Ph.D. Position in Optimization (Exact Algorithms for Routing Problems)
We are seeking a candidate for a Ph.D. position in optimization, focusing on the development of exact algorithms for routing problems.
Research Project
This project aims to design advanced mathematical models and exact solution methods for a broad class of routing problems, including pickup-and-delivery networks and multi-echelon distribution systems. Potential applications include urban logistics, collaborative distribution, and emergency evacuation planning. These problems will be modeled using set-partitioning formulations with route-based variables, and solved using advanced exact methods (e.g., decomposition approaches such as branch-and-price). The research objectives are to: (i) propose and model new logistics systems, (ii) develop state-of-the-art exact algorithms, (iii) solve large-scale instances, and (iv) derive both algorithmic and managerial insights.
Candidate Profile
Applicants should have:
• A Master’s degree in operations research, computer science, industrial engineering, or a related field;
• Good programming skills (e.g., Python, C++, or similar);
• An interest in mathematical modeling and combinatorial optimization.
A knowledge in optimization algorithms as well as an experience with integer programming, network optimization, or decomposition methods is an asset but not required.
Program
The selected candidate will be enrolled in the joint Ph.D. program in administration at Université du Québec à Montréal. The program typically lasts four years, including one year of advanced coursework followed by three years of research. Students are generally expected to publish (or submit) two to three papers in leading scientific journals during their Ph.D.
Environment
The student will be supervised by Professor Marilène Cherkesly, an expert in exact algorithms for routing problems. They will be a iliated with leading international research groups, including CIRRELT, GERAD, and CRI2GS. The research environment is highly dynamic, collaborative, and supportive. The student will interact regularly with a vibrant community of graduate students and researchers, benefit from frequent seminars and workshops, and have opportunities to collaborate with internationally recognized experts. The environment combines strong methodological expertise with a collegial and engaging atmosphere.
Application
Interested candidates should send the following to Prof. Cherkesly (cherkesly.marilene@uqam.ca):
• Curriculum vitae, clearly detailing prior experience in optimization (e.g., projects, internships, publications) and specifying the Master’s supervisor(s) and research topic;
• Academic transcripts (including Master’s);
• A brief statement of research interests (max. 1 page), including motivation for pursuing a Ph.D. and interest in studying in Montréal;
• Contact information for references.
Applications will be reviewed on a rolling basis until the position is filled.