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dc.contributor.authorWinker, Peteren_US
dc.description.abstractThreshold Accepting (TA) is a powerful optimization heuristicfrom the class of stochastic local search algorithms. It has been appliedsuccessfully to different optimization problems in statistics andeconometrics, including the uniform design problem. Using the latterapplication as example, the stochastic properties of a TA implementationare analyzed. We provide a formal framework for the analysis ofoptimization heuristics like TA, which can be used to estimate lowerbounds and to derive convergence results. It is also helpful for tuningreal applications. Based on this framework, empirical results are presentedfor the uniform design problem. In particular, for two probleminstances, the rate of convergence of the algorithm is estimated to beof the order of a power of -0.3 to -0.7 of the number of iterations.en_US
dc.relation.ispartofseries|aDiscussion paper / Universität Erfurt, Staatswissenschaftliche Fakultät |x2005,003Een_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

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