Artikel

A green vehicle routing problem with customer satisfaction criteria

This paper develops an MILP model, named Satisfactory-Green Vehicle Routing Problem. It consists of routing a heterogeneous fleet of vehicles in order to serve a set of customers within predefined time windows. In this model in addition to the traditional objective of the VRP, both the pollution and customers' satisfaction have been taken into account. Meanwhile, the introduced model prepares an effective dashboard for decision-makers that determines appropriate routes, the best mixed fleet, speed and idle time of vehicles. Additionally, some new factors evaluate the greening of each decision based on three criteria. This model applies piecewise linear functions (PLFs) to linearize a nonlinear fuzzy interval for incorporating customers' satisfaction into other linear objectives. We have presented a mixed integer linear programming formulation for the S-GVRP. This model enriches managerial insights by providing trade-offs between customers' satisfaction, total costs and emission levels. Finally, we have provided a numerical study for showing the applicability of the model.

Sprache
Englisch

Erschienen in
Journal: Journal of Industrial Engineering International ; ISSN: 2251-712X ; Volume: 12 ; Year: 2016 ; Pages: 529-544 ; Heidelberg: Springer

Klassifikation
Management
Thema
Green vehicle routing problem (GVRP)
Customer satisfaction
Time windows
Piecewise linear functions (PLFs)
Sustainable logistics
Environment

Ereignis
Geistige Schöpfung
(wer)
Afshar-Bakeshloo, M.
Mehrabi, A.
Safari, H.
Maleki, M.
Jolai, F.
Ereignis
Veröffentlichung
(wer)
Springer
(wo)
Heidelberg
(wann)
2016

DOI
doi:10.1007/s40092-016-0163-9
Handle
Letzte Aktualisierung
10.03.2025, 11:44 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Artikel

Beteiligte

  • Afshar-Bakeshloo, M.
  • Mehrabi, A.
  • Safari, H.
  • Maleki, M.
  • Jolai, F.
  • Springer

Entstanden

  • 2016

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