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- W1998728902 abstract "Discretization algorithms have been combined with discrete estimation of distribution algorithms (EDAs) to work on real-valued problems. Existing discretization algorithms, such as the fixed-height histogram (FHH) and the split-on-demand (SoD), utilize merely densities of selected chromosomes to build next-generation population, and therefore have limited exploration. This paper adds the concept of model building to FHH and SoD to solve these problems. The model utilizes a variety of information from selected chromosomes to improve the abilities of FHH and SoD to identify promising regions for future exploration. Specifically, a model of expected values of selected chromosomes is combined with FHH and SoD to form expected-value FHH and expected-value SoD. The expected-value-discretization algorithms outperform their original versions on an exploration test function as well as the 25 benchmark functions used in the SoD paper. This paper also introduces a model of differential-expected-value of selected chromosomes. The differential-expected-value FHH and differential-expected-value SoD outperform their expected-value versions when tested on the exploration test function and the 25 benchmark functions." @default.
- W1998728902 created "2016-06-24" @default.
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- W1998728902 date "2014-07-01" @default.
- W1998728902 modified "2023-09-24" @default.
- W1998728902 title "Use model building on discretization algorithms for discrete EDAs To work on real-valued problems" @default.
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- W1998728902 doi "https://doi.org/10.1109/cec.2014.6900282" @default.
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