Uncertainty Management Using Sequential Parameter Optimization

Sequential Parameter Optimization (SPO) is a meta-model based search heuristic that combines classical and modern statistical techniques. It was originally developed for the analysis of search heuristics such as simulated annealing, particle swarm optimization and evolutionary algorithms [6]. Here, SPO itself will be used as a search heuristic, i.e., SPO is applied to the objective function directly. An introduction to the state-of-the-art R implementation of SPO, the so-called sequential parameter optimization toolbox (SPOT), is presented in [5].

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