Search results for "Random optimization"

showing 2 items of 2 documents

Simulated Annealing in Bayesian Decision Theory

1992

Since the seminal paper by Kirkpatrick, Gelatt and Vechhi (1983), a number of papers in the scientific literature refer to simulated annealing as a powerful random optimization method which promises to deliver, within reasonable computing times, optimal or nearly optimal solutions to complex decision problems hitherto forbidding. The algorithm, which uses the physical process of annealing as a metaphor, is special in that, at each iteration, one may move with positive probability to solutions with higher values of the function to minimize, rather than directly jumping to the point with the smallest value within the neighborhood, thus drastically reducing the chances of getting trapped in lo…

Maxima and minimaMathematical optimizationBayes estimatorSimulated annealingBayesian probabilityRandom optimizationContext (language use)Decision problemAdaptive simulated annealingMathematics
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A multi-local optimization algorithm

1998

The development of efficient algorithms that provide all the local minima of a function is crucial to solve certain subproblems in many optimization methods. A “multi-local” optimization procedure using inexact line searches is presented, and numerical experiments are also reported. An application of the method to a semi-infinite programming procedure is included.

Statistics and ProbabilityContinuous optimizationMathematical optimizationInformation Systems and ManagementMeta-optimizationManagement Science and Operations ResearchSemi-infinite programmingMaxima and minimaVector optimizationModeling and SimulationDiscrete Mathematics and CombinatoricsRandom optimizationMulti-swarm optimizationAlgorithmMetaheuristicMathematicsTop
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