genetic algorithms optimization in order to find the optimum fuzzy membership functions parameters. More specifically, we …

-deterministic solutions and simple algorithms, artificial intelligence could become a base alternative for solving financial problems which …

The paper presents algorithms of determining a synchronized movement schedule of many objects. The author defines … problem which is based on finding a lexicographic solution. Two scheduling algorithms of synchronized movement and their …-profit analysis. The necessary and sufficient conditions for obtaining optimal solutions from the algorithms are discussed in detail …

The article presents a typology of the principle of action and evolutionary algorithms as a technique widely used for …. Evolutionary algorithms are a technique that is currently experiencing rapid development, are being successfully applied in many … of genetic algorithms in the management of sales in the division, organization, production and finance. …

We use co-evolutionary genetic algorithms to model the players' learning process in several Cournot models, and …-evolutionary algorithms we introduce, establish Nash Equilibrium in those models, in contrast to the \individual learning" versions which, as …-evolutionary genetic algorithms" as learning algorithms, the process of the game is an ergodic Markov Chain, and therefore we analyze …

, to address the problem of finite accuracy, which is inherent in genetic algorithms, since the set of feasible values in … search algorithms fail to identify the Nash Equilibrium. After a series of simulations, we conclude that the algorithm …