The Robust Vehicle Routing Problem | A novel approach to uncertainty in a classical transportation problem with real life application

Ilgaz Sungur

ISBN 10: 3639125002 / ISBN 13: 9783639125009

Published by VDM Verlag Dr. Müller, 2009

About this Item

The Robust Vehicle Routing Problem | A novel approach to uncertainty in a classical transportation problem with real life application | Ilgaz Sungur | Taschenbuch | Englisch | VDM Verlag Dr. Müller | EAN 9783639125009 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Seller Inventory # 101661613

Bibliographic Details

• Title: The Robust Vehicle Routing Problem | A novel approach to uncertainty in a classical transportation problem with real life application
• Publisher: VDM Verlag Dr. Müller
• Publication Date: 2009
• Language: English
• ISBN 10: 3639125002
• ISBN 13: 9783639125009
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 7D millimeters 220 millimeters width by 150 millimeters height by 7 millimeters depth
• Weight: 198 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

The Vehicle Routing Problem (VRP) is a classical problem of routing a fleet of vehicles from a center to service a set of customers at minimum cost. VRP has been studied over several decades due to its numerous applications in the industry. Such real life routing problems contain a high degree of uncertainty. Most of the current methods to address uncertainty in VRP either require strong assumptions or increase the complexity of the model significantly. Robust optimization has recently emerged, increasingly in this decade, as a novel approach to model uncertainty: optimize against the worst-case scenario. This study contributes to the literature by proposing a routing model that uses robust optimization with simple assumptions to model uncertainty in demand and travel times without increasing the complexity of the formulation. We adapt this model for a real life courier delivery problem with stochastic service times and time windows (via robust optimization), and with probabilistic customers (via a recourse action). We then develop a heuristic for this large scale problem and obtain improved solutions than used in practice at a leading company in the industry.

About the Author

Ilgaz Sungur received Industrial Engineering degrees from Bogazici University (BS in 2003 and MS in 2004) and University of Southern California (PhD in 2007). His academic research was focused on optimization of large scale real life problems in transportation and planning. He is currently employed as a research scientist in the industry.