Optimization Under Fuzzy If-Then Rules Using Stochastic Algorithms
نویسندگان
چکیده
A new approach to optimization of processes described by fuzzy rules, in which the functional relationship between the decision variables and the objective function is not completely known, is introduced in this paper. It is based on stochastic algorithms and allows to determine optimal values of state variables and to optimize fuzzy rules (parameters of membership functions). Stochastic algorithms have many advantages like their robustness and, in most cases, global convergence properties. Here, a new algorithm (FICRS) was developed, being applied to the solution of a case study taken from the recent literature.
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