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2006
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A Framework for Quasi-exact Optimization Using Relaxed Best-First Search

9 years 11 months ago
A Framework for Quasi-exact Optimization Using Relaxed Best-First Search
Abstract. In this paper, a framework for previous and new quasi-exact extensions of the A -algorithm is presented. In contrast to previous approaches, the new methods guarantee to expand every state at most once if guided by a socalled monotone heuristic. By that, they account more effectively for aspects of run time while still guaranteeing that the cost of the solution will not exceed the optimal cost by a certain factor. First a general upper bound for this factor is derived. This bound is (1 + ) N 2 where N is (an upper bound on) the maximum depth of the search. Next, we look at specific instances of the algorithm class described by our framework. For one of the new methods a linear, i.e. much tighter upper bound is obtained: the cost of the solution will not exceed the optimal cost by a factor greater than 1 + . The parameter 0 can be chosen by the user. Within a range of reasonable choices for , all new methods allow the user to trade off run time for solution quality. Besides t...
Rüdiger Ebendt, Rolf Drechsler
Added 14 Dec 2010
Updated 14 Dec 2010
Type Journal
Year 2006
Where KI
Authors Rüdiger Ebendt, Rolf Drechsler
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