4 présentations

• 
  15h30 - 15h55

  Acquiring Constraints for a Non-linear Transmission Maintenance Scheduling Problem

  • Hugo Barral, prés., Polytechnique Montréal
  • Mohamed Gaha, Institut de recherche d’Hydro-Québec
  • Amira Dems, Institut de recherche d’Hydro-Québec
  • Alain Côté, Institut de recherche d’Hydro-Québec
  • Franklin Nguewouo, Institut de recherche d’Hydro-Québec
  • Quentin Cappart, Polytechnique Montréal

  Power network equipment can face defects and has to be maintained to ensure transmission network reliability. Once an equipment is withdrawn from the network, it becomes unavailable and can lead to power outages when other equipment fails. This problem is referred to as transmission maintenance scheduling problem (TMS) and remains a challenge for power utilities. Numerous combinatorial constraints must be satisfied to ensure the stability and the reliability of the network. While most of these constraints can be naturally formalized in constraint programming (CP), some complex constraints like transit-power limits are challenging to model. This paper proposes a methodology based on active constraint acquisition to reformulate these constraints. The acquisition is carried out using a simulator developed by Hydro-Québec (HQ) to compute the power-flow of their transmission network. The acquired constraints are integrated into a CP model to solve the HQ network's TMS problem. Our experimental results show the relevance of the methodology to learn transit-power constraints in an automated way. It allows HQ to schedule a maintenance plan for an instance that remained intractable until now. To our knowledge, it is the first time that active constraint acquisition is successfully used for the TMS problem in an industrial setting.

• 
  15h55 - 16h20

  Constraint programming applied to molecule generation

  • David Saikali, prés., Polytechnique Montreal
  • Gilles Pesant, Polytechnique Montréal

  Automated molecule generation is a necessary tool to distinguish useful molecules from the rest. A popular approach to this task has been to use the SMILES notation, a standardized one-dimensional representation, with little information loss. This allows us to apply powerful natural language processing (nlp) techniques to this new challenge. Constraint programming could be a very promising approach as it is capable of easily modelling strict rules like the ones required by the SMILES representation. The grammar constraint is perfectly suited for this task and allows us to respect the SMILES language with a few extra constraints. We also add other constraints to target desirable properties that we observed in different molecule data sets (molecular weight, carbon frequency, etc.)

• 
  16h20 - 16h45

  A Constraint Programming Model for Short-Term Underground Mine Planning with Integrated Maintenance Scheduling

  • Younes Aalian, prés., Polytechnique Montréal
  • Michel Gamache, Polytechnique Montréal
  • Gilles Pesant, Polytechnique Montréal

  Short-term underground mine planning significantly contributes to the efficiency of mining projects. This process involves assigning different machine types to associated mining activities and establishing their start times. Maintenance plays a critical role in ensuring the availability and reliability of mining equipment, reducing downtime, and ensuring its longevity. This paper introduces a Constraint Programming (CP) model for simultaneously scheduling mining and maintenance activities in underground mining operations.
  The proposed model considers operational and equipment maintenance constraints to generate efficient and reliable schedules. Additionally, the optimization model determines the optimal timing and sequence for performing equipment maintenance, aiming to minimize its impact on the short-term mine schedule makespan.
  A data set from an underground gold mine in Canada is used to evaluate our model. Experiments show the efficacy of the CP model in integrating short-term mine planning and maintenance scheduling in underground mining by producing optimal schedules in a short computation time. Additionally, our integrated scheduling approach outperforms the non-integrated scheduling method by generating schedules with lower makespans and more maintenance activities.

• 
  16h45 - 17h10

  A Constraint Programming Model for the Electric Bus Assignment Problem with Parking Constraints

  • Mathis Azéma, École Polytechnique, Palaiseau, France
  • Guy Desaulniers, GERAD - Polytechnique Montréal
  • Jorge Mendoza, HEC Montréal
  • Gilles Pesant, prés., Polytechnique Montréal

  Electric buses serve as a key leverage in mitigating the transportation sector's carbon footprint. However, they pose a challenge, requiring transit agencies to adapt to a new operational approach. In particular, the assignment of buses to trips is more complex because it must consider the planning of the recharging activities. Unlike diesel buses, electric buses have less autonomy and take longer to refuel. In this paper, we address the assignment of electric buses to trips and the scheduling of charging events, taking into account parking constraints at the depot (a novelty in the literature). These constraints are particularly relevant in countries such as Canada where the buses are parked indoors to shelter them from harsh winter conditions. This problem, called the electric Bus Assignment Problem with Parking Constraints (eBAP-PC), is a feasibility problem. We propose a Constraint Programming model to solve it and compare it to mixed-integer linear programming approaches. In particular, we show its benefits for solving this problem with a one-day horizon and minimum end-of-day charge level constraints.