A generalized net with an ACO-algorithm optimization component Vassia Atanassova 1 , Stefka Fidanova 1 , Panagiotis Chountas 2 , Krassimir Atanassov 3 1 Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., bl. 2, Sofia 1113, Bulgaria vassia.atanassova@gmail.com, stefka@parallel.bas.bg 2 University of Westminster, Dept. of Business Information Systems, School of Electronics & Computer Science, 115 New Cavendish Street, London W1W 6UW, United Kingdom p.i.chountas@westminster.ac.uk 3 Bioinformatics and Mathematical Modelling Dept., Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., bl. 105, Sofia 1113, Bulgaria krat@bas.bg Abstract. In the paper we describe a generalized net GACOA realiz- ing an arbitrary algorithms for ant colony optimization. In this sense, this net is universal for all standard algorithms for ant colony optimiza- tion, since it describes the way of functioning and results of their work. Then, we discuss the way of constructing a GN that includes the GACOA as a subnet. In this way, we ensure the generalized net tokens’ optimal transfer with regard to the results of GACOA, Thus, we construct a gen- eralized net, featuring an optimization component and thus optimally functioning. 1 Introduction Generalized nets (GNs; see [1, 3, 5]) are an apparatus for modelling of parallel and concurrent processes, developed as an extension of the concept of Petri nets and some of their modifications. During the last 25 years it was shown that the GNs can be used for constructing of universal tools, describing the functioning and the result of the work of the other types of Petri nets, of the finite automata and Turing machine, of expert systems and machine learning processes, data bases and data warehouses, etc. (see, e.g. [2, 4, 6, 11]). In a series of papers by some of the authors, it was shown that the GNs can represent the functioning and the result of the work of different Ant Colony Op- timization (ACO) algorithms (see, e.g. [7–9]). On the other hand, in [1] it was shown that we can construct special types of GNs, featuring an optimization component. By optimization component we will understand a subnet of a given generalized net, which describes a particular optimization problem and whose