Meeting Time: October 24, 2024 at 6:00pm PDT

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Agenda Item

C.-1 24-2625 Presentation by the Superintendent of Schools, or designee to, and discussion with, the Board of Education, on Restructuring the District's Footprint including Optimal Location Analysis.

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    David Blum at October 23, 2024 at 6:39pm PDT

    This analysis is flawed.

    The locations of students are generated from some probability distribution (not clear what distribution). The location optimization must therefore be repeated many times, using newly randomized points in every repetition, to prevent overfitting to the random points. The result will be a heat map showing better and worse locations for sites, rather than point locations that are purported to be optimal. This is Monte Carlo simulation. Further, the repetitions will show how sensitive is the model to the unknown locations of students.

    Also, the analysis should show results when the constraints are relaxed (ie maximum number of schools, maximum number of students per school), in order to gain insight into the tradeoffs among the constraints.

    A single repetition using a single set of constraints might just as well be cherrypicked.