Automatic Configuration of MIP Solver: Case Study in Vertical Flight Planning
نویسندگان
چکیده
Mixed Integer Programming (MIP) solvers are highly parameterized and randomized matheuristic algorithms. How to properly design experiments for algorithm comparison using MIP solvers is an important topic. In this work, we analyze the performance variability of MIP solvers due to random seed settings and parameter configurations. The application domain is the vertical flight planning problem (VFP), which concerns assigning optimal cruise altitude and speed to each trajectory-composing segment, such that the fuel consumption is minimized, and the arrival time constraints are satisfied. Three classic piecewise linear techniques underlying VFP are compared, and their effectiveness highly depends on the solver parameter setting.
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