Home > Research > Publications & Outputs > The Time-Dependent Multiple-Vehicle Prize-Colle...

Electronic data

View graph of relations

The Time-Dependent Multiple-Vehicle Prize-Collecting Arc Routing Problem

Research output: Working paper

Unpublished

Standard

Harvard

APA

Vancouver

Author

Bibtex

@techreport{ae1d71cae30848a08c6b5c6833cf0032,
title = "The Time-Dependent Multiple-Vehicle Prize-Collecting Arc Routing Problem",
abstract = "In this paper, we introduce a multi vehicle version of the Time-Dependent Prize-Collecting Arc Routing Problem (TD-MPARP). It is inspired by a situation where a transport manager has to choose between a number of full truck load pick-ups and deliveries to be performed by a fleet of vehicles. Real-life traffic situations where the travel times change with the time of day are taken into account.Two metaheuristic algorithms, one based on Variable Neighborhood Search and one based on Tabu Search, are proposed and tested for a set of benchmark problems, generated from real road networks and travel time information. Bothalgorithms are capable of finding good solutions, though the Tabu Search approach generally shows better performance for large instances whereas the VNS is superior for small instances. We discuss the structural differences of theimplementation of the algorithms which explain these results.",
author = "Daniel Black and Richard Eglese and Sanne W{\o}hlk",
year = "2015",
language = "English",
type = "WorkingPaper",

}

RIS

TY - UNPB

T1 - The Time-Dependent Multiple-Vehicle Prize-Collecting Arc Routing Problem

AU - Black, Daniel

AU - Eglese, Richard

AU - Wøhlk, Sanne

PY - 2015

Y1 - 2015

N2 - In this paper, we introduce a multi vehicle version of the Time-Dependent Prize-Collecting Arc Routing Problem (TD-MPARP). It is inspired by a situation where a transport manager has to choose between a number of full truck load pick-ups and deliveries to be performed by a fleet of vehicles. Real-life traffic situations where the travel times change with the time of day are taken into account.Two metaheuristic algorithms, one based on Variable Neighborhood Search and one based on Tabu Search, are proposed and tested for a set of benchmark problems, generated from real road networks and travel time information. Bothalgorithms are capable of finding good solutions, though the Tabu Search approach generally shows better performance for large instances whereas the VNS is superior for small instances. We discuss the structural differences of theimplementation of the algorithms which explain these results.

AB - In this paper, we introduce a multi vehicle version of the Time-Dependent Prize-Collecting Arc Routing Problem (TD-MPARP). It is inspired by a situation where a transport manager has to choose between a number of full truck load pick-ups and deliveries to be performed by a fleet of vehicles. Real-life traffic situations where the travel times change with the time of day are taken into account.Two metaheuristic algorithms, one based on Variable Neighborhood Search and one based on Tabu Search, are proposed and tested for a set of benchmark problems, generated from real road networks and travel time information. Bothalgorithms are capable of finding good solutions, though the Tabu Search approach generally shows better performance for large instances whereas the VNS is superior for small instances. We discuss the structural differences of theimplementation of the algorithms which explain these results.

M3 - Working paper

BT - The Time-Dependent Multiple-Vehicle Prize-Collecting Arc Routing Problem

ER -