This paper presents a Variable Neighborhood Search algorithm for a Vehicle Routing Problem variant with a crowd-sourced delivery policy. We consider a heterogeneous fleet composed of conventional capacitated vehicles and some ordinary drivers, called occasional drivers, who accept to deviate from their route to deliver items to other people in exchange for a small compensation. The objective is to minimize total costs, that is conventional vehicles costs plus occasional drivers compensation. Our computational study shows that the Variable Neighborhood Search is highly effective and able to solve large-size instances within short computational times.
A variable neighborhood search for the vehicle routing problem with occasional drivers and time windows
Macrina G.;Di Puglia Pugliese L.;Guerriero F.
2020-01-01
Abstract
This paper presents a Variable Neighborhood Search algorithm for a Vehicle Routing Problem variant with a crowd-sourced delivery policy. We consider a heterogeneous fleet composed of conventional capacitated vehicles and some ordinary drivers, called occasional drivers, who accept to deviate from their route to deliver items to other people in exchange for a small compensation. The objective is to minimize total costs, that is conventional vehicles costs plus occasional drivers compensation. Our computational study shows that the Variable Neighborhood Search is highly effective and able to solve large-size instances within short computational times.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
