IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i19p7035-d924550.html
   My bibliography  Save this article

Improved Whale Optimization Algorithm Based on Hybrid Strategy and Its Application in Location Selection for Electric Vehicle Charging Stations

Author

Listed:
  • Yongjing Li

    (School of Information Science and Electrical Engineering, Shandong Jiaotong University, Jinan 250357, China)

  • Wenhui Pei

    (School of Information Science and Electrical Engineering, Shandong Jiaotong University, Jinan 250357, China)

  • Qi Zhang

    (School of Control Science and Engineering, Shandong University, Jinan 250061, China
    State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China)

Abstract

The charging station location model is a nonlinear programming model with complex constraints. In order to solve the problems of weak search ability and low solution accuracy of the whale optimization algorithm (WOA) in solving location models or high-dimensional problems, this paper proposes an improved whale optimization algorithm (IWOA) based on hybrid strategies. Chaos mapping and reverse learning mechanism are introduced in the original algorithm, and the change mode of convergence factor and probability threshold is improved. Through optimization experiments on 18 benchmark functions, the test results show that IWOA has the best solution ability. Finally, IWOA is used to solve a site selection optimization model aiming at the minimum comprehensive cost. The results show that the proposed algorithm and model can effectively reduce the comprehensive cost of site selection. This provides a necessary decision-making reference for the scientific site selection for electric vehicle charging stations.

Suggested Citation

  • Yongjing Li & Wenhui Pei & Qi Zhang, 2022. "Improved Whale Optimization Algorithm Based on Hybrid Strategy and Its Application in Location Selection for Electric Vehicle Charging Stations," Energies, MDPI, vol. 15(19), pages 1-25, September.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:19:p:7035-:d:924550
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/19/7035/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/19/7035/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Guiliang Gong & Raymond Chiong & Qianwang Deng & Xuran Gong, 2020. "A hybrid artificial bee colony algorithm for flexible job shop scheduling with worker flexibility," International Journal of Production Research, Taylor & Francis Journals, vol. 58(14), pages 4406-4420, July.
    2. Di Xu & Wenhui Pei & Qi Zhang, 2022. "Optimal Planning of Electric Vehicle Charging Stations Considering User Satisfaction and Charging Convenience," Energies, MDPI, vol. 15(14), pages 1-16, July.
    3. Gui-Ying Ning & Dun-Qian Cao & Manuel De la Sen, 2021. "Improved Whale Optimization Algorithm for Solving Constrained Optimization Problems," Discrete Dynamics in Nature and Society, Hindawi, vol. 2021, pages 1-13, February.
    4. Shuxia Yang & Di Zhang & Jing Fu & Shujing Fan & Yu Ji, 2018. "Market Cultivation of Electric Vehicles in China: A Survey Based on Consumer Behavior," Sustainability, MDPI, vol. 10(11), pages 1-23, November.
    5. Wu, Jingwen & Liao, Hua & Wang, Jin-Wei, 2020. "Analysis of consumer attitudes towards autonomous, connected, and electric vehicles: A survey in China," Research in Transportation Economics, Elsevier, vol. 80(C).
    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. Alejandro Sanz & Peter Meyer, 2024. "Electrifying the Last-Mile Logistics (LML) in Intensive B2B Operations—An European Perspective on Integrating Innovative Platforms," Logistics, MDPI, vol. 8(2), pages 1-39, April.

    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. Wang, Yuanyuan & Chi, Yuanying & Xu, Jin-Hua & Yuan, Yongke, 2022. "Consumers’ attitudes and their effects on electric vehicle sales and charging infrastructure construction: An empirical study in China," Energy Policy, Elsevier, vol. 165(C).
    2. Shuxia Yang & Yu Ji & Di Zhang & Jing Fu, 2019. "Equilibrium between Road Traffic Congestion and Low-Carbon Economy: A Case Study from Beijing, China," Sustainability, MDPI, vol. 11(1), pages 1-22, January.
    3. Asmussen, Katherine E. & Mondal, Aupal & Bhat, Chandra R., 2022. "Adoption of partially automated vehicle technology features and impacts on vehicle miles of travel (VMT)," Transportation Research Part A: Policy and Practice, Elsevier, vol. 158(C), pages 156-179.
    4. Li, Dun & Huang, Youlin & Qian, Lixian, 2022. "Potential adoption of robotaxi service: The roles of perceived benefits to multiple stakeholders and environmental awareness," Transport Policy, Elsevier, vol. 126(C), pages 120-135.
    5. Oluwasola O. Ademulegun & Paul MacArtain & Bukola Oni & Neil J. Hewitt, 2022. "Multi-Stage Multi-Criteria Decision Analysis for Siting Electric Vehicle Charging Stations within and across Border Regions," Energies, MDPI, vol. 15(24), pages 1-28, December.
    6. Reema Bera & Bhargab Maitra, 2021. "Analyzing Prospective Owners’ Choice Decision towards Plug-in Hybrid Electric Vehicles in Urban India: A Stated Preference Discrete Choice Experiment," Sustainability, MDPI, vol. 13(14), pages 1-24, July.
    7. Dongming Wu & Liukai Yu & Qianqian Zhang & Yangyang Jiao & Yuhe Wu, 2021. "Materialism, Ecological Consciousness and Purchasing Intention of Electric Vehicles: An Empirical Analysis among Chinese Consumers," Sustainability, MDPI, vol. 13(5), pages 1-19, March.
    8. Wang, Kai-Hua & Su, Chi-Wei & Xiao, Yidong & Liu, Lu, 2022. "Is the oil price a barometer of China's automobile market? From a wavelet-based quantile-on-quantile regression perspective," Energy, Elsevier, vol. 240(C).
    9. Shoujing Zhang & Tiantian Hou & Qing Qu & Adam Glowacz & Samar M. Alqhtani & Muhammad Irfan & Grzegorz Królczyk & Zhixiong Li, 2022. "An Improved Mayfly Method to Solve Distributed Flexible Job Shop Scheduling Problem under Dual Resource Constraints," Sustainability, MDPI, vol. 14(19), pages 1-19, September.
    10. Jose Esteves & Daniel Alonso-Martínez & Guillermo de Haro, 2021. "Profiling Spanish Prospective Buyers of Electric Vehicles Based on Demographics," Sustainability, MDPI, vol. 13(16), pages 1-22, August.
    11. Loni, Abdolah & Asadi, Somayeh, 2023. "Data-driven equitable placement for electric vehicle charging stations: Case study San Francisco," Energy, Elsevier, vol. 282(C).
    12. Pan, Xiaofeng & Liu, Shaobo, 2022. "Modeling travel choice behavior with the concept of image: A case study of college students’ choice of homecoming train trips during the Spring Festival travel rush in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 155(C), pages 247-258.
    13. Nnaemeka V. Emodi & Udochukwu B. Akuru & Michael O. Dioha & Patrick Adoba & Remeredzai J. Kuhudzai & Olusola Bamisile, 2023. "The Role of Internet of Things on Electric Vehicle Charging Infrastructure and Consumer Experience," Energies, MDPI, vol. 16(10), pages 1-18, May.
    14. Wang, Yaxian & Zhao, Zhenli & Baležentis, Tomas, 2023. "Benefit distribution in shared private charging pile projects based on modified Shapley value," Energy, Elsevier, vol. 263(PB).
    15. Bastida-Molina, Paula & Ribó-Pérez, David & Gómez-Navarro, Tomás & Hurtado-Pérez, Elías, 2022. "What is the problem? The obstacles to the electrification of urban mobility in Mediterranean cities. Case study of Valencia, Spain," Renewable and Sustainable Energy Reviews, Elsevier, vol. 166(C).
    16. Rong Zheng & Abdelazim G. Hussien & He-Ming Jia & Laith Abualigah & Shuang Wang & Di Wu, 2022. "An Improved Wild Horse Optimizer for Solving Optimization Problems," Mathematics, MDPI, vol. 10(8), pages 1-30, April.
    17. Ana Pavlićević & Saša Mujović, 2022. "Impact of Reactive Power from Public Electric Vehicle Stations on Transformer Aging and Active Energy Losses," Energies, MDPI, vol. 15(19), pages 1-24, September.
    18. Shuxia Yang & Ruoyang Li & Jialin Li, 2020. "“Separation of Vehicle and Battery” of Private Electric Vehicles and Customer Delivered Value: Based on the Attempt of 2 Chinese EV Companies," Sustainability, MDPI, vol. 12(5), pages 1-22, March.
    19. Ieva Meidute-Kavaliauskiene & Bülent Yıldız & Şemsettin Çiğdem & Renata Činčikaitė, 2021. "Do People Prefer Cars That People Don’t Drive? A Survey Study on Autonomous Vehicles," Energies, MDPI, vol. 14(16), pages 1-21, August.
    20. Ayetor, G.K. & Mbonigaba, Innocent & Sunnu, Albert K. & Nyantekyi-Kwakye, Baafour, 2021. "Impact of replacing ICE bus fleet with electric bus fleet in Africa: A lifetime assessment," Energy, Elsevier, vol. 221(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:jeners:v:15:y:2022:i:19:p:7035-:d:924550. 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.