Affectation des locomotives et des wagons aux trains de passagers

A survey of optimization models for train routing and scheduling -- Routing problems -- Scheduling problems -- Simultaneous locomotive and car assignment at VIA Rail Canada -- Solution methodology -- Extensions -- Computational experiments -- A benders decomposition approach for the locomotive and car assignment problem -- Benders decomposition -- Algorithmic refinements -- Computational experiments -- Simultaneous assigment of locomotives and cars to passenger trains -- A basic model -- Solution methodology -- Computational considerations -- Computational experimentation

Multi-Column Generation Model for the Locomotive Assignment Problem

We propose a new decomposition model and a multi-column generation algorithm for solving the Locomotive Assignment Problem (LAP). The decomposition scheme relies on consist configurations, where each configuration is made of a set of trains pulled by the same set of locomotives. We use the concept of conflict graphs in order to reduce the number of trains to be considered in each consist configuration generator problem: this contributes to significantly reduce the fraction of the computational times spent in generating new potential consists. In addition, we define a column generation problem for each set of variables, leading to a multi-column generation process, with different types of columns. Numerical results, with different numbers of locomotives, are presented on adapted data sets coming from Canada Pacific Railway (CPR). They show that the newly proposed algorithm is able to solve exactly realistic data instances for a timeline spanning up to 6 weeks, in very reasonable computational times

Optimization of Locomotive Management and Fuel Consumption in Rail Freight Transport

For the enormous capital investment and high operation expense of locomotives, the locomotive management/assignment and fuel consumption are two of the most important areas for railway industry, especially in freight train transportation. Several algorithms have been developed for the Locomotive Assignment Problem (LAP), including exact mathematics models, approximate dynamic programming and heuristics. These previously published optimization algorithms suffer from scalability or solution accuracy issues. In addition, each of the optimization models lacks part of the constraints that are necessary in real-world train/locomotive operation, e.g., maintenance/shop constraints or consist busting avoidance. Furthermore, there are rarely research works for the reduction of total train energy consumption on the locomotive assignment level. The thesis is organized around our three main contributions. Firstly we propose a “consist travel plan” based LAP optimization model, which covers all the required meaningful constraints and which can efficiently be solved using large scale optimization techniques, namely column generation (CG) decomposition. Our key contribution is that our LAP model can evaluate the occurrence of consist busting using the number of consist travel plans, and allows locomotive status transformation in flow conservation constraints. In addition, a new column generation acceleration architecture is developed, that allows the subproblem, i.e., column generator to create multiple columns in each iteration, that each is an optimal solution for a reduced sub-network. This new CG architecture reduces computational time greatly comparing to our original LAP model. For train fuel consumption, we derive, linearize and integrate a train fuel consumption model into our LAP model. In addition, we establish a conflict-free pre-process for time windows for train rescheduling without touching train-meet time and position. The new LAP-fuel consumption model works fine for the optimization of the train energy exhaustion on the locomotive assignment level. For the optimization models above, the numerical results are conducted on the railway network infrastructure of Canada Pacific Railway (CPR), with up to 1,750 trains and 9 types of locomotives over a two-week time period in the entire CPR railway network

Utilizing Dual Information for Moving Target Search Trajectory Optimization

Various recent events have shown the enormous importance of maritime search-and-rescue missions. By reducing the time to find floating victims at sea, the number of casualties can be reduced. A major improvement can be achieved by employing autonomous aerial systems for autonomous search missions, allowed by the recent rise in technological development. In this context, the need for efficient search trajectory planning methods arises. The objective is to maximize the probability of detecting the target at a certain time k, which depends on the estimation of the position of the target. For stationary target search, this is a function of the observation at time k. When considering the target movement, this is a function of all previous observations up until time k. This is the main difficulty arising in solving moving target search problems when the duration of the search mission increases. We present an intermediate result for the single searcher single target case towards an efficient algorithm for longer missions with multiple aerial vehicles. Our primary aim in the development of this algorithm is to disconnect the networks of the target and platform, which we have achieved by applying Benders decomposition. Consequently, we solve two much smaller problems sequentially in iterations. Between the problems, primal and dual information is exchanged. To the best of our knowledge, this is the first approach utilizing dual information within the category of moving target search problems. We show the applicability in computational experiments and provide an analysis of the results. Furthermore, we propose well-founded improvements for further research towards solving real-life instances with multiple searchers

Freight and passenger railway optimization

Das Ziel dieser Arbeit war es, einen Überblick über die aktuellen Beiträge der Literatur in den Bereichen der Eisenbahnlogistik sowohl im Güter- als auch im Personenverkehr zu geben. Während sich der Güterverkehr mit Problemen der Zusammenstellung der Züge und Waggons beziehungsweise der Verteilung der Leerfahrzeuge auseinander setzte, beschäftigte sich die Eisenbahnlogistik im Bereich des Personenverkehrs mit Optimierungsmodellen bezüglich 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 Beiträgen zu treffen. Deshalb versucht diese Arbeit nur einen kurzen Einblick über einige wichtige Beiträge 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 vernünftigen Zeit zu lösen. Darüber hinaus wurde ein Trend zur Entwicklung effizienterer entscheidungsunterstützender Hilfsprogramme für reale Gegebenheiten der Eisenbahnlogistik beobachtet. Im Großen und Ganzen sollten in Zukunft stärker 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

A rolling horizon approach for the locomotive routing problem at the Canadian National Railway Company

Cette thèse étudie le problème du routage des locomotives qui se pose à la Compagnie des chemins de fer nationaux du Canada (CN) - le plus grand chemin de fer au Canada en termes de revenus et de taille physique de son réseau ferroviaire. Le problème vise à déterminer la séquence des activités de chaque locomotive sur un horizon de planification donné. Dans ce contexte, il faut prendre des décisions liées à l'affectation de locomotives aux trains planifiés en tenant compte des besoins d'entretien des locomotives. D’autres décisions traitant l'envoi de locomotives aux gares par mouvements à vide, les déplacements légers (sans tirer des wagons) et la location de locomotives tierces doivent également être prises en compte. Sur la base d'une formulation de programmation en nombres entiers et d'un réseau espace-temps présentés dans la littérature, nous introduisons une approche par horizon roulant pour trouver des solutions sous-optimales de ce problème dans un temps de calcul acceptable. Une formulation mathématique et un réseau espace-temps issus de la littérature sont adaptés à notre problème. Nous introduisons un nouveau type d'arcs pour le réseau et de nouvelles contraintes pour le modèle pour faire face aux problèmes qui se posent lors de la division de l'horizon de planification en plus petits morceaux. Les expériences numériques sur des instances réelles montrent les avantages et les inconvénients de notre algorithme par rapport à une approche exacte.This thesis addresses the locomotive routing problem arising at the Canadian National Railway Company (CN) - the largest railway in Canada in terms of both revenue and the physical size of its rail network. The problem aims to determine the sequence of activities for each locomotive over the planning horizon. Besides assigning locomotives to scheduled trains and considering scheduled locomotive maintenance requirements, the problem also includes other decisions, such as sending locomotives to stations by deadheading, light traveling, and leasing of third-party locomotives. Based on an Integer Programming formulation and a Time-Expanded Network presented in the literature, we introduce a Rolling Horizon Approach (RHA) as a method to find near-optimal solutions of this problem in acceptable computing time. We adapt a mathematical formulation and a space-time network from the literature. We introduce a new type of arcs for the network and new constraints for the model to cope with issues arising when dividing the planning horizon into smaller ones. Computational experiments on real-life instances show the pros and cons of our algorithm when compared to an exact solution approach

Quadratic stabilization of Benders decomposition

The foundational Benders decomposition, or variable decomposition, is known to have the inherent instability of cutting plane-based methods. Several techniques have been proposed to improve this method, which has become the state of the art for important problems in operations research. This paper presents a complementary improvement featuring quadratic stabilization of the Benders cutting-plane model. Inspired by the level-bundle methods of nonsmooth optimization, this algorithmic improvement is designed to reduce the number of iterations of the method. We illustrate the interest of the stabilization on two classical problems: network design problems and hub location problems. We also prove that the stabilized Benders method has the same theoretical convergence properties as the usual Benders method