This paper focuses on solving the problem of how to assign locomotives to assembled trains optimally. To solve the problem, linear programming is applied. The situation we model in the paper occurs in the conditions of a transport operator that provides rail transport in the Czech Republic. In the paper, an extended locomotive assignment problem is modeled; the transport operator can use different classes of the locomotives to serve individual connections, some connections must be served by a predefined locomotive class, and the locomotives can be allocated to several depots at the beginning. The proposed model also takes into consideration the fact that some connections can be served by the locomotives of external transport companies or operators. The presented model is applied to a real example in order to test its functionality.

The paper presents a mathematical model and a simulation model of the freight trains classification process. We model the process as a queueing system with a server which is represented by a hump at a marshalling yard. We distinguish two types of shunting over the hump; primary shunting represents the classification of inbound freight trains over the hump (it is the primary function of marshalling yards), and secondary shunting is, for example, represented by the classification of trains of wagons entering the yard via industrial sidings. Inbound freight trains are considered to be customers in the system, and all needs of secondary shunting are failures of the hump because performing secondary shunting occupies the hump, and therefore inbound freight trains cannot be sorted. All random variables of the model are considered to be exponentially distributed with the exception of customer service times which are Erlang distributed. The mathematical model was created using method of stages and can be solved numerically employing a suitable software tool. The simulation model was created using coloured Petri nets. Both models are tested in conditions of a marshalling yard.

This paper focuses on the continuous location-routing problem that comprises of the location of multiple depots from a given region and determining the routes of vehicles assigned to these depots. The objective of the problem is to design the delivery system of depots and routes so that the total cost is minimal. The standard location-routing problem considers a finite number of possible locations. The continuous location-routing problem allows location to infinite number of locations in a given region and makes the problem much more complex. We present a genetic algorithm that tackles both location and routing subproblems simultaneously.

Queueing theory is a mathematical tool which can be applied for capacity planning and optimisation of production, manufacturing or logistics systems. One of the possible applications of queueing theory is service capacity optimisation. Let us consider that an engineering company operates m homogeneous machines. We assume that the machines are successively operating and down and times between failures and times to repair are exponentially distributed. The broken-down machines are repaired by n repairmen; we assume that n < m. In the article a mathematical model of the problem is presented; the model can be used for optimisation of the number of the repairmen with respect to costs of the system. Results obtained by the mathematical model are compared with simulation results; a simulation model of the problem is based on coloured Petri nets.

The paper deals with the line-planning problem related to urban public transport. Given the transportation network in a city, the origin-destination matrix of travel demands, and the fl eet of available vehicles, the goal is to design the routes and frequencies of lines. The proposed solution method is a combination of the exact mathematical programming algorithm and a trip assignment procedure. The solution process consists of three stages: (i) initialization, (ii) designing the line network and setting the initial frequencies of selected lines, (iii) solution improvement. In the fi rst stage, an initial set of feasible lines is proposed. In the second stage, an optimal subset of candidate lines is selected and initial frequencies of lines are computed by solving a mathematical programming model of the line-planning problem. The problem is formulated as a multiple criteria optimization problem, where the criteria refl ect travelers' demand for a high quality service, operator's interest in an effective service, and the environmental impact of the vehicles. The solution of this problem specifi es the number of vehicles of the given mode and type operating on the lines. The lines which are not assigned a vehicle will not operate. The assigned number of vehicles determines the frequency of a given line. At the same time, the solution specifi es optimal passengers' routes in the line network. The third stage consists of an iterative process, which computes new line frequencies with regard to in-vehicle and waiting times, transfers, and passengers' behavior in a situation when they have multiple travel alternatives. The approach has been verifi ed using real transportation data of a middle-sized city in the Slovak Republic. The paper presents the results of the case study.