Grant: Discovery Grants Program - Individual
University of Waterloo
$84,000.00
Efficient Algorithms for Combinatorial Optimization Problems in Networks and Beyond
FY 2022-23
Summary
Combinatorial optimization problems arise in many areas of everyday life where one needs to distribute scarce resources in a utility-maximizing fashion. Practical instances of relevant problems tend to be NP-hard, and are therefore likely intractable. This proposal focuses on the design of approximation algorithms as one way of addressing the intractability. Such algorithms are efficient and produce solutions whose quality is provably close to that of optimal solutions. In this proposal we focus on the rich subclass of discrete optimization problems that, interpreted broadly, arise in a network context. The long term goal of the proposed research program is to develop versatile and efficient techniques for the design of (approximation-) algorithms for problems in this class.The work proposed here naturally continues my existing research program. Research questions proposed focus mostly on two vibrant areas: (1) Approximate Network Design, and (2) Games in Networks. A typical optimization problem in (1) asks for a minimum-cost sub-graph of a given weighted network that satisfies certain connectivity requirements. This general model captures many classical examples (e.g., from Karp's original list of 21 NP-hard problems), and yet, impressive progress has been made over the last 5-10 years (examples can be found in Byrka et al.'s work on the approximability of the Steiner tree [J. ACM, 2013], or that of Sebo and Vygen on approximating TSP in graphic metrics [Combinatorica, 2014]). Area (2) studies the impact of selfish and strategic behaviour in a network context. As before, the area contains many celebrated results, like Nash's famous work on bargaining [Econometrica, 1950], Shapley & Shubik's study of the cooperative matching game [Int. J. Game Theory, 1971], and the more recent algorithmic extension of the previous two results to the network context due to Kleinberg & Tardos [STOC, 2008]. For each of these areas, I will outline short- and medium-term research goals that are appropriate for graduate students and whose resolution will allow me to make progress towards the proposed long-term goal of my agenda.While much of this proposal focuses on theoretical aspects of CO, the techniques described have significant practical impact. Some of the problems discussed here arose in direct collaboration with industrial partners. Thus, obtaining efficient implementations of theoretical results is a priority of my research.
Program
Discovery Grants Program - Individual
Recipient
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
RGPIN-2017-03956
Name nom
Koenemann, Jochen
Department département
Combinatorics and Optimization - Combinatorics and Optimization
Organization id
33
Institution établissement
University of Waterloo
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2022
Competition year année de concours
2017
Award amount
84000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
1507
Committee name en
Computer Science
Committee name fr
Sciences informatiques
Area of application code
802
Area of application group en
Information and communication services
Area of application group fr
Services d'information et de télécommunications
Area of application en
Information systems and technology
Area of application fr
Systèmes d'information et technologie de l'information
Research subject code
2700
Research subject group en
Information technology
Research subject group fr
Technologie de l'information
Research subject en
Information technology
Research subject fr
Technologie de l'information
Installment
inst:5;6
Partie
2
Nb partie
6
Application title
Efficient Algorithms for Combinatorial Optimization Problems in Networks and Beyond
Application summary
Combinatorial optimization problems arise in many areas of everyday life where one needs to distribute scarce resources in a utility-maximizing fashion. Practical instances of relevant problems tend to be NP-hard, and are therefore likely intractable. This proposal focuses on the design of approximation algorithms as one way of addressing the intractability. Such algorithms are efficient and produce solutions whose quality is provably close to that of optimal solutions. In this proposal we focus on the rich subclass of discrete optimization problems that, interpreted broadly, arise in a network context. The long term goal of the proposed research program is to develop versatile and efficient techniques for the design of (approximation-) algorithms for problems in this class.The work proposed here naturally continues my existing research program. Research questions proposed focus mostly on two vibrant areas: (1) Approximate Network Design, and (2) Games in Networks. A typical optimization problem in (1) asks for a minimum-cost sub-graph of a given weighted network that satisfies certain connectivity requirements. This general model captures many classical examples (e.g., from Karp's original list of 21 NP-hard problems), and yet, impressive progress has been made over the last 5-10 years (examples can be found in Byrka et al.'s work on the approximability of the Steiner tree [J. ACM, 2013], or that of Sebo and Vygen on approximating TSP in graphic metrics [Combinatorica, 2014]). Area (2) studies the impact of selfish and strategic behaviour in a network context. As before, the area contains many celebrated results, like Nash's famous work on bargaining [Econometrica, 1950], Shapley & Shubik's study of the cooperative matching game [Int. J. Game Theory, 1971], and the more recent algorithmic extension of the previous two results to the network context due to Kleinberg & Tardos [STOC, 2008]. For each of these areas, I will outline short- and medium-term research goals that are appropriate for graduate students and whose resolution will allow me to make progress towards the proposed long-term goal of my agenda.While much of this proposal focuses on theoretical aspects of CO, the techniques described have significant practical impact. Some of the problems discussed here arose in direct collaboration with industrial partners. Thus, obtaining efficient implementations of theoretical results is a priority of my research.