The heterogeneous green vehicle routing and scheduling problem with time-varying traffic congestion

Yiyong Xiao, Abdullah Konak

Research output: Contribution to journalArticle

83 Scopus citations

Abstract

The green vehicle routing and scheduling problem (GVRSP) aims to minimize green-house gas emissions in logistics systems through better planning of deliveries/pickups made by a fleet of vehicles. We define a new mixed integer liner programming (MIP) model which considers heterogeneous vehicles, time-varying traffic congestion, customer/vehicle time window constraints, the impact of vehicle loads on emissions, and vehicle capacity/range constraints in the GVRSP. The proposed model allows vehicles to stop on arcs, which is shown to reduce emissions up to additional 8% on simulated data. A hybrid algorithm of MIP and iterated neighborhood search is proposed to solve the problem.

Original languageEnglish (US)
Pages (from-to)146-166
Number of pages21
JournalTransportation Research Part E: Logistics and Transportation Review
Volume88
DOIs
StatePublished - Apr 1 2016

All Science Journal Classification (ASJC) codes

  • Business and International Management
  • Civil and Structural Engineering
  • Transportation

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