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<p class="MsoNormal">Hi, CS graduate students,<o:p></o:p></p>
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<p class="MsoNormal" style="text-indent:9.75pt">Dr. Antonio Medrano will be the second speaker in the CSCI Research Seminar Series. The title and abstract are as follows.
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<p class="MsoNormal" style="text-indent:9.75pt"> Thanks,<o:p></o:p></p>
<p class="MsoNormal" style="text-indent:9.75pt"><o:p> </o:p></p>
<p class="MsoNormal" style="text-indent:9.75pt">Longzhuang<o:p></o:p></p>
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<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><b><span style="font-size:24.0pt">CSCI Research Seminar Series --- Dr. Antonio Medrano<o:p></o:p></span></b></p>
<p class="MsoNormal">Long Li 1:00 PM - 2:00 PM Friday, Oct 1 2021 (UTC-05:00) Central Time (US & Canada)<o:p></o:p></p>
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<p class="MsoNormal" style="margin-left:.5in">ZBcgAwVj226 (92242985 from phones)<o:p></o:p></p>
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<p class="MsoNormal" style="margin-left:.5in">326651 <o:p></o:p></p>
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<p class="MsoNormal"><b>The Complete Vertex <i>p</i>-Center Problem<o:p></o:p></b></p>
<p class="MsoNormal"><span style="font-size:11.5pt">The vertex <i>p</i>-center problem consists of locating
<i>p</i> facilities among a set of <i>M</i> potential sites such that the maximum distance from any demand to its closest located facility is minimized. The complete vertex
<i>p</i>-center problem solves the <i>p</i>-center problem for all <i>p</i> from 1 to the total number of sites, resulting in a multi-objective trade-off curve between the number of facilities and the service distance required to achieve full coverage. This
trade-off provides a reference to planners and decision-makers, enabling them to easily visualize the consequences of choosing different coverage design criteria for the given spatial configuration of the problem. This is important for location optimization
applications such as locating cell-phone towers, fire station locations, and drone delivery services. I present two fast algorithms for solving the complete
<i>p</i>-center problem, one using the classical formulation but trimming variables while still maintaining optimality, the other converting the problem to a location set covering problem and solving for all distances in the distance matrix. I will also discuss
scenarios where it makes sense to solve the problem via brute-force enumeration. All methods result in significant speed-ups, with the set covering method reducing computation times by many orders of magnitude.</span><o:p></o:p></p>
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