Fast optimization algorithms for complex personnel scheduling problems

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Kronos Canadian Systems Inc. commercializes the Workforce Scheduler software to more than 1,100 organizations across the world, including more than 100 in Canada. This software allows to determine the work shift schedules of employees in various domains including retail, healthcare, leisure and hospitality, and manufacturing. Personnel shift scheduling is a complex combinatorial optimization problem that involves determining for each available employee his working days, the exact shift to work on each working day, and the job(s) to perform in each shift, in order to cover at best the demand in employees for each job. At Kronos, this problem is solved by a mathematical-programming-based optimization algorithm whose core strategies have been developed many years ago. To make the algorithm more robust to the recently integrated complex features, we propose to develop in this project new core strategies, namely, a new decomposition algorithm to split the problem into subproblems, improvement algorithms for solving each subproblem, and a new shift enumeration algorithm. Our main objective is to conceive an efficient and robust algorithm that will be able to solve the practical problem instances encountered by Kronos' clients. To achieve this goal, we will perform mathematical modeling, data analysis, and methodological developments that will involve integer programming, local search, large neighborhood search, and machine learning among others. The successful results from this research will be integrated into the Workforce Scheduler software. Given that the proposed developments will be at the heart of this software, they will provide a commercial advantage to Kronos that will be in a position to offer an improved software capable of solving large and complex personnel scheduling problems. A Canadian company will thus benefit directly from the positive impacts of this project. Moreover, a large number of Canadian companies/organizations which already use Workforce Scheduler will also benefit indirectly from this project when they will gain access to the new software version. Finally, this project will finance the training of seven MSc, PhD and postdoc students.