Performance Analysis of Cyclical Simulated Annealing Algorithms |
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| Authors: | Sheldon?H.?Jacobson mailto:shj@uiuc.edu" title=" shj@uiuc.edu" itemprop=" email" data-track=" click" data-track-action=" Email author" data-track-label=" " >Email author,Shane?N.?Hall,Laura?A.?McLay,Jeffrey?E.?Orosz |
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| Affiliation: | (1) Department of Mechanical and Industrial Engineering, University of Illinois at Urbana-Champaign, 1206 West Green Street (MC 244), Urbana, IL 61801-2906, USA;(2) Ritchie Capital Management, Batavia, IL 60510, USA |
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| Abstract: | ![]()
Generalized hill climbing (GHC) algorithms provide a framework for modeling local search algorithms for addressing intractable discrete optimization problems. Measures for assessing the finite-time performance of GHC algorithms have been developed using this framework, including the expected number of iterations to visit a predetermined objective function value level. This paper analyzes how the expected number of iterations to visit a predetermined objective function value level can be estimated for cyclical simulated annealing. Cyclical simulated annealing uses a cooling schedule that cycles through a set of temperature values. Computational results with traveling salesman problem instances taken from TSPLIB show how the expected number of iterations to visit solutions with predetermined objective function levels can be estimated for cyclical simulated annealing.AMS 2000 Subject Classification 90-08 Computational Methods: Local Search, 90C59 Heuristics: Simulated Annealing |
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| Keywords: | local search algorithms heuristics simulated annealing cooling schedules |
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