IDEAS home Printed from https://ideas.repec.org/a/gam/jadmsc/v8y2018i3p39-d161068.html
   My bibliography  Save this article

An Algorithm to Manage Transportation Logistics That Considers Sabotage Risk

Author

Listed:
  • Chaiya Chomchalao

    (Department of Industrial Engineering, Faculty of Engineering, Ubon Ratchathani University, Ubon Ratchathani 34190, Thailand)

  • Sasitorn Kaewman

    (Department of Computer Science, Faculty of Informatic, Mahasarakham University, Mahasarakham 44150, Thailand)

  • Rapeepan Pitakaso

    (Department of Industrial Engineering, Faculty of Engineering, Ubon Ratchathani University, Ubon Ratchathani 34190, Thailand)

  • Kanchana Sethanan

    (Research Unit on System Modeling for Industry, Department of Industrial Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen 40002, Thailand)

Abstract

This paper presents an algorithm to solve the multilevel location–allocation problem when sabotage risk is considered (MLLAP-SB). Sabotage risk is the risk that a deliberate act of sabotage will happen in a living area or during the transportation of a vehicle. This can change the way decisions are made about the transportation problem when it is considered. The mathematical model of the MLLAP-SB is first presented and solved to optimality by using Lingo v. 11 optimization software, but it can solve only small numbers of test instances. Second, two heuristics are presented to solve large numbers of test instances that Lingo cannot solve to optimality within a reasonable time. The original differential evolution (DE) algorithm and the extended version of DE—the modified differential evolution (MDE) algorithm—are presented to solve the MLLAP-SB. From the computational result, when solving small numbers of test instances in which Lingo is able to find the optimality, DE and MDE are able to find a 100% optimal solution while requiring much lower computational time. Lingo uses an average 96,156.67 s to solve the problem, while DE and MDE use only 104 and 90 s, respectively. Solving large numbers of test instances where Lingo cannot solve the problem, MDE outperformed DE, as it found a 100% better solution than DE. MDE has an average 0.404% lower cost than DE when using a computational time of 90 min. The difference in cost between MDE and DE changes from 0.08% when using 10 min to 0.54% when using 100 min computational time. The computational result also explicitly shows that when sabotage risk is integrated into the method of solving the problem, it can reduce the average total cost from 32,772,361 baht to 30,652,360 baht, corresponding to a 9.61% reduction.

Suggested Citation

  • Chaiya Chomchalao & Sasitorn Kaewman & Rapeepan Pitakaso & Kanchana Sethanan, 2018. "An Algorithm to Manage Transportation Logistics That Considers Sabotage Risk," Administrative Sciences, MDPI, vol. 8(3), pages 1-17, July.
    • Handle: RePEc:gam:jadmsc:v:8:y:2018:i:3:p:39-:d:161068
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2076-3387/8/3/39/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2076-3387/8/3/39/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sultana, Arifa & Kumar, Amit, 2012. "Optimal siting and size of bioenergy facilities using geographic information system," Applied Energy, Elsevier, vol. 94(C), pages 192-201.
    2. Drexl, Michael & Schneider, Michael, 2015. "A survey of variants and extensions of the location-routing problem," European Journal of Operational Research, Elsevier, vol. 241(2), pages 283-308.
    3. Nearchou, Andreas C., 2006. "Meta-heuristics from nature for the loop layout design problem," International Journal of Production Economics, Elsevier, vol. 101(2), pages 312-328, June.
    4. Bargos, Fabiano Fernandes & Lamas, Wendell de Queiroz & Bargos, Danubia Caporusso & Neto, Morun Bernardino & Pardal, Paula Cristiane Pinto Mesquita, 2016. "Location problem method applied to sugar and ethanol mills location optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 274-282.
    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. Mengjie Zhang & Lei Wang & Huanhuan Feng & Luwei Zhang & Xiaoshuan Zhang & Jun Li, 2020. "Modeling Method for Cost and Carbon Emission of Sheep Transportation Based on Path Optimization," Sustainability, MDPI, vol. 12(3), pages 1-23, January.
    2. Mohsen Jamali & Esmaeil Bakhshandeh & Mohammad Yaghoubi Khanghahi & Carmine Crecchio, 2021. "Metadata Analysis to Evaluate Environmental Impacts of Wheat Residues Burning on Soil Quality in Developing and Developed Countries," Sustainability, MDPI, vol. 13(11), pages 1-13, June.
    3. Basile, Flavia & Pilotti, Lorenzo & Ugolini, Marco & Lozza, Giovanni & Manzolini, Giampaolo, 2022. "Supply chain optimization and GHG emissions in biofuel production from forestry residues in Sweden," Renewable Energy, Elsevier, vol. 196(C), pages 405-421.
    4. Liwei Zeng & Sunil Chopra & Karen Smilowitz, 2019. "The Covering Path Problem on a Grid," Transportation Science, INFORMS, vol. 53(6), pages 1656-1672, November.
    5. Ghazale Kordi & Parsa Hasanzadeh-Moghimi & Mohammad Mahdi Paydar & Ebrahim Asadi-Gangraj, 2023. "A multi-objective location-routing model for dental waste considering environmental factors," Annals of Operations Research, Springer, vol. 328(1), pages 755-792, September.
    6. 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.
    7. Srinivas, Sharan & Ramachandiran, Surya & Rajendran, Suchithra, 2022. "Autonomous robot-driven deliveries: A review of recent developments and future directions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 165(C).
    8. Capelle, Thomas & Cortés, Cristián E. & Gendreau, Michel & Rey, Pablo A. & Rousseau, Louis-Martin, 2019. "A column generation approach for location-routing problems with pickup and delivery," European Journal of Operational Research, Elsevier, vol. 272(1), pages 121-131.
    9. Alvarez, Jose A. Lopez & Buijs, Paul & Deluster, Rogier & Coelho, Leandro C. & Ursavas, Evrim, 2020. "Strategic and operational decision-making in expanding supply chains for LNG as a fuel," Omega, Elsevier, vol. 97(C).
    10. Höhn, J. & Lehtonen, E. & Rasi, S. & Rintala, J., 2014. "A Geographical Information System (GIS) based methodology for determination of potential biomasses and sites for biogas plants in southern Finland," Applied Energy, Elsevier, vol. 113(C), pages 1-10.
    11. Jihane El Ouadi & Hanae Errousso & Nicolas Malhene & Siham Benhadou & Hicham Medromi, 2022. "A machine-learning based hybrid algorithm for strategic location of urban bundling hubs to support shared public transport," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(5), pages 3215-3258, October.
    12. Sara Martins & Pedro Amorim & Bernardo Almada-Lobo, 2018. "Delivery mode planning for distribution to brick-and-mortar retail stores: discussion and literature review," Flexible Services and Manufacturing Journal, Springer, vol. 30(4), pages 785-812, December.
    13. H. C. Yadav & Rajeev Jain & A. R. Singh & P. K. Mishra, 2017. "Kano integrated robust design approach for aesthetical product design: a case study of a car profile," Journal of Intelligent Manufacturing, Springer, vol. 28(7), pages 1709-1727, October.
    14. Danışment Vural & Robert F. Dell & Erkan Kose, 2021. "Locating unmanned aircraft systems for multiple missions under different weather conditions," Operational Research, Springer, vol. 21(1), pages 725-744, March.
    15. Michiel A. J. uit het Broek & Albert H. Schrotenboer & Bolor Jargalsaikhan & Kees Jan Roodbergen & Leandro C. Coelho, 2021. "Asymmetric Multidepot Vehicle Routing Problems: Valid Inequalities and a Branch-and-Cut Algorithm," Operations Research, INFORMS, vol. 69(2), pages 380-409, March.
    16. Maung, Thein A. & Gustafson, Cole R. & Saxowsky, David M. & Nowatzki, John & Miljkovic, Tatjana & Ripplinger, David, 2013. "The logistics of supplying single vs. multi-crop cellulosic feedstocks to a biorefinery in southeast North Dakota," Applied Energy, Elsevier, vol. 109(C), pages 229-238.
    17. Devlin, Ger & Talbot, Bruce, 2014. "Deriving cooperative biomass resource transport supply strategies in meeting co-firing energy regulations: A case for peat and wood fibre in Ireland," Applied Energy, Elsevier, vol. 113(C), pages 1700-1709.
    18. Zajac, Sandra & Huber, Sandra, 2021. "Objectives and methods in multi-objective routing problems: a survey and classification scheme," European Journal of Operational Research, Elsevier, vol. 290(1), pages 1-25.
    19. Andrés Martínez-Reyes & Carlos L. Quintero-Araújo & Elyn L. Solano-Charris, 2021. "Supplying Personal Protective Equipment to Intensive Care Units during the COVID-19 Outbreak in Colombia. A Simheuristic Approach Based on the Location-Routing Problem," Sustainability, MDPI, vol. 13(14), pages 1-16, July.
    20. Gläser, Sina & Stücken, Mareike, 2021. "Introduction of an underground waste container system–model and solution approaches," European Journal of Operational Research, Elsevier, vol. 295(2), pages 675-689.

    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:jadmsc:v:8:y:2018:i:3:p:39-:d:161068. 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.