Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/3539
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dc.creatorOrlin, James B.-
dc.creatorPunnen, Abraham P.-
dc.creatorSchulz, Andreas S.-
dc.date2003-08-15T19:49:25Z-
dc.date2003-08-15T19:49:25Z-
dc.date2003-08-15T19:49:25Z-
dc.date.accessioned2013-06-04T16:19:48Z-
dc.date.available2013-06-04T16:19:48Z-
dc.date.issued2013-06-05-
dc.identifierhttp://hdl.handle.net/1721.1/3539-
dc.identifier.urihttp://koha.mediu.edu.my:8181/xmlui/handle/1721-
dc.descriptionLocal search algorithms for combinatorial optimization problems are in general of pseudopolynomial running time and polynomial-time algorithms are often not known for finding locally optimal solutions for NP-hard optimization problems. We introduce the concept of epsilon-local optimality and show that an epsilon-local optimum can be identified in time polynomial in the problem size and 1/epsilon whenever the corresponding neighborhood can be searched in polynomial time, for epsilon > 0. If the neighborhood can be searched in polynomial time for a delta-local optimum, we present an algorithm that produces a (delta+epsilon)-local optimum in time polynomial in the problem size and 1/epsilon. As a consequence, a combinatorial optimization problem has a fully polynomial-time approximation scheme if and only if it has a fully polynomial-time augmentation schem-
dc.format173594 bytes-
dc.formatapplication/pdf-
dc.languageen_US-
dc.relationMIT Sloan School of Management Working Paper;4325-03-
dc.subjectLocal Search-
dc.subjectNeighborhood Search-
dc.subjectApproximation Algorithms-
dc.subjectComputational Complexity-
dc.subjectCombinatorial Optimization-
dc.subject0/1-Integer Programming-
dc.titleApproximate Local Search in Combinatorial Optimization-
dc.typeWorking Paper-
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