Time-dependent rural postman problem: time-space network formulation and genetic algorithm

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Jianbin Xin - (Author)
  • Benyang Yu - (Author)
  • Andrea D’Ariano - (Author)
  • Heshan Wang - (Author)
  • Meng Wang - , Delft University of Technology (Author)

Abstract

In this paper, a new time-space network model is proposed for addressing the time-dependent rural postman problem (TDRPP) of a single vehicle. The proposed model follows the idea of arc-path alternation to form a feasible and complete route. Based on the proposed model, the time dependency of the TDRPP is better described to capture its dynamic process, compared to the existing methods using a piecewise constant function with limited intervals. Furthermore, the property of first-in-first-out (FIFO) can be satisfied with the time spent on each arc. We investigate the FIFO property for the considered time-dependent network and key optimality property for the TDRPP. Based on this property, a dedicated genetic algorithm (GA) is proposed to efficiently solve the considered TDRPP that suffers from computational intractability for large-scale cases. Comprehensive simulation experiments are conducted for various time-dependent networks to show the effectiveness of the proposed GA.

Details

Original languageEnglish
Pages (from-to)2943-2972
Number of pages30
Journal Operational research : an international journal
Volume22
Issue number3
Publication statusPublished - Jul 2022
Peer-reviewedYes
Externally publishedYes

External IDs

Scopus 85105369496
Mendeley f60258db-7076-3b48-99e2-c01415ec0b3b

Keywords