A unified framework for rich routing problems with stochastic demands

Markov, Iliya (Ecole Polytechnique Fédérale de Lausanne, Switzerland) ; Bierlaire, Michel (Ecole Polytechnique Fédérale de Lausanne, Switzerland) ; Cordeau, Jean-François (CIRRELT and HEC Montréal, Canada) ; Maknoon, Yousef (Delft University of Technology, The Netherlands) ; Varone, Sacha (Haute école de gestion de Genève, HES-SO // Haute Ecole Spécialisée de Suisse Occidentale)

We introduce a unified framework for rich vehicle and inventory routing problems with complex physical and temporal constraints. Demands are stochastic, can be non-stationary, and are forecast using any model that provides the expected demands and their error term distribution, which can be any theoretical or empirical distribution. We offer a detailed discussion on the modeling of demand stochasticity, focusing on the probabilities and cost effects of undesirable events, such as stock-outs, breakdowns and route failures, and their associated recourse actions. Tractability is achieved through the ability to pre-compute or at least partially pre-process the stochastic information, which is possible under mild assumptions for a general inventory policy. We integrate the stochastic aspect into a mixed integer non-linear program, illustrate applications to various problem classes, and show how to model specific problems through the lens of inventory routing. The case study is based on two sets of realistic instances, representing a waste collection inventory routing problem and a facility maintenance problem, respectively. We analyze the effects of our assumptions on modeling realism and tractability, and demonstrate that our framework significantly outperforms deterministic policies in its ability to limit the number of undesirable events for the same routing cost.


Keywords:
Article Type:
scientifique
Faculty:
Economie et Services
School:
HEG - Genève
Institute:
CRAG - Centre de Recherche Appliquée en Gestion
Subject(s):
Economie/gestion
Date:
2018-08
Pagination:
28 p.
Published in:
Transportation Research Part B: Methodological
Numeration (vol. no.):
2018, vol. 114, pp. 213-240
DOI:
ISSN:
0191-2615
Appears in Collection:

Note: The status of this file is: public


 Record created 2019-05-24, last modified 2019-06-07

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