Resource constrained routing and scheduling: Review and research prospects

In the service industry, it is crucial to efficiently allocate scarce resources to perform tasks and meet particular service requirements. What considerably complicates matters is when these resources, for example skilled technicians, nurses, and home carers have to visit different customer locations. This paper provides a comprehensive survey on resource constrained routing and scheduling that unveils the problem characteristics with respect to resource qualifications, service requirements and problem objectives. It also identifies the most effective exact and heuristic algorithms for this class of problems. The paper closes with several research prospects

Managing Advanced Synchronization Aspects in Logistics Systems

In this thesis, we model various complex logistics problems and develop appropriate techniques to solve them. We improve industrial practices by introducing synchronized solutions to problems that were previously solved independently. The first part of this thesis focuses on cross-docks. We simultaneously optimize supplier orders and cross-docking operations to either reduce the storage space required or evenly distribute workload over the week. The second part of this thesis is devoted to transport problems in which two types of vehicles are synchronized, one of which can be transported by the other. The areas of application range from home services to parcel delivery to customers. After analyzing the complexity associated with these synchronized solutions (i.e., largescale problems for which the decisions depend on each other), we design algorithms based on the "destroy-and-repair" principle to find efficient solutions. We also introduce mathematical programs for all the considered problems. The problems under study arose directly from collaborations with various industrial partners. In this respect, our achieved solutions have been benchmarked with current industrial practice. Depending on the problem, we have been able to reduce the environmental impact generated by the industrial activities, the overall cost, or the social impact. The achieved gains compared to current industrial practice range from 10 to 70%, depending on the application. -- Dans cette thèse, nous modélisons divers problèmes logistiques complexes et développons des techniques appropriées pour les résoudre. Nous cherchons à améliorer certaines pratiques industrielles en introduisant des solutions synchronisées à des problèmes qui étaient auparavant résolus indépendamment. La première partie de cette thèse porte sur les cross-docks. Nous optimisons simultanément les commandes fournisseurs et les opérations au sein de la plateforme de logistique pour réduire l’espace de stockage requis ou répartir uniformément la charge de travail sur la semaine. La deuxième partie de cette thèse est consacrée aux problèmes de transport dans lesquels deux types de véhicules sont synchronisés, l’un pouvant être transporté par l’autre. Les domaines d’application vont du service à domicile à la livraison de colis chez des clients. Après avoir analysé la complexité des solutions synchronisées (c’est-à-dire des problèmes de grandes dimensions pour lesquels les décisions dépendent les unes des autres), nous concevons des algorithmes basés sur le principe de "destruction / reconstruction" pour trouver des solutions efficaces. Nous modélisons également les problèmes considérés avec la programmation mathématique. Les problèmes à l’étude viennent de collaborations avec divers partenaires industriels. A cet égard, les solutions que nous présentons sont comparées aux pratiques industrielles actuelles. En fonction du problème, nous avons pu réduire l’impact environnemental généré par les activités industrielles, le coût global, ou l’impact social des solutions. Les gains obtenus par rapport aux pratiques industrielles actuelles varient de 10 à 70%, selon l’application. Mot-clefs: Logistique, Synchronisation, Problème de transport, Tournée de véhicules, Plateforme de Cross-dock (transbordement), Programmation Mathématiques, Métaheuristiques, Matheuristiques, Instances Réelle

Résolution de problèmes de tournées avec synchronisation : applications au cas multi-échelons et au cross-docking

Transportation systems are more and more interconnected, this has lead to a new kind of constraints, called synchronization constraints, in vehicle routing problems. In this thesis, we study two cases in which this type of constraints arises. First, we propose a heuristic method for a two-echelon problem arising in City Logistics. Second, we study the integration of a cross-dockin pickup and delivery vehicle routing problems. To that end we propose a matheuristic for the vehicule routing problem with cross-docking, and we propose an extension of this problem that integrates specific resource synchonization constraints arising at the cross-dock. A method for a 3D loading problem is also presented.L’interconnexion croissante dans les systèmes de transports a conduit à la modélisation de nouvelles contraintes, dites contraintes de synchronisation, dans les problèmes de tournées de véhicules. Dans cette thèse, nous nous intéressons à deux cas dans lesquels ce type de problématiques apparaît. Dans un premier temps, nous proposons une méthode heuristique pour un problème à deux échelons rencontré pour la distribution de marchandises en ville. Dans un second temps, nous étudions l’intégration d’un cross-dock dans des tournées de collectes et livraisons. Une première contribution à ce sujet concerne le problème de tournées de véhicules avec cross-docking, et une seconde contribution intègre, en plus, des contraintes de ressources au cross-dock dans le problème de routage. Une méthode pour un problème de chargement 3D, étudié lors d’un stage doctoral en entreprise, est également présentée

Optimization of a city logistics transportation system with mixed passengers and goods

International audienceIn this paper, we propose a mathematical model and an adaptive large neighborhood search to solve a two{tiered transportation problem arising in the distribution of goods in congested city cores. In the rst tier, goods are transported in city buses from a consolidation and distribution center to a set of bus stops. The main idea is to use the buses spare capacity to drive the goods in the city core. In the second tier, nal customers are distributed by a eet of near{zero emissions city freighters. This system requires transferring the goods from buses to city freighters at the bus stops. We model the corresponding optimization problem as a variant of the pickup and delivery problem with transfers and solve it with an adaptive large neighborhood search. To evaluate its results, lower bounds are calculated with a column generation approach. The algorithm is assessed on data sets derived from a eld study in the medium-sized city of La Rochelle in France

Multi-robot task allocation system to improve assistance in domestic scenarios

The AURORA project aims at developing new strategies to take assistive robotics a step further. In order to provide extended services to potential users, engaging a team of simpler robots is often preferable to using a unique, super-capable robot. In such multi-robot systems, the coordination for task execution is one of the major challenges to overcome. The present thesis proposes a solution to the specific issue of multi-robot task allocation within an heterogeneous team of robots, with additional inter-task precedence constraints. The main elements of the state of the art that support this project are reported, including useful taxonomies and existing methods. From the analyzed solutions, the one that better fits with the constraints of the project is an iterated auction-based algorithm able to manage precedence constraints, which has been modified to handle heterogeneity and partial scheduling. The selected solution has been designed and implemented with the particular purpose of being applied to the robotized kitchen setup of the AURORA project; it is however flexible and scalable and can therefore be applied to other use-cases, for instance vehicle-routing problems. Several evaluation scenarios have been tested, that demonstrate the good functioning and characteristics of the system, as well as the possibility to integrate humans into the task assignation process

A branch-cut-and-price approach for the single-trip and multi-trip two-echelon vehicle routing problem with time windows

International audienceThe paper studies the two-echelon capacitated vehicle routing problem with time windows, in which delivery of freight from depots to customers is performed using intermediate facilities called satellites. We consider the variant of the problem with precedence constraints for unloading and loading freight at satellites. In this variant allows for storage and consolidation of freight at satellites. Thus, the total transportation cost may decrease in comparison with the alternative variant with exact freight synchronization at satellites. We suggest a mixed integer programming formulation for the problem with an exponential number of route variables and an exponential number of precedence constraints which link first-echelon and second-echelon routes. Routes at the second echelon connecting satellites and clients may consist of multiple trips and visit several satellites. A branch-cut-and-price algorithm is proposed to solve efficiently the problem. This is the first exact algorithm in the literature for the multi-trip variant of the problem. We also present a post-processing procedure to check whether the solution can be transformed to avoid freight consolidation and storage without increasing its transportation cost. It is shown that all single-trip literature instances solved to optimality admit optimal solutions of the same cost for both variants of the problem either with precedence constraints or with exact synchronization constraints. Experimental results reveal that our algorithm can be used to solve these instances significantly faster than another recent approach proposed in the literature

Shared Mobility Optimization in Large Scale Transportation Networks: Methodology and Applications

abstract: Optimization of on-demand transportation systems and ride-sharing services involves solving a class of complex vehicle routing problems with pickup and delivery with time windows (VRPPDTW). Previous research has made a number of important contributions to the challenging pickup and delivery problem along different formulation or solution approaches. However, there are a number of modeling and algorithmic challenges for a large-scale deployment of a vehicle routing and scheduling algorithm, especially for regional networks with various road capacity and traffic delay constraints on freeway bottlenecks and signal timing on urban streets. The main thrust of this research is constructing hyper-networks to implicitly impose complicated constraints of a vehicle routing problem (VRP) into the model within the network construction. This research introduces a new methodology based on hyper-networks to solve the very important vehicle routing problem for the case of generic ride-sharing problem. Then, the idea of hyper-networks is applied for (1) solving the pickup and delivery problem with synchronized transfers, (2) computing resource hyper-prisms for sustainable transportation planning in the field of time-geography, and (3) providing an integrated framework that fully captures the interactions between supply and demand dimensions of travel to model the implications of advanced technologies and mobility services on traveler behavior.Dissertation/ThesisDoctoral Dissertation Civil, Environmental and Sustainable Engineering 201

Applications of biased-randomized algorithms and simheuristics in integrated logistics

Transportation and logistics (T&L) activities play a vital role in the development of many businesses from different industries. With the increasing number of people living in urban areas, the expansion of on-demand economy and e-commerce activities, the number of services from transportation and delivery has considerably increased. Consequently, several urban problems have been potentialized, such as traffic congestion and pollution. Several related problems can be formulated as a combinatorial optimization problem (COP). Since most of them are NP-Hard, the finding of optimal solutions through exact solution methods is often impractical in a reasonable amount of time. In realistic settings, the increasing need for 'instant' decision-making further refutes their use in real life. Under these circumstances, this thesis aims at: (i) identifying realistic COPs from different industries; (ii) developing different classes of approximate solution approaches to solve the identified T&L problems; (iii) conducting a series of computational experiments to validate and measure the performance of the developed approaches. The novel concept of 'agile optimization' is introduced, which refers to the combination of biased-randomized heuristics with parallel computing to deal with real-time decision-making.Las actividades de transporte y logística (T&L) juegan un papel vital en el desarrollo de muchas empresas de diferentes industrias. Con el creciente número de personas que viven en áreas urbanas, la expansión de la economía a lacarta y las actividades de comercio electrónico, el número de servicios de transporte y entrega ha aumentado considerablemente. En consecuencia, se han potencializado varios problemas urbanos, como la congestión del tráfico y la contaminación. Varios problemas relacionados pueden formularse como un problema de optimización combinatoria (COP). Dado que la mayoría de ellos son NP-Hard, la búsqueda de soluciones óptimas a través de métodos de solución exactos a menudo no es práctico en un período de tiempo razonable. En entornos realistas, la creciente necesidad de una toma de decisiones "instantánea" refuta aún más su uso en la vida real. En estas circunstancias, esta tesis tiene como objetivo: (i) identificar COP realistas de diferentes industrias; (ii) desarrollar diferentes clases de enfoques de solución aproximada para resolver los problemas de T&L identificados; (iii) realizar una serie de experimentos computacionales para validar y medir el desempeño de los enfoques desarrollados. Se introduce el nuevo concepto de optimización ágil, que se refiere a la combinación de heurísticas aleatorias sesgadas con computación paralela para hacer frente a la toma de decisiones en tiempo real.Les activitats de transport i logística (T&L) tenen un paper vital en el desenvolupament de moltes empreses de diferents indústries. Amb l'augment del nombre de persones que viuen a les zones urbanes, l'expansió de l'economia a la carta i les activitats de comerç electrònic, el nombre de serveis del transport i el lliurament ha augmentat considerablement. En conseqüència, s'han potencialitzat diversos problemes urbans, com ara la congestió del trànsit i la contaminació. Es poden formular diversos problemes relacionats com a problema d'optimització combinatòria (COP). Com que la majoria són NP-Hard, la recerca de solucions òptimes mitjançant mètodes de solució exactes sovint no és pràctica en un temps raonable. En entorns realistes, la creixent necessitat de prendre decisions "instantànies" refuta encara més el seu ús a la vida real. En aquestes circumstàncies, aquesta tesi té com a objectiu: (i) identificar COP realistes de diferents indústries; (ii) desenvolupar diferents classes d'aproximacions aproximades a la solució per resoldre els problemes identificats de T&L; (iii) la realització d'una sèrie d'experiments computacionals per validar i mesurar el rendiment dels enfocaments desenvolupats. S'introdueix el nou concepte d'optimització àgil, que fa referència a la combinació d'heurístiques esbiaixades i aleatòries amb informàtica paral·lela per fer front a la presa de decisions en temps real.Tecnologies de la informació i de xarxe