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UID:www.tcs.tifr.res.in/event/398
DTSTAMP:20230914T125923Z
SUMMARY:Static vs Adjustable Solutions in Dynamic Optimization
DESCRIPTION:Speaker: Vineet Goyal (Columbia University\nIndustrial Engineer
ing and Operations Research\n500 West\, 120th Street\nNew York\, NY 10027\
nUnited States of America)\n\nAbstract: \nWe study the performance of stat
ic solutions for two-stage adjustable robust linear optimization problems
with uncertain constraint and objective coefficients and give a tight char
acterization of the adaptivity gap. Computing an optimal adjustable robust
optimization problem is often intractable\, but a static solution can be
computed efficiently in most cases. We show that for a fairly general clas
s of uncertainty sets\, a static solution is optimal for the two-stage adj
ustable robust linear optimization problem. Furthermore\, when a static so
lution is not optimal\, we give a tight approximation bound on the perform
ance of the static solution that is related to a measure of non-convexity
of a transformation of the uncertainty set. We also show that our bound is
at least as good (and in many case significantly better) as the bound giv
en by the symmetry of the uncertainty set.\n \n
URL:https://www.tcs.tifr.res.in/web/events/398
DTSTART;TZID=Asia/Kolkata:20130828T170000
DTEND;TZID=Asia/Kolkata:20130828T180000
LOCATION:AG-69
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