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An Improved Cuckoo Search for a Patient Transportation Problem with Consideration of Reducing Transport Emissions

Author

Listed:
  • Liyang Xiao

    (Nanomedicine Lab, Univ. Bourgogne Franche-Comté, UTBM, 25030 Besancon, France)

  • Mahjoub Dridi

    (Nanomedicine Lab, Univ. Bourgogne Franche-Comté, UTBM, 25030 Besancon, France)

  • Amir Hajjam El Hassani

    (Nanomedicine Lab, Univ. Bourgogne Franche-Comté, UTBM, 25030 Besancon, France)

  • Hongying Fei

    (School of Management, Shanghai University, 99 ShangDa Road, BaoShan District, Shanghai 200444, China)

  • Wanlong Lin

    (Shanghai No.3 Rehabilitation Hospital, 100 JiaoCheng Road, JingAn District, Shanghai 200072, China)

Abstract

Many government agencies and business organizations have realized that it is necessary to consider not only the economic cost but also the road transport emissions when they determine the transport policies and operations. In this study, a patient transportation problem with the aim of reducing transport emissions has been formulated by implementing CVRP model. In order to determine the routes of patient transportation with optimized emissions for targeted hospital, an improved Cuckoo Search (ICS) algorithm is proposed. In this study, a ‘split’ procedure has been implemented to simplify the individual’s representation. A new category of cuckoos has been introduced to improve the ICS’s search ability. Two heuristics have been applied to improve the quality of initial population. A local search mechanism has been embedded in the search procedure to improve the quality of solutions obtained at the end of each iteration. The computational results were encouraging and demonstrated the effectiveness of the proposed solution method.

Suggested Citation

  • Liyang Xiao & Mahjoub Dridi & Amir Hajjam El Hassani & Hongying Fei & Wanlong Lin, 2018. "An Improved Cuckoo Search for a Patient Transportation Problem with Consideration of Reducing Transport Emissions," Sustainability, MDPI, vol. 10(3), pages 1-19, March.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:3:p:793-:d:136046
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    Cited by:

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    2. 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.

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