Minimizing the carbon footprint for the time-dependent heterogeneous-fleet vehicle routing problem with alternative paths

Wan Yu Liu, Chun-Cheng Lin, Ching Ren Chiu, You Song Tsao, Qunwei Wang*

*Corresponding author for this work

Research output: Contribution to journalArticle

24 Scopus citations

Abstract

Torespondto the reduction of greenhouse gas emissions and global warming, this paper investigates the minimal-carbon-footprint time-dependent heterogeneous-fleet vehicle routing problem with alternative paths (MTHVRPP). This finds a route with the smallestcarbon footprint, instead of the shortestroute distance, which is the conventional approach, to serve a number of customers with a heterogeneous fleet of vehicles in cases wherethere may not be only one path between each pair of customers, and the vehicle speed differs at different times of the day. Inheriting from the NP-hardness of the vehicle routing problem, the MTHVRPP is also NP-hard. This paper further proposes a genetic algorithm (GA) to solve this problem. The solution representedbyour GA determines the customer serving ordering of each vehicle type. Then, the capacity check is used to classify multiple routes of each vehicle type, and the path selection determines the detailed paths of each route. Additionally, this paper improves the energy consumption model used for calculating the carbon footprint amount more precisely. Compared with the results without alternative paths, our experimental results show that the alternative path in this experimenthas a significant impact on the experimental results in terms of carbon footprint

Original languageEnglish
Pages (from-to)4658-4684
Number of pages27
JournalSustainability (Switzerland)
Volume6
Issue number7
DOIs
StatePublished - 1 Jan 2014

Keywords

  • Alternative path
  • Carbon footprint
  • Genetic algorithm
  • Heterogeneous fleet
  • Vehicle routing problem

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