An integer multi-objective optimization model and an enhanced non-dominated sorting genetic algorithm for contraflow scheduling problem

Pei Heng Li, Yingyan Lou

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

To determine the onset and duration of contraflow evacuation, a multi-objective optimization (MOO) model is proposed to explicitly consider both the total system evacuation time and the operation cost. A solution algorithm that enhances the popular evolutionary algorithm NSGA-II is proposed to solve the model. The algorithm incorporates preliminary results as prior information and includes a meta-model as an alternative to evaluation by simulation. Numerical analysis of a case study suggests that the proposed formulation and solution algorithm are valid, and the enhanced NSGA-II outperforms the original algorithm in both convergence to the true Pareto-optimal set and solution diversity.

Original languageEnglish (US)
Pages (from-to)2399-2405
Number of pages7
JournalJournal of Central South University
Volume22
Issue number6
DOIs
StatePublished - Jun 13 2015

Keywords

  • contraflow scheduling
  • hurricane evacuation
  • multi-objective optimization
  • NSGA-II

ASJC Scopus subject areas

  • Engineering(all)
  • Metals and Alloys

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