Context-aware, preference-based vehicle routing
Vehicle routing is an important service that is used by both private individuals and
commercial enterprises. Drivers may have different contexts that are characterized by …
commercial enterprises. Drivers may have different contexts that are characterized by …
Data driven vrp: A neural network model to learn hidden preferences for vrp
The traditional Capacitated Vehicle Routing Problem (CVRP) minimizes the total distance of
the routes under the capacity constraints of the vehicles. But more often, the objective …
the routes under the capacity constraints of the vehicles. But more often, the objective …
A collaborative method for route discovery using taxi drivers' experience and preferences
This paper presents a collaborative route discovery method that leverages the experience
and preferences of taxi drivers in urban areas. The proposed method is mainly comprised of …
and preferences of taxi drivers in urban areas. The proposed method is mainly comprised of …
Optimization for classical machine learning problems on the gpu
Constrained optimization problems arise frequently in classical machine learning. There
exist frameworks addressing constrained optimization, for instance, CVXPY and GENO …
exist frameworks addressing constrained optimization, for instance, CVXPY and GENO …
Personal routes with high-dimensional costs and dynamic approximation guarantees
In a personalized route planning query, a user can specify how relevant different criteria as
travel time, gas consumption, scenicness, etc. are for his individual definition of an optimal …
travel time, gas consumption, scenicness, etc. are for his individual definition of an optimal …
Map matching for semi-restricted trajectories
T Behr, TC van Dijk, A Forsch… - … GIScience 2021)-Part …, 2021 - drops.dagstuhl.de
We consider the problem of matching trajectories to a road map, giving particular
consideration to trajectories that do not exclusively follow the underlying network. Such …
consideration to trajectories that do not exclusively follow the underlying network. Such …
Scalable unsupervised multi-criteria trajectory segmentation and driving preference mining
We present analysis techniques for large trajectory data sets that aim to provide a semantic
understanding of trajectories reaching beyond them being point sequences in time and …
understanding of trajectories reaching beyond them being point sequences in time and …
Preference-based trajectory clustering-an application of geometric hitting sets
In a road network with multicriteria edge costs we consider the problem of computing a
minimum number of driving preferences such that a given set of paths/trajectories is optimal …
minimum number of driving preferences such that a given set of paths/trajectories is optimal …
Learn and route: learning implicit preferences for vehicle routing
We investigate a learning decision support system for vehicle routing, where the routing
engine learns implicit preferences that human planners have when manually creating route …
engine learns implicit preferences that human planners have when manually creating route …
Inferring routing preferences from user-generated trajectories using a compression criterion
A Forsch, J Oehrlein, B Niedermann… - Journal of Spatial …, 2023 - 204.48.17.207
The optimal path between two vertices in a graph depends on the optimization objective,
which is often defined as a weighted sum of multiple criteria. When integrating two criteria …
which is often defined as a weighted sum of multiple criteria. When integrating two criteria …