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dc.contributor.authorWinker, Peteren_US
dc.description.abstractThreshold Accepting (TA) is a powerful optimization heuristic from the class of stochastic local search algorithms. It has been applied successfully to different optimization problems in statistics and econometrics, including the uniform design problem. Using the latter application as example, the stochastic properties of a TA implementation are analyzed. We provide a formal framework for the analysis of optimization heuristics like TA, which can be used to estimate lower bounds and to derive convergence results. It is also helpful for tuning real applications. Based on this framework, empirical results are presented for the uniform design problem. In particular, for two problem instances, the rate of convergence of the algorithm is estimated to be of the order of a power of -0.3 to -0.7 of the number of iterations.en_US
dc.relation.ispartofseriesDiscussion paper / Universität Erfurt, Staatswissenschaftliche Fakultät 2005,003Een_US
dc.subject.keywordHeuristic optimizationen_US
dc.subject.keywordThreshold Acceptingen_US
dc.subject.keywordStochastic analysis of heuristicsen_US
dc.subject.stwMathematische Optimierungen_US
dc.subject.stwStochastischer Prozessen_US
dc.subject.stwHeuristisches Verfahrenen_US
dc.subject.stwuniform design problemen_US
dc.titleThe Stochastics of Threshold Accepting: Analysis of an Application to the Uniform Design Problemen_US
dc.typeWorking Paperen_US
Appears in Collections:Discussion Papers, Staatswissenschaftliche Fakultät, Universität Erfurt

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