Stochastic optimization model of locomotive assignment to freight trains

Abstract

Consideration was given to the optimization model of assigning the locomotives to the freight trains. The model was formulated in terms of a dynamic problem of stochastic programming with probabilistic constraints. The state variables characterize positions of the locomotives and trains at each time instant. The variables defining the motion of locomotives and their assignment to trains at each time instant play the role of controls. The expectation of the total freight traffic is the criterial function of the problem. A two-stage hybrid algorithm to solve the problem was developed. It combines the coordinatewise search and a genetic algorithm. Results of the numerical experiment were given.