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DTSTAMP:20260828T214212Z
LAST-MODIFIED:20121116T203436Z
DTSTART:20090731T154500Z
DTEND:20090731T164500Z
UID:event467@bu.edu
URL:http://physics.bu.edu/internal/events/show/467
SUMMARY:Making Really Hard Modeling Problems Much Easier
DESCRIPTION:Featuring Scott Kirkpatrick\, Hebrew Univerisity (formerly IBM)
	\nHosted by: H. Eugene Stanley\n\nPart of the Biophysics/Condensed Matter S
	eminar Series.\n\nAbstract:\nPhysically-motivated modeling underlies our ef
	forts to understand\nbiomolecule structures from their genetic recipes\, to
	 assemble large\ncollections of fragmented and overlapping genetic data int
	o coherent\nwholes\, or to search for stable strategies in complex\, turbul
	ent\neconomic markets.  These large problems are difficult because of the\n
	cumbersome representations that their state requires\, and the\ncombinatori
	c explosion of possibilities that must be searched.  In the\npast 25 years 
	or so\, progress in these areas has often involved taking\nthe physical pic
	ture and intuitions of the more complicated problems\ndown to label an unde
	rlying (and still difficult) combinatorial problem\,\nin order to discover 
	is some combination of intelligent moves\, pruning\,\nand better cost funct
	ion characterization can make the problems far\neasier.  Some fairly genera
	l examples now exist of how to tell is a\nproblem is really hard\, and ther
	e are general strategies to follow in\nfinding effective heuristics.  The T
	ravelling Salesman Problem has long\nbeen studied from this point of view a
	nd a less familiar problem\,\nfinding coverings\, independent sets\, and cl
	iques\, may have a similar\nbroad relevance.  I'll talk about some old and 
	some new work in both\nareas\, and show how these relate to the physical pr
	oblems.
LOCATION:SCI 352\, 590 Commonwealth Avenue\, 02215
STATUS:CONFIRMED
CLASS:PUBLIC
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