David Schindl
PhD in mathematics
david.schindl@unifr.ch
https://orcid.org/0000-0002-7009-5530
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Lecturer,
Department of Informatics
PER 21 bu. C321
Bd de Pérolles 90
1700 FribourgPER 21, C321
Graph theory, discrete optimization (applications in logistics, supply chain, vehicle routes, scheduling/timetabling, etc.), statistics.
Biography
I obtained my PhD in mathematics from EPFL in 2004. After a 3-year postdoc at the Group for Research in Decision Analysis (GERAD) in Montreal, I was hired in 2008 at the Haute Ecole de Gestion (HEG) in Geneva, my main employer, where I am currently a lecturer.
My areas of research are graph theory and combinatorial optimization, with applications in logistics, vehicle routing and scheduling. In particular, since 2012 I have been in charge of course and exam timetabling at the HEG.
My teaching areas are decision support and graph theory (UniFR), and statistics and mathematics applied to economics (HEG).
Research and publications
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Publications
30 publications
Extremal Chemical Graphs for the Arithmetic-Geometric Index
Match Communications in Mathematical and in Computer Chemistry (2025) | Journal article -
Research projects
Efficient and sustainable waste collection
Status: CompletedStart 01.09.2019 End 31.08.2022 Funding Innovation In Swiss municipalities, a curbside system is often used to collect the non-recoverable solid waste. In principle, the trucks stop at every household for the collection. Due to the many stops of the heavy trucks, this classic strategy causes high fuel consumption, emissions and noise.
The objective of this project is to improve the municipal solid waste collection process by designing efficient and sustainable waste collection strategies targeted to the needs of the municipalities. This objective is pursued through the following three components. First, new waste collection concepts are proposed using modern physical waste collection elements, such as electric vehicles and containers with compressors. For example, small, agile vehicles may bring the garbage bags to larger containers in intermediate depots and large vehicles may then regularly discharge these containers. Second, mathematical models and optimization algorithms are developed for deciding how to design a waste collection concept for a given municipality in the best possible way. Typical decisions are about the locations of the waste collection points, the types of vehicles used to collect the waste at all collection points and the routing of each vehicle. Third, an interactive decision support tool is developed. It enables to specify the inputs, such as the street network and the waste quantities, and to display the results of the optimization algorithms for all alternatives. This tool will help the decision-makers to choose the best waste collection concept for their municipality.