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In order to provide the fastest search for optimal solution, both the structure and the parameters of genetic algorithms (GA) should be optimized. The advantage of recently introduced micro-genetic algorithms (µGA) is that they operate with smaller genetic populations than standard GA. This paper describes the method of determining an optimal (best possible) mutation interval for µGA based on the...
Although methods for design of genetic algorithms (GA) are well established, general expressions for determination of optimal GA parameters are still missing. There is also a problem of possible inaccuracy of a found solution. This paper describes a GA performance analysis for a selected vector-based optimization problem that has led to useful GA parameter selection criteria. The paper also describes...
In this paper we describe a design and implementation of an on-line scheduling algorithm for Controller Area Network (CAN) messages that exploits properties of genetic algorithms (GA) to achieve global message throughput optimization. The use of GA-based scheduler has been found effective even in time-critical distributed control systems, such as the considered control system that encompasses several...
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