Skip to Main content Skip to Navigation
Journal articles

The capacitated vehicle routing problem with evidential demands

Abstract : We propose to represent uncertainty on customer demands in the Capacitated Vehicle Routing Problem (CVRP) using the theory of evidence. To tackle this problem, we extend classical stochastic programming modelling approaches. Specifically, we propose two models for this problem. The first model is an extension of the chance-constrained programming approach, which imposes certain minimum bounds on the belief and plausibility that the sum of the demands on each route respects the vehicle capacity. The second model extends the stochas-tic programming with recourse approach: for each route, it represents by a belief function the uncertainty on its recourses, i.e., corrective actions performed when the vehicle capacity is exceeded, and defines the cost of a route as its classical cost (without recourse) plus the worst expected cost of its recourses. We solve the proposed models using a metaheuristic algorithm and present experimental results on instances adapted from a well-known CVRP data set.
Complete list of metadatas

Cited literature [58 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-02542697
Contributor : Daniel Porumbel <>
Submitted on : Wednesday, April 29, 2020 - 12:20:48 PM
Last modification on : Monday, May 4, 2020 - 9:18:28 AM

File

CVRPED_final.pdf
Files produced by the author(s)

Identifiers

Citation

Nathalie Helal, Frédéric Pichon, Daniel Porumbel, David Mercier, Eric Lefevre. The capacitated vehicle routing problem with evidential demands. International Journal of Approximate Reasoning, Elsevier, 2018, 95, pp.124-151. ⟨10.1016/j.ijar.2018.02.003⟩. ⟨hal-02542697⟩

Share

Metrics

Record views

37

Files downloads

16