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Multiobjective Location Routing Problem considering Uncertain Data after Disasters

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  • Keliang Chang
  • Hong Zhou
  • Guijing Chen
  • Huiqin Chen

Abstract

The relief distributions after large disasters play an important role for rescue works. After disasters there is a high degree of uncertainty, such as the demands of disaster points and the damage of paths. The demands of affected points and the velocities between two points on the paths are uncertain in this article, and the robust optimization method is applied to deal with the uncertain parameters. This paper proposes a nonlinear location routing problem with half-time windows and with three objectives. The affected points can be visited more than one time. The goals are the total costs of the transportation, the satisfaction rates of disaster nodes, and the path transport capacities which are denoted by vehicle velocities. Finally, the genetic algorithm is applied to solve a number of numerical examples, and the results show that the genetic algorithm is very stable and effective for this problem.

Suggested Citation

  • 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.
    • Handle: RePEc:hin:jnddns:1703608
    DOI: 10.1155/2017/1703608
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    References listed on IDEAS

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    Cited by:

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    2. Zhong, Shaopeng & Cheng, Rong & Jiang, Yu & Wang, Zhong & Larsen, Allan & Nielsen, Otto Anker, 2020. "Risk-averse optimization of disaster relief facility location and vehicle routing under stochastic demand," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).

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