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

Yiyong Xiao and Abdullah Konak

Transportation Research Part E: Logistics and Transportation Review, 2016, vol. 88, issue C, 146-166

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.

Keywords: CO2 emissions; Vehicle routing; Vehicle scheduling; Green logistics; Mixed integer programming; Hybrid optimization; Matheuristics (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (44)

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DOI: 10.1016/j.tre.2016.01.011

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