Objective: this research addresses the pressing task of determining optimal sites for remote maintenance of shunting locomotives within railway transport framework by applying a binary optimization method. The rationale for adopting mobile maintenance technologies is justified in the context of Russia's extensive railway network, which comprises a large number of stations and service depots, as well as diverse fleets of diesel locomotives. This research reviews existing approaches to locating locomotive facilities and highlights the complexity of manually selecting solutions in the presence of substantial infrastructure and the diversity of the operational fleet. Methods: a mathematical model employing binary optimization method is developed to minimize the total costs of maintenance and repair through efficient distribution of locomotive field maintenance centres. The findings of a numerical experiment conducted on the Gorky Railway network are presented in this study along with a calculation algorithm. The study also includes the construction of transfer graphs for diesel locomotives, identifying the optimal stations for locomotive field maintenance placement and an assessment of cost dynamics associated with varied field services. Results: a methodology has been developed to improve the efficiency of shunting locomotive operations by reducing non-productive downtime and the costs associated with transportation of machines. The conclusions obtained have significant practical implications for railway transport companies engaged in the planning and management of rolling stock repair and maintenance. Practical significance: this paper also discusses the organization of maintenance for shunting locomotives, highlighting the need to account for their operational specificities across sections of the network. Data on the distribution of diesel locomotives across stations are presented and potential scenarios for field maintenance placement of locomotives are analyzed. Particular attention is devoted to the assessment of the economic efficiency of alternative placement options, which enables selection of the optimal approach given specific operating conditions.
Smirnov et al. (Tue,) studied this question.