The use of a decision making scheme based on fuzzy logic applied to the design of electromagnetic devices is presented. In the Multi-Objective Optimisation, the different scalar objectives are merged together firstly by means of a fuzzyfication process and then by the application of a fuzzy logical operator. This scheme can be easily coupled to any search optimisation (zeroth order algorithm) since it does not require differentiation of the scalar functions. Two different implementations of the procedure, coupled to Simulated Annealing and to Genetic Algorithm stochastic search are presented. The two procedures are tested versus a two solenoids SMES (Superconducting Magnetic Energy Storage) Multi-Objective Optimisation problem.
Multi-objective optimisation with stochastic algorithms and fuzzy definition of objective function / Chiampi, Mario; G., Fuerntratt; Magele, C. h.; Ragusa, CARLO STEFANO; Repetto, Maurizio. - In: INTERNATIONAL JOURNAL OF APPLIED ELECTROMAGNETICS AND MECHANICS. - ISSN 1383-5416. - 9:4(1998), pp. 381-389.
Multi-objective optimisation with stochastic algorithms and fuzzy definition of objective function
CHIAMPI, Mario;RAGUSA, CARLO STEFANO;REPETTO, MAURIZIO
1998
Abstract
The use of a decision making scheme based on fuzzy logic applied to the design of electromagnetic devices is presented. In the Multi-Objective Optimisation, the different scalar objectives are merged together firstly by means of a fuzzyfication process and then by the application of a fuzzy logical operator. This scheme can be easily coupled to any search optimisation (zeroth order algorithm) since it does not require differentiation of the scalar functions. Two different implementations of the procedure, coupled to Simulated Annealing and to Genetic Algorithm stochastic search are presented. The two procedures are tested versus a two solenoids SMES (Superconducting Magnetic Energy Storage) Multi-Objective Optimisation problem.Pubblicazioni consigliate
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https://hdl.handle.net/11583/1398024
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