Article

Article title USING FUZZY RESTRICTIONS WHEN SOLVING OPTIMIZATION PROBLEMS IMMUNE METHODS
Authors Yu.O. Chernyshev, N.N. Ventsov
Section SECTION I. EVOLUTIONAL SIMULATION
Month, Year 06, 2016 @en
Index UDC 681.3
DOI
Abstract The proposed representation of the process of decision not clearly specified optimization problem allows to extend the functionality of self-regulation known evolutionary search strategies of solutions using the method of negative selection. A distinctive feature of the proposed model solutions fuzzy opti-mization problem using the methods of artificial immune systems is the procedure for generating intellectual fuzzy decoders based on an analysis of the domain. The proposed algorithm implementation of the immune response is based on the method of alternative adaptation allows the intelligent selection of the set of admissible strategies. Scientific novelty of the proposed approach is to supplement evolutionary search strategy elements by negative selection. This symbiosis allows to evaluate not only the solutions in terms of optimality, but in the context of proximity to the analyte intermediate result proscribed solutions. Using fuzzy assessments of the computational process in conjunction with adaptive methods of decision-making allows you to adjust not only biodiversity, but also the inertial component of the search strategy. The variable component defines methods for assessing the results and can be specified in natural language vague terms such as "very close to L», «close to L», «a little close to the L», etc. The inertial component determines the degree of dynamic response of search procedures on strict conformity vague terms.

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Keywords Fuzzy systems; adaptation; implication; intellectual methods
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