Abstract. The new modification of ant colony optimization has been proposed to solve travelling salesman problem. This modification is based on using fuzzy rules and fuzzy terms like «a little», «much», «almost» etc. Fuzzy logic controller was developed to define fuzzy rules. This controller allows to regulate values of heuristic coefficients of ant colony optimization dynamically. Experimental research was carried out. The results received show high effectiveness of fuzzy logic controller using in ant colony optimization. The modified ant colony optimization algorithm finds shorter routes on 1-3%. This modification can be used to solve other problems.
In this paper new possibilities of evolutionary design are defined and program support computer aided design tools on their basis focused on natural analogy application are described. Features of design programs developed in computer algebra system MAPLE are discussed. It is shown that the prominent features of genetic algorithms for field of circuit design are elitism and mutation.
This paper represents the following improvement of evolutionary analog circuit design on the base of the univariate marginal distribution algorithm. Experiments have indicated that the high mutation rate increases the success rate, although the computational expenses are increased as well. An effective mutation rate is considered with respect to a high success rate and small computational expenses. Experiments for analog arrays are discussed.
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