There are three implemented algorithms in this work: lessons permutation, lessons permutation with simulated annealing adjustment, lessons permutation using Bayesian approach theory to optimize SA parameters algorithms. Algorithms and graphical user interface are programmed with JSP which is based on Java object programming language. To evaluate schedule goodness algorithms are computing every penalty points which are given for some inconvenieces. User is able to define how much penalty points will be given if some inconveniece is satisfied. Also he is able to assign stochastic algorithm parameters. There was accomplished theory, where was observed using of simulated annealing and Bayesian approch methods in other stochastic algorithms and their different combination. There is a description of profiled school schedule optimization algorithm, which is based on SA searching methodology: searching for the optima through lower quality solutions, using temperature function which convergence, difference in quality. Algorythm which is using BA was created in case to improve SA searching methodology. User by changing systems temperature or annealing speed througth parameters can make big influence to SA behaviour. Passing parameters then using algorithm with BA meaner influence is made to behaviour because this method prognosticates, acording to him, better parameters with which SA should work effectively and changing them. Researches with three stochastic algorithms were made... [to full text]