103 research outputs found
Dynamic railway junction rescheduling using population based ant colony optimisation
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Efficient rescheduling after a perturbation is an important concern of the railway industry. Extreme delays can result in large fines for the train company as well as dissatisfied customers. The problem is exacerbated by the fact that it is a dynamic one; more timetabled trains may be arriving as the perturbed trains are waiting to be rescheduled. The new trains may have different priorities to the existing trains and thus the rescheduling problem is a dynamic one that changes over time. The aim of this research is to apply a population-based ant colony optimisation algorithm to address this dynamic railway junction rescheduling problem using a simulator modelled on a real-world junction in the UK railway network. The results are promising: the algorithm performs well, particularly when the dynamic changes are of a high magnitude and frequency
Optimized shunting with mixed-usage tracks
We consider the planning of railway freight classification at hump yards, where the problem
involves the formation of departing freight train blocks from arriving trains subject to
scheduling and capacity constraints. The hump yard layout considered consists of arrival
tracks of sufficient length at an arrival yard, a hump, classification tracks of non-uniform
and possibly non-sufficient length at a classification yard, and departure tracks of sufficient
length. To increase yard capacity, freight cars arriving early can be stored temporarily
on specific mixed-usage tracks. The entire hump yard planning process is covered in this
paper, and heuristics for arrival and departure track assignment, as well as hump scheduling,
have been included to provide the neccessary input data. However, the central problem
considered is the classification track allocation problem. This problem has previously
been modeled using direct mixed integer programming models, but this approach did not
yield lower bounds of sufficient quality to prove optimality. Later attempts focused on
a column generation approach based on branch-and-price that could solve problem instances
of industrial size. Building upon the column generation approach we introduce
a direct arc-based integer programming model, where the arcs are precedence relations
between blocks on the same classification track. Further, the most promising models
are adapted for rolling-horizon planning. We evaluate the methods on historical data
from the Hallsberg shunting yard in Sweden. The results show that the new arc-based
model performs as well as the column generation approach. It returns an optimal schedule
within the execution time limit for all instances but from one, and executes as fast
as the column generation approach. Further, the short execution times of the column
generation approach and the arc-indexed model make them suitable for rolling-horizon
planning, while the direct mixed integer program proved to be too slow for this.
Extended analysis of the results shows that mixing was only required if the maximum
number of concurrent trains on the classification yard exceeds 29 (there are 32 available
tracks), and that after this point the number of extra car roll-ins increases heavily
Scheduled service network design for integrated planning of rail freight transportation
Cette thĂšse Ă©tudie une approche intĂ©grant la gestion de lâhoraire et la conception de rĂ©seaux de services pour le transport ferroviaire de marchandises. Le transport par rail sâarticule autour dâune structure Ă deux niveaux de consolidation oĂč lâaffectation des wagons aux blocs ainsi que des blocs aux services reprĂ©sentent des dĂ©cisions qui complexifient grandement la gestion des opĂ©rations. Dans cette thĂšse, les deux processus de consolidation ainsi que lâhoraire dâexploitation sont Ă©tudiĂ©s simultanĂ©ment. La rĂ©solution de ce problĂšme permet dâidentifier un plan dâexploitation rentable comprenant les politiques de blocage, le routage et lâhoraire des trains, de mĂȘme que lâhabillage ainsi que lâaffectation du traffic.
Afin de décrire les différentes activités ferroviaires au niveau tactique, nous étendons le réseau physique et construisons une structure de réseau espace-temps comprenant trois couches dans lequel la dimension liée au temps prend en considération les impacts temporels sur les opérations. De plus, les opérations relatives aux trains, blocs et wagons sont décrites par différentes couches. Sur la base de cette structure de réseau, nous modélisons ce problÚme de planification ferroviaire comme un problÚme de conception de réseaux de services.
Le modÚle proposé se formule comme un programme mathématique en variables mixtes. Ce dernie
r sâavĂšre trĂšs difficile Ă rĂ©soudre en raison de la grande taille des instances traitĂ©es et de sa complexitĂ© intrinsĂšque. Trois versions sont Ă©tudiĂ©es : le modĂšle simplifiĂ© (comprenant des services directs uniquement), le modĂšle complet (comprenant des services directs et multi-arrĂȘts), ainsi quâun modĂšle complet Ă trĂšs grande Ă©chelle. Plusieurs heuristiques sont dĂ©veloppĂ©es afin dâobtenir de bonnes solutions en des temps de calcul raisonnables.
PremiÚrement, un cas particulier avec services directs est analysé. En considérant une cara
ctéristique spécifique du problÚme de conception de réseaux de services directs nous développons un nouvel algorithme de recherche avec tabous. Un voisinage par cycles est privilégié à cet effet. Celui-ci est basé sur la distribution du flot circulant sur les blocs selon les cycles issus du réseau résiduel.
Un algorithme basĂ© sur lâajustement de pente est dĂ©veloppĂ© pour le modĂšle complet, et nous
proposons une nouvelle mĂ©thode, appelĂ©e recherche ellipsoidale, permettant dâamĂ©liorer davantage la qualitĂ© de la solution. La recherche ellipsoidale combine les bonnes solutions admissibles gĂ©nĂ©rĂ©es par lâalgorithme dâajustement de pente, et regroupe les caractĂ©ristiques des bonnes solutions afin de crĂ©er un problĂšme Ă©lite qui est rĂ©solu de facon exacte Ă lâaide dâun logiciel commercial. Lâheuristique tire donc avantage de la vitesse de convergence de lâalgorithme dâajustement de pente et de la qualitĂ© de solution de la recherche ellipsoidale. Les tests numĂ©riques illustrent lâefficacitĂ© de lâheuristique proposĂ©e. En outre, lâalgorithme reprĂ©sente une alternative intĂ©ressante afin de rĂ©soudre le problĂšme simplifiĂ©.
Enfin, nous Ă©tudions le modĂšle complet Ă trĂšs grande Ă©chelle. Une heuristique hybride est dĂ©veloppĂ©e en intĂ©grant les idĂ©es de lâalgorithme prĂ©cĂ©demment dĂ©crit et la gĂ©nĂ©ration de colonnes. Nous proposons une nouvelle procĂ©dure dâajustement de pente oĂč, par rapport Ă lâancienne, seule lâapproximation des couts liĂ©s aux services est considĂ©rĂ©e. La nouvelle approche dâajustement de pente sĂ©pare ainsi les dĂ©cisions associĂ©es aux blocs et aux services afin de fournir une dĂ©composition naturelle du problĂšme. Les rĂ©sultats numĂ©riques obtenus montrent que lâalgorithme est en mesure dâidentifier des solutions de qualitĂ© dans un contexte visant la rĂ©solution dâinstances rĂ©elles.This thesis studies a scheduled service network design problem for rail freight transportation planning. Rails follow a special two level consolidation organization, and the car-to-block, block-to-service handling procedure complicates daily operations. In this research, the two consolidation processes as well as the operation schedule are considered simultaneously, and by solving this problem, we provide an overall cost-effective operating plan, including blocking policy, train routing, scheduling, make-up policy and traffic distribution.
In order to describe various rail operations at the tactical level, we extend the physical network and construct a 3-layer time-space structure, in which the time dimension takes into consideration the temporal impacts on operations. Furthermore, operations on trains, blocks, and cars are described in different layers. Based on this network structure, we model the rail planning problem to a service network design formulation.
The proposed model relies on a complex mixed-integer programming formulation. The problem is very hard to solve due to the computational difficulty as well as the tremendous size of the application instances. Three versions of the problem are studied, which are the simplified model (with only non-stop services), complete model (with both non-stop and multi-stop services) and very-large-scale complete model. Heuristic algorithms are developed to provide good feasible solutions in reasonable computing efforts.
A special case with non-stop services is first studied. According to a specific characteristic of the direct service network design problem, we develop a tabu search algorithm. The tabu search moves in a cycle-based neighborhood, where flows on blocks are re-distributed according to the cycles in a conceptual residual network.
A slope scaling based algorithm is developed for the complete model, and we propose a new method, called ellipsoidal search, to further improve the solution quality. Ellipsoidal search combines the good feasible solutions generated from the slope scaling, and collects the features of good solutions into an elite problem, and solves it with exact solvers. The algorithm thus takes advantage of the convergence speed of slope scaling and solution quality of ellipsoidal search, and is proven effective. The algorithm also presents an alternative for solving the simplified problem.
Finally, we work on the very-large-size complete model. A hybrid heuristic is developed by integrating the ideas of previous research with column generation. We propose a new slope scaling scheme where, compared with the previous scheme, only approximate service costs instead of both service and block costs are considered. The new slope scaling scheme thus separates the block decisions and service decisions, and provide a natural decomposition of the problem. Experiments show the algorithm is good to solve real-life size instances
OPTIMIZATION OF RAILWAY TRANSPORTATION HAZMATS AND REGULAR COMMODITIES
Transportation of dangerous goods has been receiving more attention in the realm of academic and scientific research during the last few decades as countries have been increasingly becoming industrialized throughout the world, thereby making Hazmats an integral part of our life style. However, the number of scholarly articles in this field is not as many as those of other areas in SCM. Considering the low-probability-and-high-consequence (LPHC) essence of transportation of Hazmats, on the one hand, and immense volume of shipments accounting for more than hundred tons in North America and Europe, on the other, we can safely state that the number of scholarly articles and dissertations have not been proportional to the significance of the subject of interest. On this ground, we conducted our research to contribute towards further developing the domain of Hazmats transportation, and sustainable supply chain management (SSCM), in general terms.
Transportation of Hazmats, from logistical standpoint, may include all modes of transport via air, marine, road and rail, as well as intermodal transportation systems. Although road shipment is predominant in most of the literature, railway transportation of Hazmats has proven to be a potentially significant means of transporting dangerous goods with respect to both economies of scale and risk of transportation; these factors, have not just given rise to more thoroughly investigation of intermodal transportation of Hazmats using road and rail networks, but has encouraged the competition between rail and road companies which may indeed have some inherent advantages compared to the other medium due to their infrastructural and technological backgrounds. Truck shipment has ostensibly proven to be providing more flexibility; trains, per contra, provide more reliability in terms of transport risk for conveying Hazmats in bulks.
In this thesis, in consonance with the aforementioned motivation, we provide an introduction into the hazardous commodities shipment through rail network in the first chapter of the thesis. Providing relevant statistics on the volume of Hazmat goods, number of accidents, rate of incidents, and rate of fatalities and injuries due to the incidents involving Hazmats, will shed light onto the significance of the topic under study. As well, we review the most pertinent articles while putting more emphasis on the state-of-the-art papers, in chapter two. Following the discussion in chapter 3 and looking at the problem from carrier companyâs perspective, a mixed integer quadratically constraint problem (MIQCP) is developed which seeks for the minimization of transportation cost under a set of constraints including those associating with Hazmats. Due to the complexity of the problem, the risk function has been piecewise linearized using a set of auxiliary variables, thereby resulting in an MIP problem. Further, considering the interests of both carrier companies and regulatory agencies, which are minimization of cost and risk, respectively, a multiobjective MINLP model is developed, which has been reduced to an MILP through piecewise linearization of the risk term in the objective function. For both single-objective and multiobjective formulations, model variants with bifurcated and nonbifurcated flows have been presented. Then, in chapter 4, we carry out experiments considering two main cases where the first case presents smaller instances of the problem and the second case focuses on a larger instance of the problem.
Eventually, in chapter five, we conclude the dissertation with a summary of the overall discussion as well as presenting some comments on avenues of future work
Freight and passenger railway optimization
Das Ziel dieser Arbeit war es, einen Ăberblick ĂŒber die aktuellen BeitrĂ€ge der Literatur in den Bereichen der Eisenbahnlogistik sowohl im GĂŒter- als auch im Personenverkehr zu geben. WĂ€hrend sich der GĂŒterverkehr mit Problemen der Zusammenstellung der ZĂŒge und Waggons beziehungsweise der Verteilung der Leerfahrzeuge auseinander setzte, beschĂ€ftigte sich die Eisenbahnlogistik im Bereich des Personenverkehrs mit Optimierungsmodellen bezĂŒglich Eisenbahnlinienplanung, Erstellung eines Fahrplanes, Inbetriebnahme von Fahrzeugen und Besatzungs- und Einsatzplanung.
Die Bereiche der Eisenbahnlogistik haben in der Literatur eindeutig an Aufmerksamkeit gewonnen. In der Folge war es schwierig eine Auswahl aus dieser Vielfalt an BeitrĂ€gen zu treffen. Deshalb versucht diese Arbeit nur einen kurzen Einblick ĂŒber einige wichtige BeitrĂ€ge der letzten Jahre im Bereich der Eisenbahnlogistik zu geben. Aufgrund hochentwickelter mathematischer Techniken und deren Lösungsmöglichkeiten, die in den letzten Jahren aufgekommen sind, war es nun möglich die komplizierten Modelle der Eisenbahnlogistik in einer vernĂŒnftigen Zeit zu lösen. DarĂŒber hinaus wurde ein Trend zur Entwicklung effizienterer entscheidungsunterstĂŒtzender Hilfsprogramme fĂŒr reale Gegebenheiten der Eisenbahnlogistik beobachtet. Im GroĂen und Ganzen sollten in Zukunft stĂ€rker integrierte Modelle der Eisenbahnplanung und Routenplanung entwickelt werden um robuste Lösungen und Methoden zu fördern.The aim of this work was to provide a survey of recent contributions about freight and passenger transportation. Whereas passenger optimization models considered problems such as line planning, train timetabling, platforming, rolling stock circulation, shunting and crew scheduling, freight transportation dealt with issues concerning car blocking, train makeup, routing, and empty car distribution.
The field of rail transportation has clearly received attention resulting in a diversity of literature contribution. As it was difficult to handle the large amount of papers, this work is trying to give a short review of some important contributions made in recent years.
Due to the increase in more sophisticated mathematical techniques, constant refinements in development of the models were made that were able to deal with larger problems. In addition, a trend towards more efficient transportation support systems was observed taking robustness into account. In addition, solution approaches that can deal with larger disturbances of the rail environment in a considerable speed and time, have received attention. Thus, future research can be done to develop more integrated models of scheduling and routing problems of train and passenger transportation to provide robust solutions and problem solving methods that handle disturbances of rail environment
Ant colony optimization with immigrants schemes for the dynamic railway junction rescheduling problem with multiple delays
Train rescheduling after a perturbation is a challenging task and is an important concern of the railway industry as delayed trains can lead to large fines, disgruntled customers and loss of revenue. Sometimes not just one delay but several unrelated delays can occur in a short space of time which makes the problem even more challenging. In addition, the problem is a dynamic one that changes over time for, as trains are waiting to be rescheduled at the junction, more timetabled trains will be arriving, which will change the nature of the problem. The aim of this research is to investigate the application of several different ant colony optimization (ACO) algorithms to the problem of a dynamic train delay scenario with multiple delays. The algorithms not only resequence the trains at the junction but also resequence the trains at the stations, which is considered to be a first step towards expanding the problem to consider a larger area of the railway network. The results show that, in this dynamic rescheduling problem, ACO algorithms with a memory cope with dynamic changes better than an ACO algorithm that uses only pheromone evaporation to remove redundant pheromone trails. In addition, it has been shown that if the ant solutions in memory become irreparably infeasible it is possible to replace them with elite immigrants, based on the best-so-far ant, and still obtain a good performance
Vulnerability Assessment and Re-routing of Freight Trains Under Disruptions: A Coal Supply Chain Network Application
In this paper, we present a two-stage mixed integer programming (MIP) interdiction model in which an interdictor chooses a limited amount of elements to attack first on a given network, and then an operator dispatches trains through the residual network. Our MIP model explicitly incorporates discrete unit flows of trains on the rail network with time-variant capacities. A real coal rail transportation network is used in order to generate scenarios to provide tactical and operational level vulnerability assessment analysis including rerouting decisions, travel and delay costs analysis, and the frequency of interdictions of facilities for the dynamic rail system
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Optimization models and methods for transportation services
Managing transportation services efficiently is essential to both public and private sectors. This dissertation addresses three scheduling problems in modern transportation systems: the network design problem, the train dispatching problem, and the service route design problem. The transportation network design problem with service requirements designs arcs on a directed network and route commodities on the designed arcs so that i) commodities satisfy service requirements and ii) the total cost is minimized. We develop three mathematical programming models: a compact but weak arc-flow formulation, a large but strong path-flow formulation, and a hybrid formulation that uses both the arc-flow and the path-flow representations. We show that the hybrid formulation can significantly strengthen the LP formulation without introducing many variables. To find a good hybrid formulation, we develop columnization and decolumnization algorithms that uses the LP relaxation information to identify commodities that should use the path-flow representation. We also develop valid inequalities for commodities using the path-flow representation. The train dispatching problem schedules the movements of trains on scarce railroad tracks so as to improve the average velocity of trains. We develop a mathematical programming model and strengthen the model using valid inequalities. Besides, we present a heuristic to find a feasible solution quickly, which can serve as the warm-start solution to the MIP solver. For the third problem, we seek to design vehicle routes to deliver and pickup orders for a major grocery chain. We design a GRASP that can incorporate various operational requirements, including warehouse loading capacity, loading sequence, time window requirements, truck volume and weight capacities, and driver time limits. Our GRASP procedure consists of two phases: the solution construction (Phase I) and the Tabu search (Phase II). We show that the neighborhood structure of solutions is highly degenerate, which limits the solution space explored by the Tabu search. We apply the Tabu search with random variable neighborhood to increase the solution space explored.Operations Research and Industrial Engineerin
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