Scheduling problems arise in a wide-range of applications that require finding the best possible sequence to perform a set of tasks, including job shop scheduling and flight scheduling. However, this problem is NP-complete, and solving large-scale problems efficiently can require expert knowledge and insights. Leveraging our experience and insights from applying these algorithms, we present recommendations and techniques to efficiently solve large-scale problems, including:

• Gurobi features that increase solver performance for optimal scheduling

• Tips on formulations for real-world scheduling problems, including sample problems

• Implementation and tuning tricks for scheduling problems with linear and non-linear constraints

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