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 language | English |
|---|---|
| Pages (from-to) | 146-166 |
| Number of pages | 21 |
| Journal | Transportation Research Part E: Logistics and Transportation Review |
| Volume | 88 |
| DOIs | |
| State | Published - 1 Apr 2016 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
Keywords
- CO emissions
- Green logistics
- Hybrid optimization
- Matheuristics
- Mixed integer programming
- Vehicle routing
- Vehicle scheduling
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