Solving vehicle assignment problems by process-network synthesis to minimize cost and environmental impact of transportation

F. Friedler, Mate Barany, B. Bertók, Zoltan Kovacs, L. T. Fan

Research output: Contribution to journalArticle

22 Citations (Scopus)

Abstract

A method and software are proposed for optimal assignment of vehicles to transportation tasks in terms of total cost and emission. The assignment problem is transformed into a process-network synthesis problem that can be algorithmically handled by the P-graph framework. In the proposed method, each task is given by a set of attributes to be taken account in the assignment; this is also the case for each vehicle. The overall mileage is calculated as the sum of the lengths of all the routes to be travelled during, before, after, and between the tasks (Desaulniers et al. 1998; Baita et al. 2000). Cost and emission are assigned to the mileages of each vehicle type. In addition to the globally optimal solution of the assignment problem, the P-graph framework provides the n-best suboptimal solutions that can be ranked according to multiple criteria. The viability of the proposed method is illustrated by an example.

Original languageEnglish
Pages (from-to)637-642
Number of pages6
JournalClean Technologies and Environmental Policy
Volume13
Issue number4
DOIs
Publication statusPublished - Aug 2011

Fingerprint

Environmental impact
environmental impact
cost
Costs
viability
software
method
vehicle
attribute

Keywords

  • Combinatorial optimization
  • P-graph
  • Transportation
  • Vehicle assignment

ASJC Scopus subject areas

  • Environmental Chemistry
  • Environmental Engineering
  • Management, Monitoring, Policy and Law

Cite this

Solving vehicle assignment problems by process-network synthesis to minimize cost and environmental impact of transportation. / Friedler, F.; Barany, Mate; Bertók, B.; Kovacs, Zoltan; Fan, L. T.

In: Clean Technologies and Environmental Policy, Vol. 13, No. 4, 08.2011, p. 637-642.

Research output: Contribution to journalArticle

@article{681ba35b9b7f42e9bad08157eabf297f,
title = "Solving vehicle assignment problems by process-network synthesis to minimize cost and environmental impact of transportation",
abstract = "A method and software are proposed for optimal assignment of vehicles to transportation tasks in terms of total cost and emission. The assignment problem is transformed into a process-network synthesis problem that can be algorithmically handled by the P-graph framework. In the proposed method, each task is given by a set of attributes to be taken account in the assignment; this is also the case for each vehicle. The overall mileage is calculated as the sum of the lengths of all the routes to be travelled during, before, after, and between the tasks (Desaulniers et al. 1998; Baita et al. 2000). Cost and emission are assigned to the mileages of each vehicle type. In addition to the globally optimal solution of the assignment problem, the P-graph framework provides the n-best suboptimal solutions that can be ranked according to multiple criteria. The viability of the proposed method is illustrated by an example.",
keywords = "Combinatorial optimization, P-graph, Transportation, Vehicle assignment",
author = "F. Friedler and Mate Barany and B. Bert{\'o}k and Zoltan Kovacs and Fan, {L. T.}",
year = "2011",
month = "8",
doi = "10.1007/s10098-011-0348-2",
language = "English",
volume = "13",
pages = "637--642",
journal = "Clean Technologies and Environmental Policy",
issn = "1618-954X",
publisher = "Springer Verlag",
number = "4",

}

TY - JOUR

T1 - Solving vehicle assignment problems by process-network synthesis to minimize cost and environmental impact of transportation

AU - Friedler, F.

AU - Barany, Mate

AU - Bertók, B.

AU - Kovacs, Zoltan

AU - Fan, L. T.

PY - 2011/8

Y1 - 2011/8

N2 - A method and software are proposed for optimal assignment of vehicles to transportation tasks in terms of total cost and emission. The assignment problem is transformed into a process-network synthesis problem that can be algorithmically handled by the P-graph framework. In the proposed method, each task is given by a set of attributes to be taken account in the assignment; this is also the case for each vehicle. The overall mileage is calculated as the sum of the lengths of all the routes to be travelled during, before, after, and between the tasks (Desaulniers et al. 1998; Baita et al. 2000). Cost and emission are assigned to the mileages of each vehicle type. In addition to the globally optimal solution of the assignment problem, the P-graph framework provides the n-best suboptimal solutions that can be ranked according to multiple criteria. The viability of the proposed method is illustrated by an example.

AB - A method and software are proposed for optimal assignment of vehicles to transportation tasks in terms of total cost and emission. The assignment problem is transformed into a process-network synthesis problem that can be algorithmically handled by the P-graph framework. In the proposed method, each task is given by a set of attributes to be taken account in the assignment; this is also the case for each vehicle. The overall mileage is calculated as the sum of the lengths of all the routes to be travelled during, before, after, and between the tasks (Desaulniers et al. 1998; Baita et al. 2000). Cost and emission are assigned to the mileages of each vehicle type. In addition to the globally optimal solution of the assignment problem, the P-graph framework provides the n-best suboptimal solutions that can be ranked according to multiple criteria. The viability of the proposed method is illustrated by an example.

KW - Combinatorial optimization

KW - P-graph

KW - Transportation

KW - Vehicle assignment

UR - http://www.scopus.com/inward/record.url?scp=84875230240&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84875230240&partnerID=8YFLogxK

U2 - 10.1007/s10098-011-0348-2

DO - 10.1007/s10098-011-0348-2

M3 - Article

AN - SCOPUS:84875230240

VL - 13

SP - 637

EP - 642

JO - Clean Technologies and Environmental Policy

JF - Clean Technologies and Environmental Policy

SN - 1618-954X

IS - 4

ER -