System and method for estimation of a distribution algorithm
First Claim
1. A method for optimization, comprising the steps of:
- (a) providing an initial population or a data set with a plurality of members respectively represented by parameter sets;
(b) applying one or a plurality of fitness functions to evaluate the quality of the members of the population;
(c) generating offspring of the population by means of a stochastic model using information from all members of the population;
(d) applying one or a plurality of fitness functions to evaluate the quality of the offspring with respect to the underlying problem of the optimization;
(e) selecting offspring, and (f) repeating steps (c) through (e) until the quality reaches a threshold value.
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Abstract
The underlying invention generally relates to the field of Estimation of Distribution Algorithm, especially to optimization problems, including single-objective optimization and Multi-Objective Optimization. The proposed method for optimization comprises six steps. In a first step it provides an initial population or a data set with a plurality of members respectively represented by parameter sets. Then one or a plurality of fitness functions are applied to evaluate the quality of the members of the population. In a third step offspring of the population is generated by means of a stochastic model using information from all members of the population. One or a plurality of fitness functions are applied to evaluate the quality of the offspring with respect to the underlying problem of the optimization. In a fifth step offspring is selected. Lastly the method goes back to the third step until the quality reaches a threshold value.
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Citations
9 Claims
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1. A method for optimization, comprising the steps of:
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(a) providing an initial population or a data set with a plurality of members respectively represented by parameter sets;
(b) applying one or a plurality of fitness functions to evaluate the quality of the members of the population;
(c) generating offspring of the population by means of a stochastic model using information from all members of the population;
(d) applying one or a plurality of fitness functions to evaluate the quality of the offspring with respect to the underlying problem of the optimization;
(e) selecting offspring, and (f) repeating steps (c) through (e) until the quality reaches a threshold value. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A system for optimization, comprising:
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means for providing an initial population or a data set with a plurality of members respectively represented by parameter sets;
means for applying one or a plurality of fitness functions to evaluate the quality of the members of the population;
means for generating offspring of the population by means of a stochastic model using information from all members of the population;
means for applying one or a plurality of fitness functions to evaluate the quality of the offspring with respect to the underlying problem of the optimization;
means for selecting offspring; and
means for comparing the quality to a threshold value.
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Specification