This paper presents methods for optimal test frequencies search with the use of heuristic approaches. It includes a short summary of the analogue circuits fault diagnosis and brief introductions to the soft computing techniques like evolutionary computation and the fuzzy set theory. The reduction of both, test time and signal complexity are the main goals of developed methods. At the before test stage, a heuristic engine is applied for the principal frequency search. The methods produce a frequency set which can be used in the SBT diagnosis procedure. At the after test stage, only a few frequencies can be assembled instead of full amplitude response characteristic. There are ambiguity sets provided to avoid a fault tolerance masking effect.
In the calculations presented in the article, an artificial immune system (AIS) was used to plan the routes of the fleet of delivery vehicles supplying food products to customers waiting for the delivery within a specified, short time, in such a manner so as to avoid delays and minimize the number of delivery vehicles. This type of task is classified as an open vehicle routing problem with time windows (OVRPWT). It comes down to the task of a traveling salesman, which belongs to NP-hard problems. The use of the AIS to solve this problem proved effective. The paper compares the results of AIS with two other varieties of artificial intelligence: genetic algorithms (GA) and simulated annealing (SA). The presented methods are controlled by sets of parameters, which were adjusted using the Taguchi method. Finally, the results were compared, which allowed for the evaluation of all these methods. The results obtained using AIS proved to be the best.