algorithms and artificial immune system," Resources, Conservation & Recycling, Elsevier, vol. 74(C), pages 156-169.
    7. Walther, Grit & Schatka, Anne & Spengler, Thomas S., 2012. "Design of regional production networks for second generation synthetic bio-fuel – A case study in Northern Germany," European Journal of Operational Research, Elsevier, vol. 218(1), pages 280-292.
    8. Becker, Tristan & Lier, Stefan & Werners, Brigitte, 2019. "Value of modular production concepts in future chemical industry production networks," European Journal of Operational Research, Elsevier, vol. 276(3), pages 957-970.
    9. Rahman, Shams & Subramanian, Nachiappan, 2012. "Factors for implementing end-of-life computer recycling operations in reverse supply chains," International Journal of Production Economics, Elsevier, vol. 140(1), pages 239-248.
    10. Mallidis, I. & Vlachos, D. & Dekker, R., 2010. "Greening Supply Chains: Impact on Cost and Design," Econometric Institute Research Papers EI 2010-39a, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    11. Jabbarzadeh, Armin & Fahimnia, Behnam & Sheu, Jiuh-Biing & Moghadam, Hani Shahmoradi, 2016. "Designing a supply chain resilient to major disruptions and supply/demand interruptions," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 121-149.
    12. Duong, Quang Huy & Zhou, Li & Meng, Meng & Nguyen, Truong Van & Ieromonachou, Petros & Nguyen, Duy Tiep, 2022. "Understanding product returns: A systematic literature review using machine learning and bibliometric analysis," International Journal of Production Economics, Elsevier, vol. 243(C).
    13. Varsei, Mohsen & Polyakovskiy, Sergey, 2017. "Sustainable supply chain network design: A case of the wine industry in Australia," Omega, Elsevier, vol. 66(PB), pages 236-247.
    14. Jeihoonian, Mohammad & Kazemi Zanjani, Masoumeh & Gendreau, Michel, 2017. "Closed-loop supply chain network design under uncertain quality status: Case of durable products," International Journal of Production Economics, Elsevier, vol. 183(PB), pages 470-486.
    15. Roba W. Salem & Mohamed Haouari, 2017. "A simulation-optimisation approach for supply chain network design under supply and demand uncertainties," International Journal of Production Research, Taylor & Francis Journals, vol. 55(7), pages 1845-1861, April.
    16. 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.
    17. 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).
    18. Blossey, Gregor & Hahn, Gerd J. & Koberstein, Achim, 2022. "Planning pharmaceutical manufacturing networks in the light of uncertain production approval times," International Journal of Production Economics, Elsevier, vol. 244(C).
    19. Gu, Wei & Wang, Chen & Dai, Shufen & Wei, Lirong & Chiang, I. Robert, 2021. "Optimal strategies for reverse logistics network construction: A multi-criteria decision method for Chinese iron and steel industry," Resources Policy, Elsevier, vol. 74(C).
    20. Margolis, Joshua T. & Sullivan, Kelly M. & Mason, Scott J. & Magagnotti, Mariah, 2018. "A multi-objective optimization model for designing resilient supply chain networks," International Journal of Production Economics, Elsevier, vol. 204(C), pages 174-185.

    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:spr:snopef:v:2:y:2021:i:3:d:10.1007_s43069-021-00087-8. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.