IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v197y2018icp232-242.html
   My bibliography  Save this article

Using OEE to evaluate the effectiveness of urban freight transportation systems: A case study

Author

Listed:
  • Muñoz-Villamizar, Andrés
  • Santos, Javier
  • Montoya-Torres, Jairo R.
  • Jaca, Carmen

Abstract

The transport of goods is essential for the economic growth of cities and regions. Urban freight transportation makes up a very small percentage of the total transportation time for goods, but it can represent up to 28% of total transportation costs. To reduce overall costs and increase revenue from this operation, one common methodology used by decision makers is the optimization models. This paper proposes a new methodology for evaluating the effectiveness of urban freight transportation systems using the OEE (Overall Equipment Effectiveness) metric, a well-known rate used in the Lean Manufacturing framework. The methodology uses a mathematical model with several objective functions, two of which are multi-objective, to explore the relationships and trade-offs between economic development, quality, performance and availability (partial rates of the OEE). The final objective is to optimize the OEE metrics and the profitability of a transportation system. This methodology was tested using real-data from the city of Bogotá, Colombia. Experiments were run with different companies, costs, demands and travel times in order to validate the proposed approach. The results show the benefits of using multi-objective functions to optimize both OEE (quality, performance and availability metrics) and profits. The proposed methodology provides an ‘ex ante’ evaluation of the tactical and operational decisions made by companies in configuring an urban freight transport system.

Suggested Citation

  • Muñoz-Villamizar, Andrés & Santos, Javier & Montoya-Torres, Jairo R. & Jaca, Carmen, 2018. "Using OEE to evaluate the effectiveness of urban freight transportation systems: A case study," International Journal of Production Economics, Elsevier, vol. 197(C), pages 232-242.
  • Handle: RePEc:eee:proeco:v:197:y:2018:i:c:p:232-242
    DOI: 10.1016/j.ijpe.2018.01.011
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925527318300410
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ijpe.2018.01.011?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. G. B. Dantzig & J. H. Ramser, 1959. "The Truck Dispatching Problem," Management Science, INFORMS, vol. 6(1), pages 80-91, October.
    2. Parsa, Payam & Rossetti, Manuel D. & Zhang, Shengfan & Pohl, Edward A., 2017. "Quantifying the benefits of continuous replenishment program for partner evaluation," International Journal of Production Economics, Elsevier, vol. 187(C), pages 229-245.
    3. Tsekouras, Kostas D. & Pantzios, Christos J. & Karagiannis, Giannis, 2004. "Malmquist productivity index estimation with zero-value variables: The case of Greek prefectural training councils," International Journal of Production Economics, Elsevier, vol. 89(1), pages 95-106, May.
    4. Gu, Jinxiang & Goetschalckx, Marc & McGinnis, Leon F., 2007. "Research on warehouse operation: A comprehensive review," European Journal of Operational Research, Elsevier, vol. 177(1), pages 1-21, February.
    5. Alaei, Saeed & Setak, Mostafa, 2015. "Multi objective coordination of a supply chain with routing and service level consideration," International Journal of Production Economics, Elsevier, vol. 167(C), pages 271-281.
    6. Rosario Domingo & Sergio Aguado, 2015. "Overall Environmental Equipment Effectiveness as a Metric of a Lean and Green Manufacturing System," Sustainability, MDPI, vol. 7(7), pages 1-17, July.
    7. G. Clarke & J. W. Wright, 1964. "Scheduling of Vehicles from a Central Depot to a Number of Delivery Points," Operations Research, INFORMS, vol. 12(4), pages 568-581, August.
    8. Abdelhamid Moutaoukil & Gilles Neubert & Ridha Derrouiche, 2015. "Urban Freight Distribution : The impact of delivery time on sustainability," Post-Print hal-02313322, HAL.
    9. Li, Xiangyong & Tian, Peng & Leung, Stephen C.H., 2010. "Vehicle routing problems with time windows and stochastic travel and service times: Models and algorithm," International Journal of Production Economics, Elsevier, vol. 125(1), pages 137-145, May.
    10. Tsekouras, Kostas & Chatzistamoulou, Nikos & Kounetas, Kostas & Broadstock, David C., 2016. "Spillovers, path dependence and the productive performance of European transportation sectors in the presence of technology heterogeneity," Technological Forecasting and Social Change, Elsevier, vol. 102(C), pages 261-274.
    11. Vieira, José Geraldo Vidal & Fransoo, Jan C. & Carvalho, Carla Deguirmendjian, 2015. "Freight distribution in megacities: Perspectives of shippers, logistics service providers and carriers," Journal of Transport Geography, Elsevier, vol. 46(C), pages 46-54.
    12. Langevin, André & Mbaraga, Pontien & Campbell, James F., 1996. "Continuous approximation models in freight distribution: An overview," Transportation Research Part B: Methodological, Elsevier, vol. 30(3), pages 163-188, June.
    13. Zhang, Jianghua & Zhao, Yingxue & Xue, Weili & Li, Jin, 2015. "Vehicle routing problem with fuel consumption and carbon emission," International Journal of Production Economics, Elsevier, vol. 170(PA), pages 234-242.
    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. Nader, Joelle & El-Khalil, Raed & Nassar, Elma & Hong, Paul, 2022. "Pandemic planning, sustainability practices, and organizational performance: An empirical investigation of global manufacturing firms," International Journal of Production Economics, Elsevier, vol. 246(C).
    2. Orji, Ifeyinwa Juliet & Kusi-Sarpong, Simonov & Gupta, Himanshu & Okwu, Modestus, 2019. "Evaluating challenges to implementing eco-innovation for freight logistics sustainability in Nigeria," Transportation Research Part A: Policy and Practice, Elsevier, vol. 129(C), pages 288-305.
    3. Mohammad Zaher Akkad & Tamás Bányai, 2020. "Multi-Objective Approach for Optimization of City Logistics Considering Energy Efficiency," Sustainability, MDPI, vol. 12(18), pages 1-23, September.
    4. Michał Lasota & Aleksandra Zabielska & Marianna Jacyna & Piotr Gołębiowski & Renata Żochowska & Mariusz Wasiak, 2024. "Method for Delivery Planning in Urban Areas with Environmental Aspects," Sustainability, MDPI, vol. 16(4), pages 1-18, February.
    5. Magdalena Mucowska, 2021. "Trends of Environmentally Sustainable Solutions of Urban Last-Mile Deliveries on the E-Commerce Market—A Literature Review," Sustainability, MDPI, vol. 13(11), pages 1-26, May.
    6. Hung, Yick-Hin & Li, Leon Y.O. & Cheng, T.C.E., 2022. "Uncovering hidden capacity in overall equipment effectiveness management," International Journal of Production Economics, Elsevier, vol. 248(C).

    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. Jorge Oyola & Halvard Arntzen & David L. Woodruff, 2017. "The stochastic vehicle routing problem, a literature review, Part II: solution methods," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 6(4), pages 349-388, December.
    2. Briseida Sarasola & Karl Doerner & Verena Schmid & Enrique Alba, 2016. "Variable neighborhood search for the stochastic and dynamic vehicle routing problem," Annals of Operations Research, Springer, vol. 236(2), pages 425-461, January.
    3. Briseida Sarasola & Karl F. Doerner & Verena Schmid & Enrique Alba, 2016. "Variable neighborhood search for the stochastic and dynamic vehicle routing problem," Annals of Operations Research, Springer, vol. 236(2), pages 425-461, January.
    4. Chiang, Wen-Chyuan & Li, Yuyu & Shang, Jennifer & Urban, Timothy L., 2019. "Impact of drone delivery on sustainability and cost: Realizing the UAV potential through vehicle routing optimization," Applied Energy, Elsevier, vol. 242(C), pages 1164-1175.
    5. Jumbo, Olga & Moghaddass, Ramin, 2022. "Resource optimization and image processing for vegetation management programs in power distribution networks," Applied Energy, Elsevier, vol. 319(C).
    6. Ido Orenstein & Tal Raviv & Elad Sadan, 2019. "Flexible parcel delivery to automated parcel lockers: models, solution methods and analysis," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 8(5), pages 683-711, December.
    7. Coelho, V.N. & Grasas, A. & Ramalhinho, H. & Coelho, I.M. & Souza, M.J.F. & Cruz, R.C., 2016. "An ILS-based algorithm to solve a large-scale real heterogeneous fleet VRP with multi-trips and docking constraints," European Journal of Operational Research, Elsevier, vol. 250(2), pages 367-376.
    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. 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).
    10. 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).
    11. 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.
    12. van Gils, Teun & Ramaekers, Katrien & Braekers, Kris & Depaire, Benoît & Caris, An, 2018. "Increasing order picking efficiency by integrating storage, batching, zone picking, and routing policy decisions," International Journal of Production Economics, Elsevier, vol. 197(C), pages 243-261.
    13. Loske, Dominic & Klumpp, Matthias, 2021. "Human-AI collaboration in route planning: An empirical efficiency-based analysis in retail logistics," International Journal of Production Economics, Elsevier, vol. 241(C).
    14. 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.
    15. 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.
    16. 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.
    17. Hongtao Lei & Gilbert Laporte & Bo Guo, 2012. "A generalized variable neighborhood search heuristic for the capacitated vehicle routing problem with stochastic service times," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 20(1), pages 99-118, April.
    18. Muyldermans, L. & Pang, G., 2010. "On the benefits of co-collection: Experiments with a multi-compartment vehicle routing algorithm," European Journal of Operational Research, Elsevier, vol. 206(1), pages 93-103, October.
    19. Yossiri Adulyasak & Jean-François Cordeau & Raf Jans, 2014. "Optimization-Based Adaptive Large Neighborhood Search for the Production Routing Problem," Transportation Science, INFORMS, vol. 48(1), pages 20-45, February.
    20. Abdelkader Sbihi & Richard Eglese, 2010. "Combinatorial optimization and Green Logistics," Annals of Operations Research, Springer, vol. 175(1), pages 159-175, March.

    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:eee:proeco:v:197:y:2018:i:c:p:232-242. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijpe .

    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.