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Section: New Results
A MILP approach to minimize the number of late jobs with and without machine availability constraints
The study in [14] investigates
scheduling problems that occur when the weighted number of
late jobs that are subject to deterministic machine
availability constraints have to be minimized. These
problems can be modeled as a more general job selection
problem. Cases with resumable, non-resumable, and
semi-resumable jobs as well as cases without availability
constraints are investigated. The proposed efficient mixed
integer linear programming approach includes possible
improvements to the model, notably specialized lifted
knapsack cover cuts. The method proves to be competitive
compared with existing dedicated methods: numerical
experiments on randomly generated instances show that all
350-job instances of the test bed are closed for the
well-known problem