DECISION-MAKING AT EVOLUTIONARY SEARCH DURING LIMITED NUMBER OF FUZZY EXPERIMENTS WITH MULTIPLE CRITERIA

Abstract

Context. The mechanism of decision-making during limited number of fuzzy experiments with multiple criteria are considered. The investigation object is process decision-making for project or control in complex systems with multiple criteria. Objective. It is necessary to determine optimal (most preferred) parameters of the systems with multiple criteria. It is no the mathematical model of the system, there is limited number of fuzzy experiments only. Method. experimental study of a process with several criteria (functions) depending on its parameters; the use of expert fuzzy evaluation to build a matrix of preferences for individual implementations; building a function of choosing preferred solutions based on a preference matrix by constructing a mathematical model of preference recognition, formulation and solving the problem of generalized mathematical programming as the final step in building the selection mechanism. The decision-making mechanism depends on the expert assessment procedure when comparing a limited set of results with each other, as well as on the statement of conditions when solving the problem of generalized mathematical programming. Comparison of a finite number of fuzzy experiments is convenient for expert evaluation. Presentation of the final choice as a result of solving the problem of generalized mathematical programming is convenient for using such a mechanism in automatic control systems already without human intervention. The proposed scheme of decision-making during limited number of fuzzy experiments has been applied to decision-making of project management for pellet burner. Results. Experimental decision-making fuzzy results are presented in the presence of several criteria for a pellet burner of a tubular heater, which confirm the acceptability of the developed decision-making mechanism. It was proposed the new scheme for constructing a selection mechanism for decision-making in systems with several criteria where there is a sample of fuzzy experimental results. Conclusions. The scheme of decision-making is includes the solving the generalized mathematical programming as the final step in building the selection mechanism. For the problem of generalized mathematical programming it may be applied the evolutionary search with choice function in form of preference or in form of lock.