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Capacitated Facility Location and Allocation with Uncertain Demand for Tourism Logistics: A Multiobjective Optimisation Approach

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Listed:
  • Zhiyang Jin
  • Yang Li
  • Guohua Fu
  • Kunhao Dai
  • Na Qiu
  • Jinyi Liu
  • Mao Lin
  • Zhennan Qin

Abstract

The paper develops a Multiobjective Optimisation (MOO) model for addressing Capacitated Facility Location Problem (CFLP) in tourism logistics, where two objectives are total of cost and customer service level. Nondominated Sorting Genetic Algorithm II (NSGA II) is used to solve the model. The illustrative case with imaginary data demonstrates that the model can figure out the location of the nodes of tourism logistics network and allocation of these sites, while the total of cost is reduced by up to 56.75% and customer service level is increased by an average of 105%. The distinction of this study compared to the current papers is that our model incorporates both items A and B to the subject matter of tourism logistics, where items A refer to tourism-related products and items B involve personal goods of tourists. The model established is limited with one assumption and one limitation which are associated with Vehicle Routing Problem (VRP) and the boundary of tourism logistics activity. Therefore, further research for the elimination of these limits is recommended.

Suggested Citation

  • Zhiyang Jin & Yang Li & Guohua Fu & Kunhao Dai & Na Qiu & Jinyi Liu & Mao Lin & Zhennan Qin, 2019. "Capacitated Facility Location and Allocation with Uncertain Demand for Tourism Logistics: A Multiobjective Optimisation Approach," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-18, June.
    • Handle: RePEc:hin:jnlmpe:4158940
    DOI: 10.1155/2019/4158940
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