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Algorithms the Dynamic Hoist Scheduling Problem with Multiple Hoists
The project develops new optimization methods for a complex industrial scheduling problem involving multiple hoists moving parts through electroplating tanks under strict timing and safety constraints. Unlike existing models, the project focuses on a dynamic setting where new tasks can appear during production and where multiple hoists share tracks and must coordinate movements. The work will produce an ILP formulation and lightweight heuristic algorithms capable of generating fast, near-optimal schedules that can scale to real factory environments. The collaboration between Politecnico di Milano and Concordia University strengthens shared expertise in discrete optimization and industrial scheduling, supports ongoing joint research, and brings advanced modeling techniques, practical algorithms, and industrial datasets to both institutions.
Faculty Supervisor:
Tommaso Schettini
Student:
Partner:
Politecnico di Milano
Discipline:
Computer science
Sector:
Education
University:
Concordia University
Program:
Globalink Research Award
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Mitacs is funded by the Government of Canada, the Government of Alberta, the Government of British Columbia, Research Manitoba, the Government of New Brunswick, the Government of Newfoundland and Labrador, the Government of Nova Scotia, the Government of Ontario, Innovation PEI, the Government of Quebec, the Government of Saskatchewan, and the Government of Yukon.