Planning Electric-Rolling-Stock Maintenance in Conditions of Limited Resources

Russian Electrical Engineering, Россия. 2017. Vol. 88. No. 12. P. 839–841.

Sidorenko V., Уманский В. И., Чжо М. А., Алексеев В. М., Розенберг Е. Н.

Planning electric-rolling-stock (ERS) maintenance in conditions of limited resources can be carried out based on the following criteria of efficiency of construction of the cycle diagram of the electric rolling stock: meeting the requirements of the railway-traffic safety provided by adjusting the planned movement time of the electric rolling stock for the purpose of not allowing an excessive lapse of time between the maintenance over that permissible and uniformity of maintenance. The solution of the set problem using the graph theory allows obtaining the whole set of the permissible values of maintenance and selecting a value that, on the one hand, corresponds to the planned train time schedule (PTTS) and, on the other hand, differs minimally from the optimal with respect to the selected criterion. This takes a significant amount of time. The problem can be quickly solved using a genetic algorithm. The introduction of a new criterion—total excess time lapse between maintenance works over the permissible interval—allows obtaining the solution with any initial data, which is not always achievable when using the uniform-maintenance criterion. The crossover and permutation algorithm implemented within the genetic algorithm is adapted taking into account considering the peculiarities of the agents engaged in solving the problem that has been set out. We have studied the possibility of using various types of crossover and permutation to construct the cycle diagrams and influence of the parameters of the genetic algorithm on the results. The obtained analytical results are tested for the conditions of the Moscow subway.

Keywords: оптимизация, optimization, техническое обслуживание, планирование, комбинаторика, planning, генетический алгоритм, теория графов, combinatorics, maintenance planning, genetic algorithm, электроподвижной состав, electric rolling stock, graph theory