Current Projects

	Decision Diagrams for Discrete Optimization Problems This project explores the use of Decision Diagrams (DD) to solve discrete optimization problems, where a relaxed DD is used to represent a discrete relaxation of the problem.
	Mobile Robot Task Planning and Scheduling in Retirement Homes This project investigates the use of combinatorial optimization methods for the planning and scheduling of robot tasks within a retirement home environment.
	Constraint Programming for Strictly Convex Integer Quadratic Programs In this work we strengthen constraint programming to solve strictly convex integer quadratic programs with novel inference rules and search strategies.
	Hybrid Quantum-Classical Computing Algorithms The goal of this project is to explore and develop quantum computing and classical computing hybrid algorithms for combinatorial optimization problems.
	The Senior Transportation Problem This project studies a vehicle routing problem variation that arises from an on-demand transportation services for the seniors and handicapped.
	Problem Difficulty and the Phase Transition in Heuristic Search This project aims to understand the relationship between constrainedness and problem difficulty in heuristic search using the phase transition framework.
	Matching Problems within the Social Needs Marketplace This project aims at solving a matching problem within the social needs marketplace, combining approaches from the matching and queueing theory literatures.
	Resource Scheduling in Cloud Computing Environments Cloud computing environments are large, complex, and dynamic systems. We aim to increase efficiency of a back-end cloud in order to speed up service by using stochastic optimization techniques.

Past Projects

	Constraint Integer Programming This project aims at combining the advantages of constraint programming and mixed integer programming and developing a new method that computes the scheduling problem more efficiently.
	Design Patterns for AI Planning and Scheduling Applications This project aims at developing modern design patterns for automated planning & scheduling applications to speed up the design process of knowledge models
	Execution Monitoring of Rich Plan Representations This project focuses on Execution Monitoring (EM) for plans represented in a rich format, such as Partial Order Plans. The focus is on effective state evaluation and action selection for an agent acting in a world with uncertainty.
	Integration of Queueing and Scheduling The goal of this project is to develop an effective methodology for solving dynamic scheduling problems based on the integration of approaches from the scheduling literature and the queueing theory literature.
	Integration of Maintainence and Scheduling This project aims at integrating maintenance reasoning into production scheduling problems to improve the overall system performance through modeling the effect of equipment conditions on the production process.
	Learning Macro Actions for Artificial Intelligence Planning In this project, we introduce a learning approach to choose macro operators for remodeling planning domains per problem instance. Also, we remodel the planning domains similarly by removing basic operators as well as adding macros in an instance-specific context.
	Optimization in Forestry Logistics and Scheduling A collaboration between TIDEL and École Polytechnique (Montreal) to model and solve tactical problems in forestry logistics where uncertainty in travel time, service time, and inventory level are taken into account. We build the application using Constraint and Integer Programming, Simulation, and techniques in Heuristics.