David Schindl
PhD in Mathematik
david.schindl@unifr.ch
https://orcid.org/0000-0002-7009-5530
Graphentheorie, diskrete Optimierung (Anwendungen in Logistik, Supply Chain, Fahrzeugtouren, Stundenplanung, ...), Statistik.
Lehrbeauftragte_r
Departement für Informatik
Bd de Pérolles 90
1700 Fribourg
Biografie
Ich habe 2004 meinen Doktortitel in Mathematik an der EPFL erworben. Nach drei Jahren als Postdoktorand bei der Group for Research in Decision Analysis (GERAD) in Montreal wurde ich 2008 an der Haute Ecole de Gestion (HEG) in Genf, meinem Hauptarbeitgeber, angestellt, wo ich derzeit als Maître d'enseignement tätig bin.
Meine Forschungsgebiete sind Graphentheorie und kombinatorische Optimierung mit Anwendungen in den Bereichen Logistik, Fahrzeugtouren und Stundenplanung. Insbesondere bin ich seit 2012 für die Erstellung der Vorlesungs- und Prüfungspläne der HSW zuständig.
Meine Lehrgebiete sind Entscheidungsunterstützung und Graphentheorie (UniFR), sowie Statistik und angewandte Wirtschaftsmathematik (HEG).
Forschung und Publikationen
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Publications
30 Publikationen
Extremal Chemical Graphs for the Arithmetic-Geometric Index
Match Communications in Mathematical and in Computer Chemistry (2025) | Artikel -
Forschungsprojekte
Efficient and sustainable waste collection
Status: AbgeschlossenBeginn 01.09.2019 Ende 31.08.2022 Finanzierung 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.