IDEAS home Printed from https://ideas.repec.org/a/vrs/logitl/v14y2023i1p263-274n13.html
   My bibliography  Save this article

Firefly Algorithm with Tabu Search to Solve the Vehicle Routing Problem with Minimized Fuel Emissions: Case Study of Canned Fruits Transport

Author

Listed:
  • Paisarnvirosrak Nattapol

    (Naresuan University, Faculty of Logistics and Digital Supply Chain, Phitsanulok, Thailand)

  • Rungrueang Phornprom

    (Kasetsart University, Faculty of Management Sciences, Chon Buri, Thailand)

Abstract

Nowadays, logistics is used to assess economic growth and address energy consumption and environmental problems. Optimizing collection and delivery routes reduces fuel consumption and cost, thereby minimizing greenhouse gas (GHG) emissions. The vehicle routing problem with time windows (VRPTW) is addressed to identify routes that minimize total transportation costs, fuel consumption, and GHG emissions based on collection and delivery activities. Firefly Algorithm (FA) integrated with Tabu Search (TS) as (FATS) was proposed within the case study concerning canned fruit transport. The results showed that the proposed method outperformed the existing approaches and reduced the fuel consumption from 31,286 to 26,314 litres per year. The proposed algorithm also reduced the number of used vehicles from seven to six, as five 6-wheel trucks and one 4-wheel truck, with transportation cost reduced from 1,061,851 to 893,108 Baht per year, as well as greenhouse gas emissions, which were reduced from 90,730 to 76,312 kg CO2 per year.

Suggested Citation

  • Paisarnvirosrak Nattapol & Rungrueang Phornprom, 2023. "Firefly Algorithm with Tabu Search to Solve the Vehicle Routing Problem with Minimized Fuel Emissions: Case Study of Canned Fruits Transport," LOGI – Scientific Journal on Transport and Logistics, Sciendo, vol. 14(1), pages 263-274, January.
    • Handle: RePEc:vrs:logitl:v:14:y:2023:i:1:p:263-274:n:13
    DOI: 10.2478/logi-2023-0024
    as

    Download full text from publisher

    File URL: https://doi.org/10.2478/logi-2023-0024
    Download Restriction: no
    File URL: https://libkey.io/10.2478/logi-2023-0024?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
    ---><---

    References listed on IDEAS

    as
    1. Rajeev Goel & Raman Maini, 2019. "Evolutionary Ant Colony Algorithm Using Firefly Based Transition for Solving Vehicle Routing Problems: EAFA for VRPs," International Journal of Swarm Intelligence Research (IJSIR), IGI Global, vol. 10(3), pages 46-60, July.
    2. G. B. Dantzig & J. H. Ramser, 1959. "The Truck Dispatching Problem," Management Science, INFORMS, vol. 6(1), pages 80-91, October.
    3. Danlian Li & Qian Cao & Min Zuo & Fei Xu, 2020. "Optimization of Green Fresh Food Logistics with Heterogeneous Fleet Vehicle Route Problem by Improved Genetic Algorithm," Sustainability, MDPI, vol. 12(5), pages 1-17, March.
    4. Ezzatollah Asgharizadeh & Sobhan Jooybar & Hannan Amoozad Mahdiraji & Jose Arturo Garza-Reyes, 2022. "A Novel Travel Time Estimation Model for Modeling a Green Time-Dependent Vehicle Routing Problem in Food Supply Chain," Sustainability, MDPI, vol. 14(14), pages 1-16, July.
    5. Md Ashikur Rahman & Rajalingam Sokkalingam & Mahmod Othman & Kallol Biswas & Lazim Abdullah & Evizal Abdul Kadir, 2021. "Nature-Inspired Metaheuristic Techniques for Combinatorial Optimization Problems: Overview and Recent Advances," Mathematics, MDPI, vol. 9(20), pages 1-32, 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. Daqing Wu & Jiyu Li & Jiye Cui & Dong Hu, 2023. "Research on the Time-Dependent Vehicle Routing Problem for Fresh Agricultural Products Based on Customer Value," Agriculture, MDPI, vol. 13(3), pages 1-23, March.
    2. Jumbo, Olga & Moghaddass, Ramin, 2022. "Resource optimization and image processing for vegetation management programs in power distribution networks," Applied Energy, Elsevier, vol. 319(C).
    3. Babagolzadeh, Mahla & Zhang, Yahua & Abbasi, Babak & Shrestha, Anup & Zhang, Anming, 2022. "Promoting Australian regional airports with subsidy schemes: Optimised downstream logistics using vehicle routing problem," Transport Policy, Elsevier, vol. 128(C), pages 38-51.
    4. Tianlu Zhao & Yongjian Yang & En Wang, 2020. "Minimizing the average arriving distance in carpooling," International Journal of Distributed Sensor Networks, , vol. 16(1), pages 15501477198, January.
    5. A. Mor & M. G. Speranza, 2020. "Vehicle routing problems over time: a survey," 4OR, Springer, vol. 18(2), pages 129-149, June.
    6. Chou, Chang-Chi & Chiang, Wen-Chu & Chen, Albert Y., 2022. "Emergency medical response in mass casualty incidents considering the traffic congestions in proximity on-site and hospital delays," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    7. Pradhananga, Rojee & Taniguchi, Eiichi & Yamada, Tadashi & Qureshi, Ali Gul, 2014. "Bi-objective decision support system for routing and scheduling of hazardous materials," Socio-Economic Planning Sciences, Elsevier, vol. 48(2), pages 135-148.
    8. Qi, Mingyao & Lin, Wei-Hua & Li, Nan & Miao, Lixin, 2012. "A spatiotemporal partitioning approach for large-scale vehicle routing problems with time windows," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(1), pages 248-257.
    9. Marcel Nicola & Claudiu-Ionel Nicola, 2022. "Improvement of Linear and Nonlinear Control for PMSM Using Computational Intelligence and Reinforcement Learning," Mathematics, MDPI, vol. 10(24), pages 1-34, December.
    10. 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).
    11. Tibor Holczinger & Olivér Ősz & Máté Hegyháti, 2020. "Scheduling approach for on-site jobs of service providers," Flexible Services and Manufacturing Journal, Springer, vol. 32(4), pages 913-948, December.
    12. Zhiping Zuo & Yanhui Li & Jing Fu & Jianlin Wu, 2019. "Human Resource Scheduling Model and Algorithm with Time Windows and Multi-Skill Constraints," Mathematics, MDPI, vol. 7(7), pages 1-18, July.
    13. Narjes MASHHADI BANDANI & Alireza NADERI & Mohsen AKBARPOUR SHIRZAEI, 2017. "Cement Transportation Limited-Fleet Modeling And Assigning To Rated Demands," Transport Problems, Silesian University of Technology, Faculty of Transport, vol. 12(1), pages 111-123, March.
    14. Ji, Chenlu & Mandania, Rupal & Liu, Jiyin & Liret, Anne, 2022. "Scheduling on-site service deliveries to minimise the risk of missing appointment times," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    15. Baals, Julian & Emde, Simon & Turkensteen, Marcel, 2023. "Minimizing earliness-tardiness costs in supplier networks—A just-in-time truck routing problem," European Journal of Operational Research, Elsevier, vol. 306(2), pages 707-741.
    16. Yeo, Lip Siang & Teng, Sin Yong & Ng, Wendy Pei Qin & Lim, Chun Hsion & Leong, Wei Dong & Lam, Hon Loong & Wong, Yat Choy & Sunarso, Jaka & How, Bing Shen, 2022. "Sequential optimization of process and supply chains considering re-refineries for oil and gas circularity," Applied Energy, Elsevier, vol. 322(C).
    17. Müller, Juliane, 2010. "Approximative solutions to the bicriterion Vehicle Routing Problem with Time Windows," European Journal of Operational Research, Elsevier, vol. 202(1), pages 223-231, April.
    18. Martinhon, Carlos & Lucena, Abilio & Maculan, Nelson, 2004. "Stronger K-tree relaxations for the vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 158(1), pages 56-71, October.
    19. Ling Gai & Ying Jin & Binyuan Zhang, 2022. "An integrated method for hybrid distribution with estimation of demand matching degree," Journal of Combinatorial Optimization, Springer, vol. 44(4), pages 2782-2808, November.
    20. Jin Li & Feng Wang & Yu He, 2020. "Electric Vehicle Routing Problem with Battery Swapping Considering Energy Consumption and Carbon Emissions," Sustainability, MDPI, vol. 12(24), pages 1-20, December.

    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:vrs:logitl:v:14:y:2023:i:1:p:263-274:n:13. 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: Peter Golla (email available below). General contact details of provider: https://www.sciendo.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.