Emergency location-routing problem with uncertain demand under path risk

Hua Li Sun, Zhan Jie Zhou, Yao Feng Xue

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

The location-routing problem (LRP) is an important logistics problem in emergency management. Considering the risk of the extended traveling time, the risk of road connectivity, the road complexity and the demand uncertainty of relief supplies, a multi-objective optimization model based on the stochastic chance constrained programming was proposed to minimize the total transportation time and the total system cost. Then, an improved genetic algorithm (GA) with penalty function was presented to solve the optimization problem. The results of numerical examples show that the optimization model and the improved GA algorithm proposed in this paper are feasible and effective.

Original languageEnglish
Pages (from-to)962-966
Number of pages5
JournalShanghai Jiaotong Daxue Xuebao/Journal of Shanghai Jiaotong University
Volume47
Issue number6
StatePublished - Jun 2013

Keywords

  • Emergency logistics
  • Genetic algorithm
  • Location-routing problem (LRP)
  • Path risk
  • Stochastic chance constrained programming

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