AIRO Young Opportunity
Expires
15 Aug 2021
Institution
Université Laval and Université du Québec à Montréal
Country
Canada
Description
Supervisors: Leandro Coelho (Université Laval) and Franklin Djeumou Fomeni (Université du
Québec à Montréal)
Start date: 1 January 2022
Duration: 4 years
Summary of the project:
Binary Quadratic Optimization (BQO) is a special class of discrete optimization, which amounts to
optimizing a quadratic objective function of binary decision variables subject to a set of linear
constraints. Some applications of BQO include portfolio optimization, projects selection, sustainable
development, facilities location and vehicle routing problems. BQO problems are known to be very
challenging to solve due to the non-linear nature of their objective functions and the discrete nature of
their decision variables. Indeed, even simple special cases of BQO, such as the quadratic knapsack
problem, the quadratic assignment problem, etc., are known to be strongly NP-hard. The aim of this
research project is to develop a host of innovating solution methodologies for solving BQO problems.
These methodologies will include heuristic, meta-heuristics and exact algorithms. Some of the
techniques to be used include, but not limited to, dynamic programming, cutting planes, polyhedral
studies, branch-and-cut and decision diagram.
We invite applications from highly motivated candidates for full-time PhD or Postdoc positions to
develop advanced methodologies for solving BQO problems and use them for some applications in
finance, in energy and in transportation.
Work environment:
The successful candidates will be jointly supervised by Leandro Coelho (professor at Université Laval
in Quebec City) and Franklin Djeumou Fomeni (professor at Université du Québec à Montréal,
UQAM, Montreal). They will also have the opportunity to become members of both GERAD
(www.gerad.ca) and CIRRELT (www.cirrelt.ca).
Qualifications:
Masters in Operations Research or equivalent
Knowledge of optimization methods (e.g.: heuristics, linear programming)
Programming skill: C/C++ (preferred) or Python/Matlab
Conditions:
A financial support of up to 22 000$ per year for PhD. For postdoc, it will be comensurate with
experience
Required documents:
Degrees certificates, Academic transcripts, CV, Cover letter and two reference letters
To apply: Email all documents to djeumou_fomeni.franklin@uqam.ca / leandro.coelho@fsa.ulaval.ca
Québec à Montréal)
Start date: 1 January 2022
Duration: 4 years
Summary of the project:
Binary Quadratic Optimization (BQO) is a special class of discrete optimization, which amounts to
optimizing a quadratic objective function of binary decision variables subject to a set of linear
constraints. Some applications of BQO include portfolio optimization, projects selection, sustainable
development, facilities location and vehicle routing problems. BQO problems are known to be very
challenging to solve due to the non-linear nature of their objective functions and the discrete nature of
their decision variables. Indeed, even simple special cases of BQO, such as the quadratic knapsack
problem, the quadratic assignment problem, etc., are known to be strongly NP-hard. The aim of this
research project is to develop a host of innovating solution methodologies for solving BQO problems.
These methodologies will include heuristic, meta-heuristics and exact algorithms. Some of the
techniques to be used include, but not limited to, dynamic programming, cutting planes, polyhedral
studies, branch-and-cut and decision diagram.
We invite applications from highly motivated candidates for full-time PhD or Postdoc positions to
develop advanced methodologies for solving BQO problems and use them for some applications in
finance, in energy and in transportation.
Work environment:
The successful candidates will be jointly supervised by Leandro Coelho (professor at Université Laval
in Quebec City) and Franklin Djeumou Fomeni (professor at Université du Québec à Montréal,
UQAM, Montreal). They will also have the opportunity to become members of both GERAD
(www.gerad.ca) and CIRRELT (www.cirrelt.ca).
Qualifications:
Masters in Operations Research or equivalent
Knowledge of optimization methods (e.g.: heuristics, linear programming)
Programming skill: C/C++ (preferred) or Python/Matlab
Conditions:
A financial support of up to 22 000$ per year for PhD. For postdoc, it will be comensurate with
experience
Required documents:
Degrees certificates, Academic transcripts, CV, Cover letter and two reference letters
To apply: Email all documents to djeumou_fomeni.franklin@uqam.ca / leandro.coelho@fsa.ulaval.ca