Urban hazmat transportation with multi-factor

Jiaoman Du, Xiang Li, Changjing Shang, Lei Li

Research output: Contribution to journalArticlepeer-review

6 Citations (SciVal)
215 Downloads (Pure)

Abstract

In this paper, an urban hazmat transportation problem considering multiple factors that tangle with real-world applications (i.e., weather conditions, traffic conditions, population density, time window, link closure and half link closure) is investigated. Based on multiple depot capacitated vehicle routing problem, we provide a multi-level programming formulation for urban hazmat transportation. To obtain the Pareto optimal solution, an improved biogeography-based optimization (improved BBO) algorithm is designed, comparing with the original BBO and genetic algorithm, with both simulated numerical examples and a real-world case study, demonstrating the effectiveness of the proposed approach
Original languageEnglish
Pages (from-to)6307-6328
Number of pages22
JournalSoft Computing
Volume24
Issue number9
Early online date01 Apr 2019
DOIs
Publication statusPublished - 01 May 2020

Keywords

  • urban hazmat transportation
  • multiple factors
  • multi-level programming
  • biogeography-based optimization
  • pareto optimization
  • Multi-level programming
  • Biogeography-based optimization
  • Urban hazmat transportation
  • Pareto optimization
  • Multiple factors

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