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Using greedy clustering method to solve capacitated location-routing problem with fuzzy demands

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  • Zare Mehrjerdi, Yahia
  • Nadizadeh, Ali

Abstract

In this paper, the capacitated location-routing problem with fuzzy demands (CLRP-FD) is considered. In CLRP-FD, facility location problem (FLP) and vehicle routing problem (VRP) are observed simultaneously. Indeed, the vehicles and the depots have a predefined capacity to serve the customers that have fuzzy demands. To model this problem, a fuzzy chance constrained programming model of that is designed based upon the fuzzy credibility theory. To solve this problem, a greedy clustering method (GCM) including the stochastic simulation is proposed. To obtain the best value of the dispatcher preference index of the model and to analyze its influence on the final solution, numerical experiments are carried out. Finally, to show the performance of the greedy clustering method, associated results are compared with the lower bound of the solutions.

Suggested Citation

  • Zare Mehrjerdi, Yahia & Nadizadeh, Ali, 2013. "Using greedy clustering method to solve capacitated location-routing problem with fuzzy demands," European Journal of Operational Research, Elsevier, vol. 229(1), pages 75-84.
    • Handle: RePEc:eee:ejores:v:229:y:2013:i:1:p:75-84
    DOI: 10.1016/j.ejor.2013.02.013
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    8. Drexl, M. & Schneider, M., 2013. "A survey of Location-Routing Problems," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 63234, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
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    10. Nadizadeh, Ali & Hosseini Nasab, Hasan, 2014. "Solving the dynamic capacitated location-routing problem with fuzzy demands by hybrid heuristic algorithm," European Journal of Operational Research, Elsevier, vol. 238(2), pages 458-470.
    11. Aderemi Oluyinka Adewumi & Olawale Joshua Adeleke, 2018. "A survey of recent advances in vehicle routing problems," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 9(1), pages 155-172, February.
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    13. 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.
    14. Zhang, Ying & Qi, Mingyao & Lin, Wei-Hua & Miao, Lixin, 2015. "A metaheuristic approach to the reliable location routing problem under disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 83(C), pages 90-110.
    15. Zhang, Bo & Li, Hui & Li, Shengguo & Peng, Jin, 2018. "Sustainable multi-depot emergency facilities location-routing problem with uncertain information," Applied Mathematics and Computation, Elsevier, vol. 333(C), pages 506-520.
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    17. Keliang Chang & Hong Zhou & Guijing Chen & Huiqin Chen, 2017. "Multiobjective Location Routing Problem considering Uncertain Data after Disasters," Discrete Dynamics in Nature and Society, Hindawi, vol. 2017, pages 1-7, March.
    18. Zhuo Sun & Ni Yan & Yining Sun & Haobin Li, 2019. "Location-Routing Optimization with Split Demand for Customer Self-Pickup via Data Analysis and Heuristics Search," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 36(06), pages 1-24, December.
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    20. Prodhon, Caroline & Prins, Christian, 2014. "A survey of recent research on location-routing problems," European Journal of Operational Research, Elsevier, vol. 238(1), pages 1-17.
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