Schedules Cluster Recognition with Use Conditional Probability

This paper presents use conditional probability for schedules cluster recognition problem. Task scheduling in this approach are generated with the function, which defines the dependence between random parameter of priority rule and the operation number. There are some algorithms, which differ from each other in type and in the manner of change value of these functions. The paper gives the formulation of schedules cluster recognition problem and basic grid-based clustering algorithm is described. Schedules are generated too by the optimization algorithms (for example: simulated annealing, taboo method, genetic algorithm, and other mataheuristic) many times in the clustering process. Structures for some of schedules are considered.