A simulation modelling methodology for evaluating flat-shunted yard operations

Abstract

Provided, in this paper, is a simulation modelling methodology for analysing and evaluating flat-shunted yard operations. Created and implemented is a yard simulation model using a computer package for event-based simulation, SIMUL’8. The main idea behind the simulation modelling approach is to simulate the flat-shunted yard operations dividing the yard into segments so that the behaviour of each segment can be described and analyzed separately. The simulation model takes the shape of queuing network. The components of the queuing network are interconnected queuing systems that interact and influence one another, so that the global impact of freight train operations is captured. The queuing systems replicate the preliminary specified segments that consist of a set of work centres (i.e., servers) and/or storage areas (i.e., capacity limitations). This modelling approach allows us to study the processing capabilities of the yards. In the shape of “Case Study”, we demonstrate how the proposed approach is implemented in terms of “real world” case.

Introduction

In the traditional rail freight systems, unlike block trains and shuttle trains, a single freight car or block of freight cars does not move usually on one freight train directly to its demand destination. Instead, the freight car moves on various freight trains. This process can be specified by schedules. To some extent, the schedules indicate the connections between freight trains that the freight car must be part of in order to arrive at its demand destination at the appointed time. These connections in the rail networks, take place at the yards. If a connection between two planned freight trains in a yard fails, the client does not receive his freight at the appointed time, the yard queue materializes because freight cars are left behind awaiting some next possible connection, the yard limited physical capacity is reduced, the yard limited processing capability is reduced and the yard personnel encounters difficulties to serve the next freight trains, costs (both operating costs and waiting costs) for the rail freight service provider are on the increase, and the service provided deteriorates. Consequently, the yards are facilities that play an important role for the execution of the freight transportation service by rail and their importance must not be neglected.

The railway freight operator under this study is Comboios de Portugal, CP – Carga, still the main Portuguese rail freight service provider. CP Carga schedules in advance its freight trains at planning management level. These schedules consist of information for the movement of freight cars in the shape of freight trains over the rail network subject to demands of origins and destinations, arrivals and departures of freight trains as well as reassembling in the yards. Next, the prepared schedules are submitted to the operations for execution.

At planning level, the planner tries to satisfy required demands for transportation according to the preliminary planned freight trains, historical data, and production scheme in operation as well as available slots in the actual timetables among the passenger trains in a case of extra freight trains. The planning process is totally performed manually and to a significant extent depends upon the experience and the skills of the planner. Moreover, the planning process methodology does not explicitly involve the estimation of the maximum processing capabilities of the yards. There is no instrument for it. Therefore, some suggestions for freight train/freight car movement are infeasible with respect to the maximum operational capacities of the yards.

On the other hand, what is observed in the front-line operations with the CP freight trains is that the operations fulfil the daily services with little regard to what was planned. The yard personnel say things such as: “the superiors consider the shunting to be executed for 20–30 min, we cannot perform it because only the brake test takes about 20 min…moreover, they planned too many freight cars to stay in the yard, there is not enough space, we need lines to execute our work, therefore in every opportune case regardless of the plan we send freight cars away to ensure space for the incoming freight trains!” In response to this situation the planning personnel say things such as: “we planned well what was required by the commercial department but the operation did not execute it as we planned” [21, p. 12]!

Therefore, Planning and Operations at CP Carga have shown a low confidence in each other. This awkward situation appears to be because at the planning stage the maximum processing capabilities of the CP yards are not estimated and considered explicitly and therefore in many cases the operations encounter difficulties to produce what is scheduled. This situation motivated us to provide an adequate methodology accompanied with a reliable tool for estimating the maximum processing capabilities of CP Cargo yards.

The objectives of this work are to provide an adequate methodology accompanied with a reliable tool for estimating, analysing and evaluating the performance capabilities of rail yards using an appropriate approach for the purposes of a rail freight operator. The provided methodology is envisaged to be used at planning management level of freight services by rail.

This work includes a paper addressed at “A simulation modelling methodology for evaluating flat-shunted yard operations” and is presented in a cumulative fashion, each section dependent to a certain extent on the material in the preceding sections.

The rest of this paper is organized, as follows: in Section 2 short definitions for yards are provided followed by a brief literature review focusing on analytical queueing models and simulations in Section 3. Next, a presentation of the event-based simulation language, SIMUL 8 and its attributes used for the objectives of this paper are given. A simulation modelling methodology for evaluating flat-shunted yard operations is provided in Section 5, followed by a detailed case study demonstrating its application in Section 6. We wrap up with synthesis and conclusions in Section 7.