Application of finite automata with genetic algorithms in JavaScript for determination of manpower system control

The strict hierarchical manpower system is modeled in the state space where the desired number of men in particular rank is determined by predefined trajectory function. The transition model is represented by the principles of System Dynamics where each rank is represented as the state element and transition as the flow. The basis for the model is the structure of the exponential delay chain with additional outflows from particular states. The strategy for achieving the desired states is determined by the application of the genetic algorithms which are implemented in JavaScript as well as the System Dynamics model. Parameter boundaries were taken into consideration which was determined according to the historical data. Predetermination of the desired system states by the set of exponential functions reduced the optimization burden. The optimization problem was defined as the minimization of the sum of quadratic difference between desired and actual states in all ranks for the observed time horizon. Time boundaries in considered optimization problem were not constant which contributes to the complexity of the addressed optimization task. The six state finite automaton code realization is described which prevents the oscillations in the strategies. The algorithm for integration of system dynamics model and genetic algorithm with finite automaton is described.