Erhan Kozan

Heuristic Techniques for Single Line Train Scheduling

Optimising a train schedule on a single line track is known to be NP-Hard with respect to the number of conflicts in the schedule. This makes it difficult to determine optimum solutions to real life problems in reasonable time and raises the need for good heuristic techniques. The heuristics applied and compared in this paper are a local search heuristic with an improved neighbourhood structure, genetic algorithms, tabu search and two hybrid algorithms. When no time constraints are enforced on solution time, the genetic and hybrid algorithms were within five percent of the optimal solution for at least ninety percent of the test problems.

An approach to determine storage locations of containers at seaport terminals

This paper models the seaport system with the objective of determining the optimal storage strategy for various container-handling schedules. A container location model (CLM) is developed, with an objective function designed to minimise the turn around time of container ships, and solved using genetic algorithm (GA). The results section presents an analyses of different resource levels and a comparison with current practice at the Port of Brisbane.

Modeling Train Delays in Urban Networks

The reliability of urban passenger trains is a critical performance measure for passenger satisfaction and ultimately market share. A delay to one train in a peak period can have a severe effect on the schedule adherence of other trains. This paper presents an analytically based model to quantify the expected positive delay for individual passenger trains and track links in an urban rail network. The model specifically addresses direct delay to trains, knock-on delays to other trains, and delays at scheduled connections. A solution to the resultant system of equations is found using an iterative refinement algorithm. Model validation, which is carried out using a real-life suburban train network consisting of 157 trains, shows the model estimates to be on average within 8% of those obtained from a large scale simulation. Also discussed, is the application of the model to assess the consequences of increased scheduled slack time as well as investment strategies designed to reduce delay.

Comparison of analytical and simulation planning models of seaport container terminals

This paper discusses the major factors influencing the transfer efficiency of seaport container terminals. The objective is to utilise queuing techniques to draw inferences regarding strategies for a container terminals service improvement by using analytical expressions. The model developed here is referred to as a batch‐arrival multi server queuing system and designated as a stochastic model. Later the model is compared with another analytical model and a simulation approach. A comparative analysis is performed on these models and results show that the analytical model can take the place of the simulation model.

Scheduling trains as a blocking parallel-machine job shop scheduling problem

In this paper, the train scheduling problem is modelled as a blocking parallel-machine job shop scheduling (BPMJSS) problem. In the model, trains, single-track sections and multiple-track sections, respectively, are synonymous with jobs, single machines and parallel machines, and an operation is regarded as the movement/traversal of a train across a section. Due to the lack of buffer space, the real-life case should consider blocking or hold-while-wait constraints, which means that a track section cannot release and must hold the train until next section on the routing becomes available. Based on literature review and our analysis, it is very hard to find a feasible complete schedule directly for BPMJSS problems. Firstly, a parallel-machine job-shop-scheduling (PMJSS) problem is solved by an improved shifting bottleneck procedure (SBP) algorithm without considering blocking conditions. Inspired by the proposed SBP algorithm, feasibility satisfaction procedure (FSP) algorithm is developed to solve and analyse the BPMJSS problem, by an alternative graph model that is an extension of the classical disjunctive graph models. The proposed algorithms have been implemented and validated using real-world data from Queensland Rail. Sensitivity analysis has been applied by considering train length, upgrading track sections, increasing train speed and changing bottleneck sections. The outcomes show that the proposed methodology would be a very useful tool for the real-life train scheduling problems.

An assignment model for dynamic load planning of intermodal trains

Intermodal terminals are important facilities in the container transport network, providing an exchange of containers between road and rail transport. Numerous factors can affect throughput in such highly integrated systems. These include numbers and types of equipment, physical layout, storage capacity and operating strategies. This study aims to improve operating strategies by developing an analytical tool to assist in load planning of container trains. The problem investigated can be described as a dynamic assignment problem with many uncertain parameters. Numerical investigations focus on tuning the proposed model to deal with the uncertainties.

Mathematical modelling of container transfers and storage locations at seaport terminals

This paper models the seaport system with the objective of determining the optimal storage strategy and container-handling schedule. It presents an iterative search algorithm that integrates a container-transfer model with a container-location model in a cyclic fashion to determine both optimal locations and corresponding handling schedule. A genetic algorithm (GA), a tabu search (TS) and a tabu search/genetic algorithm hybrid are used to solve the problem. The implementation of these models and algorithms are capable of handling the very large problems that arise in container terminal operations. Different resource levels are analysed and a comparison with current practise at an Australian port is done.

Scheduling Trains with Priorities: A No-Wait Blocking Parallel-Machine Job-Shop Scheduling Model

The paper investigates train scheduling problems when prioritised trains and non-prioritised trains are simultaneously traversed in a single-line rail network. In this case, no-wait conditions arise because the prioritised trains such as express passenger trains should traverse continuously without any interruption. In comparison, non-prioritised trains such as freight trains are allowed to enter the next section immediately if possible or to remain in a section until the next section on the routing becomes available, which is thought of as a relaxation of no-wait conditions. With thorough analysis of the structural properties of the No-Wait Blocking Parallel-Machine Job-Shop-Scheduling (NWBPMJSS) problem that is originated in this research, an innovative generic constructive algorithm (called NWBPMJSS_Liu-Kozan) is proposed to construct the feasible train timetable in terms of a given order of trains. In particular, the proposed NWBPMJSS_Liu-Kozan constructive algorithm comprises several recursively-used sub-algorithms (i.e. Best-Starting-Time-Determination Procedure, Blocking-Time-Determination Procedure, Conflict-Checking Procedure, Conflict-Eliminating Procedure, Tune-up Procedure and Fine-tune Procedure) to guarantee feasibility by satisfying the blocking, no-wait, deadlock-free and conflict-free constraints. A two-stage hybrid heuristic algorithm (NWBPMJSS_Liu-Kozan-BIH) is developed by combining the NWBPMJSS_Liu-Kozan constructive algorithm and the Best-Insertion-Heuristic (BIH) algorithm to find the preferable train schedule in an efficient and economical way. Extensive computational experiments show that the proposed methodology is promising because it can be applied as a standard and fundamental toolbox for identifying, analysing, modelling and solving real-world scheduling problems.

A railway capacity determination model and rail access charging methodologies

This article discusses approaches to the determination of railway capacity and the significance of the following factors on capacity: mix of trains, length and weight of trains, direction of train travel, acceleration and deceleration, stopping protocols of trains, location and length of crossing loops, location of signals, length of sections, dwell times and sectional running times. A more accurate method to calculate railway capacity is developed using previously unaddressed aspects for capacity determination. Capacity and pricing are two key issues for organizations involved with open track access regimes. A train access charging methodology is therefore developed and incorporated into a railway capacity determination model.

Modelling the number and location of sidings on a single line railway

Abstract This article puts forward a model to determine the required number and position of sidings on a single track rail corridor. The sidings are positioned to minimise both the risk of delays and the delays caused by train conflicts, for a given cyclic train schedule. The key feature of the model is the allowance of variable train velocities and non-uniform departure times. A decomposition procedure, used to partition the mixed integer non-linear program into easily solvable sub-models was found to converge quickly. Numerical results, using actual train schedules, indicate considerable savings in terms of both conflict delay and risk of delay when track sidings are positioned using the model. Simulations are used to demonstrate how the model can be used determine the required number of sidings given a pre-defined level of service.