Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/3539
Title: Approximate Local Search in Combinatorial Optimization
Keywords: Local Search
Neighborhood Search
Approximation Algorithms
Computational Complexity
Combinatorial Optimization
0/1-Integer Programming
Issue Date: 5-Jun-2013
Description: Local 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
URI: http://koha.mediu.edu.my:8181/xmlui/handle/1721
Other Identifiers: http://hdl.handle.net/1721.1/3539
Appears in Collections:MIT Items

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