Markov Processes in Modeling Life Cycle of Economic Clusters

The object is economic clusters' life cycle (ECLC). The aim is to model its regulations algorithm. The hypothesis: ECLC transitions are stochastic processes independent of past. The method is Markov processes with discrete time. The algorithm is implemented in programming language Eсlipse. The results are: 1) mathematical model of ECLC with life-cycle stages, stochastic transitions, transition values. For mature clusters their borders and actors are defined; 2) ECLC modeling algorithm with given stochastic transition matrix considering influence of different environments; 3) software "Modeling _Cluster_v1" for Androids to model online cluster development based on ECLC regulations. The novelties: for the first time ECLC model considers stochastic character of life-cycle stages simulating the number of actors at each stage, cluster’s size, diameter and delimitation. Practical application: Program is applied to education, for interest groups involved in cluster development and projects to model of clusters’ evolution trajectories under different environmental