Le Problème de Transport à la Demande (PTD), consiste à prendre en charge le transport des personnes d'un lieu de départ vers un lieu d'arrivée. Il est caractérisé par un ensemble de demandes de transport et d'un nombre de véhicules disponible. L'ultime objectif dans ce travail de thèse est d'offrir une alternative optimisée au déplacement individuel et collectif. Le PTD est classé parmi les problèmes NP-difficile, la majorité des travaux de recherche ont été concentrés sur l'utilisation des méthodes approchées pour le résoudre.Ce problème est également multicritère, la solution proposée dans ce travail permet à la fois une réduction du temps de voyage et également de la distance parcourue. Dans cette thèse, nous proposons notre contribution à l'étude et à la résolution du problème de transport à la demande multicritère et dynamique en appliquant l'algorithme de recuit simulé multi-objectif. Une grande partie de notre travail concerne la conception, le développement et la validation des approches qui permettent de donner des solutions optimales ou quasi optimales, pour un PTD. Ces approches utilisent une méthode multicritère qui s’appuie sur l’algorithme de recuit simulé. La modélisation du PTD est représentée par une architecture multi-acteurs. Cette architecture met en évidence l’aspect distribué du système ainsi que les interactions et les relations qui peuvent avoir lieu entre les différents acteurs. Nous présentons dans ce travail un Système Multi-Agents pour la planification des itinéraires des véhicules affectés au transport des voyageurs. Les agents de ce système utilisent le module d’optimisation développé dans la première partie / The Dial a Ride Problem (DRP) is to take passengers from a place of departures to places of arrivals. Different versions of the dynamic Dial a Ride Problem are found in every day practice; transportation of people in low-density areas, transportation of the handicapped and elderly persons and parcel pick-up and delivery service in urban areas. In the DRP, customers send transportation requests to an operator. A request consists of a specified pickup location and destination location along with a desired departure or arrival time. The ultimate aim is to offer an alternative to displacement optimized individually and collectively. The DRP is classified as NP-hard problem that’s why most research has been concentrated on the use of approximate methods to solve it. Indeed the DRP is a multi-criteria problem, the proposed solution of which aims to reduce both route duration in response to a certain quality of service provided. In this thesis, we offer our contribution to the study and solving the DRP in the application using a multi agent system based on the Multi-Objective Simulated Annealing Algorithm

During the past several decades, agricultural intensification has been crucial to increase the food supply. Several processes related to intensification are very detrimental to the environment, particularly biodiversity. Today, agriculture is facing the challenge of satisfying its demand for food while improving its environmental sustainability. Knowledge of the shape of the relationship between biodiversity and intensity is necessary to determine both where conservation policies will be most effective and how to allocate intensity to reconcile production and biodiversity. Few empirical studies on this relationship exist, and the influence of the spatial arrangement of intensity on biodiversity remains untested. This Ph.D. thesis determined how to target both agricultural intensity and its spatial allocation for meeting production and conservation objectives of farmlands. To answer this research question, we used a country-scaled approach that combined two France-scaled databases that describe agriculture and farmland birds. We characterized a nationwide gradient of agricultural intensity and studied a farmland bird community along this gradient, using several trait-based descriptors (specialization, trophic level, and species main habitat). Agricultural intensity and bird communities were described at the Small Agricultural Region (SAR; mean width = 22.4 km) level. As a first step, we developed a novel method to estimate an intensity indicator that was based on Input Costs/ha, with SAR resolution. This indicator provides a continuous intensity measure that is relevant across different types of agricultural systems. Secondly, we investigated the effects of a gradient of land uses (grassland to arable land) and its heterogeneity on the bird community. We found habitat specialists suffered from habitat loss, while generalists benefited from heterogeneity. Thirdly, we showed that the community responded significantly to intensity, with winner species replacing loser species along the gradient. The shift between losers and winners was sharper at low intensities. Interestingly, spatial aggregation of intensity had a strengthening effect on the bird community. Finally, the relationships linking intensity to the bird community, food production, and economic performance were integrated into a model aimed at optimizing intensity allocation. Optimal allocations reached win-no-lose solutions with the three criteria. They corresponded to targeted intensity modifications: many small changed, favoring homogeneous, extensive clusters, were optimal within an extensification scenario; while a few large changes, favoring heterogeneity, were optimal within an intensification scenario. We provide one of the first studies demonstrating that spatial aggregation of intensity can influence the biodiversity/intensity relationship. Our results also provide an opportunity to improve the effectiveness of conservation policies, at national scales, with spatial targeting: opposite targeting should be performed either to maximize biodiversity benefits or to increase production, while mitigating biodiversity impacts. Our results highlight the importance of mixed allocation strategies between land sparing/sharing extremes. In order to put these opportunities into effect, further research should address the technical solutions that achieve intensity modification at the farm level and design targeted policies that benefit biodiversity and other environmental criteria

Uppsatsen undersöker hur Emballator Växjöplast prioriterar och resonerar kring aspekterna volymutnyttjande, plocktid, säkerhet, kapitalbindning och servicenivå vid optimering av deras färdigvarulager. Författarna kom fram till följande slutsats: Fallföretaget prioriterar säkerhet högst för att skydda individen Servicenivå prioriteras efter säkerhet då de arbetar kundfokuserat. Efter servicenivå prioriteras volymutnyttjande för att minska sin externlagring. Plocktid prioriteras efter volymutnyttjande där målsättningen är att undvika nyanställningar. Sist prioriteras kapitalbindning då denna inte är fokus för logistikfunktionen.   Vidare undersöker författarna hur en multi-criteria optimization av aspekterna vid optimering av färdigvarulagret kan gå till. Författarna kommer fram till följande slutsatser: The main criteria method är bäst lämpad optimeringsmetod. Volymutnyttjande ska minimeras givet att resterande aspekter uppfyller respektive bivillkor. De flesta förvaringsmetoder och artikelplaceringar uppfyller aspekternas bivillkor Bäst lämpad förvaringsmetod och artikelplacering grundas därför på vilken som möjliggör bäst volymutnyttjande. Slutligen utvärderas Emballator Växjöplasts nuvarande färdigvarulager sett till aspekterna utifrån analysen för frågeställning 2. Här presenteras även kortsiktiga och långsiktiga förbättringsförslag. Författarna kom fram till följande slutsats: Deras nuvarande förpackning, förvaringsmetod samt artikelplacering tillgodoser respektive bivillkor men kan förbättras sett till the main criteria, volymutnyttjande. Ett kortsiktigt förbättringsförslag genom att utföra en liknande artikelplacering på bättre sätt kan upp till 38-57 fler pallar rymmas på färdigvarulagret. Ett långsiktigt förbättringsförslag genom att kombinera traditionella pallställage och drive-through eller push-back-hyllor, kan totala antal pallplatser på färdigvarulagret öka med 18,4 %. / The essay examines how Emballator Växjöplast prioritize and reason among the aspects safety, service level, utilization rate, order picking time and capital tied up in inventory when optimizing their finished goods warehouse. The authors came to the following conclusion: Firstly, they prioritize safety the highest to protect the individuals within the warehouse. Service level is prioritized secondly because they operate with a customer focus. After service level utilization rate is prioritized to lower their need for external storage. Order picking time is prioritized after utilization rate with the goal to avoid the need for employing more operators within the warehouse. Lastly capital tied up in inventory is prioritized because the aspect is not in focus for the logistics department.   Moreover, the authors investigate how multi-criteria optimization as an optimization method can be used when optimizing a finished goods warehouse considering several contradictive aspects and the conclusion is: The main criteria method is best suited in optimization method. Utilization rate is the main criteria and the other aspects are constraints. The majority of storage systems and storage assignment policy are within the constraints. The best storage systems and storage assignment policy is therefore mainly determined by the main criteria.   Lastly a discussion regarding the finished goods warehouse is held and both short term and long term improvements regarding the aspects are presented. The conclusions made by the authors are as follows: Their current packaging, storage systems and storage assignment policy is sufficient in terms of the different constraints but the main criteria can be improved. Short term improvements are to use a similar storage assignment policy in a better way and enable room for 38-57 more pallets in the finished goods warehouse. Long term improvements are to improve both storage assignment policy and the storage system. By combining traditional racks with some other storage system such as drive-through or push-back-shelves the number of pallets that can fit within the warehouse can increase by 18,4%.

En chirurgie mini-invasive guidée par l’image, une planification préopératoire précise des trajectoires des outils chirurgicaux est un facteur clé pour une intervention réussie. Cependant, une planification efficace est une tâche difficile, qui peut être considérablement améliorée en considérant différents facteurs contributifs tels que les déformations biomécaniques intra-opératoires, ou en introduisant de nouvelles techniques d'optimisation. Dans ce travail, nous nous concentrons sur deux aspects. Le premier aspect porte sur l'intégration de la déformation intra-opératoire dans le processus de planification de trajectoire. Nos méthodes combinent des techniques d'optimisation géométrique à base de simulations biomécaniques. Elles sont caractérisées par un certain niveau de généralité, et ont été expérimentées sur deux types d’interventions chirurgicales: les procédures percutanées pour l'ablation de tumeurs hépatiques, et la stimulation cérébrale profonde en neurochirurgie. Deuxièmement, nous étudions, mettons en œuvre, et comparons plusieurs approches d'optimisation en utilisant des méthodes qualitatives et quantitatives, et nous présentons une méthode efficace d'optimisation évolutionnaire multicritères à base de Pareto qui permet de trouver des solutions optimales qui ne sont pas accessibles par les méthodes existantes. / In image-guided minimally invasive surgery, a precise preoperative planning of the surgical tools trajectory is a key factor to a successful intervention. However, an efficient planning is a challenging task, which can be significantly improved when considering different contributing factors such as biomechanical intra-operative deformations, or novel optimization techniques. In this work, we focus on two aspects. The first aspect addresses integrating intra-operative deformation to the path planning process. Our methods combine geometric-based optimization techniques with physics-based simulations. They are characterized with a certain level of generality, and are experimented on two different surgical procedures: percutaneous procedures for hepatic tumor ablation, and in neurosurgery for Deep Brain Stimulation (DBS). Secondly, we investigate, implement, and compare many optimization approaches using qualitative and quantitative methods, and present an efficient evolutionary Pareto-based multi-criteria optimization method which can find optimal solutions that are not reachable via the current state of the art methods.

La moitié des forêts tropicales du monde est désignée comme des forêts de production par les services forestiers nationaux. Si l'effet de la déforestation sur les émissions de carbone et les pertes de biodiversité en région tropicale ont fait l'objet de nombreuses études, les impacts à long terme de l'exploitation commerciale de bois sur ces forêts restent à ce jour très peu étudiés. Or, les enjeux sont grandissants pour ces forêts de production. Non seulement elles doivent alimenter le commerce du bois tropical, mais leur rôle dans le stockage de carbone et dans la préservation de la biodiversité est de plus en plus reconnu. La thèse développée ici s'organise en trois temps. Premièrement, un modèle de bilan carbone de l'exploitation forestière est développé, et les différences régionales de dynamique de récupération du carbone post-exploitation sont modelisées. Deuxièmement, un modèle de récupération du volume de bois d'oeuvre a été développé et calibré à l'échelle amazonienne. Ces résultats ont permis de montrer la lenteur de la récupération du volume de bois d'Amazonie, et la non-durabilité des pratiques actuelles d'exploitation. Ces modèles (carbone et bois d'oeuvre) ont été élaborés dans un cadre bayésien, avec l'appui et les données du Tropical managed Forest Observatory (www.tmfo.org), réseau rassemblant 9 institutions de recherche et plus de 200 parcelles de suivi de la dynamique forestière après exploitation en Amazonie. Enfin, une analyse comparative de scénarios prospectifs a été effectuée, où les compromis possibles entre services écosystémiques (bois d'oeuvre, carbone et biodiversité) ont été explorés par des techniques d'optimisation multicritères. / Half of the world's tropical forets are designated by national forest services as production forests. While here have been numerous studies on the impact if devorestation on carbon emissions and biodiversity loss in the tropics, the long-term impacts of selective logging are still poorly studied; However, the importance of these production forests is increasing. Not only must they meet the growing tropical timber demand, but their role in Carbon storage and the biodiversity conservation is increasingly recognized. The studies developped in this thesis are threefold. First, a carbon balance model of logging is developped, and regional differences in post-logging carbon recovery of timber volume on the Amazon, and thus the unsustainability of current logging practices. These models (carbon and timber) were developped on a Bayesian framework, with support and data from the Tropical managed Forest Observatory (TmFO : www.tmfo.org), a netword of 9 research institutions and more than 200 forest plotswhere post-logging forest dynamics have been monitored for <30 years in the Amazon. Finally, a comparative analysis of prospective scenarios was carried out, where potential tradeoffs between ecosystem services (timber, carbone and biodiversity) were explored using multi-criteria optimization analysis.

The work deals with the optimization of trusses construction building and transport machinery. The goal was to create an algorithm that can design an optimized design. The simulation took place on two experiments involving 52 sets of different entries, which are processed in detail into graphs. One-dimensional target mass or price function is used as part of optimization, but there is also an incorporated multidimensional purpose function. The finite element variation method for the beam system is used for the strength calculation of the truss structure and the genetic algorithm is used for optimization. At the end of the work, specific steps are formulated that lead to the most appropriate algorithm settings.

[ES] En esta tesis doctoral se estudia el problema de secuenciación de máquinas paralelas no relacionadas con necesidad de ajustes y recursos adicionales asignados en los ajustes. En este problema, se tiene un grupo de tareas (también llamadas trabajos), donde cada una debe ser procesada en una de las máquinas paralelas disponibles. Para procesar una tarea después de otra en la misma máquina, se debe hacer un ajuste en la máquina. Se asume que estos ajustes deben ser realizados por un recurso adicional limitado (por ejemplo, operarios). En esta tesis doctoral se estudian dos variantes del problema planteado: 1) considerando el problema con el único objetivo de minimizar el tiempo máximo de finalización de todos los trabajos (makespan), y 2) considerando el problema multi-objetivo minimizando simultáneamente el makespan y el consumo máximo de recursos adicionales. Inicialmente, se realiza una completa revisión bibliográfica sobre estudios relacionados con el problema planteado. En esta revisión se detecta que, a pesar de existir numerosos estudios de secuenciación de máquinas paralelas, no muchos de estos estudios tienen en cuenta recursos adicionales. Posteriormente, para introducir el problema a estudiar antes de plantear métodos de resolución, se realiza una breve explicación de los principales problemas de secuenciación de máquinas paralelas. El problema de un solo objetivo está clasificado como NP-Hard. Por ello, para abordar su resolución se han diseñado e implementado heurísticas y metaheurísticas siguiendo dos enfoques diferentes. Para el primer enfoque, que ignora la información sobre el consumo de recursos adicionales en la fase constructiva, se adaptan dos de los mejores algoritmos existentes en la literatura para el problema de máquinas paralelas con ajustes sin necesidad de recursos adicionales. En el segundo enfoque, que sí tiene en cuenta la información sobre el consumo de recursos adicionales en la fase constructiva, se proponen nuevos algoritmos heurísticos y metaheurísticos para resolver el problema. Tras analizar los resultados de los experimentos computacionales realizados, concluimos que hay diferencias entre los dos enfoques, siendo significativamente mejor el enfoque que tiene en cuenta la información sobre los recursos adicionales. Al igual que en el caso de un solo objetivo, la complejidad del problema multi-objetivo obliga a presentar algoritmos heurísticos o metaheurísticos para resolverlo. En esta tesis se presenta un nuevo algoritmo metaheurístico multi-objetivo eficiente para encontrar buenas aproximaciones a la frontera de Pareto del problema. Además, se adaptaron otros tres algoritmos que han mostrado buenos resultados en diferentes estudios de problemas de secuenciación de máquinas multi-objetivo. Después de realizar experimentos computacionales exhaustivos, concluimos que el nuevo algoritmo propuesto en esta tesis es significativamente mejor que los otros tres algoritmos existentes, y que se han adaptado para resolver este problema. / [CAT] En aquesta tesi doctoral s'estudia el problema de seqüenciació de màquines paral·leles no relacionades amb necessitat d'ajustos i recursos addicionals assignats en els ajustos. En aquest problema, es tenen un grup de tasques (també anomenades treballs), on cadascuna ha de ser processada en una de les màquines paral·leles disponibles. Per processar una tasca després d'una altra en la mateixa màquina, s'ha de fer un ajustament en la màquina. S'assumeix que aquests ajustos en les màquines per a processar una tasca després del processament d'una altra, han de ser realitzats per un recurs addicional limitat (per exemple, operaris). En aquesta tesi doctoral s'estudien dos variants al problema plantejat: 1) considerant el problema com l'únic objectiu de minimitzar el temps màxim de finalització de tots els treballs (makespan), i 2) considerant el problema multi-objectiu minimitzant simultàniament el makespan i el consum màxim de recursos addicionals. Inicialment, es realitza una completa revisió bibliogràfica sobre estudis relacionats amb el problema plantejat. En esta revisió es detecta que, tot i existir nombrosos estudis de seqüenciació de màquines paral·leles, hi ha molts pocs que tenen en compte recursos addicionals. Posteriorment, per introduir el problema a estudiar abans de plantejar mètodes de resolució, es realitza una breu explicació dels principals problemes de seqüenciació de màquines paral·leles. El problema d'un sol objectiu està classificat com NP-Hard. Per això, per abordar la seua resolució s'han dissenyat i implementat heurístiques y metaheurístiques seguint dos enfocs diferents. El primer enfoc ignora la informació sobre el consum de recursos en la fase constructiva, adaptant dos dels millors algoritmes existents en la literatura per al problema de seqüenciació de màquines paral·leles amb ajustaments sense necessitat de recursos. Per al segon enfoc si es té en compte la informació sobre el consum de recursos en la fase constructiva. Després d'analitzar els resultats dels experiments computacionals realitzats, concloem que hi ha diferencies entre els dos enfocs, sent significativament millor l'enfoc que té en compte la informació sobre el recursos. De la mateixa manera que en el cas d'un sol objectiu, la complexitat del problema multi-objectiu obliga a presentar algoritmes heurístics o metaheurístics per a resoldre-ho. En aquesta tesi es presenta un nou algoritme metaheurístic multi-objectiu eficient per trobar bones aproximacions a la frontera de Pareto del problema. A més, es van adaptar altres tres algoritmes que han mostrat bons resultats en diferents estudis de problemes de seqüenciació de màquines multi-objectiu. Després de realitzar experiments computacionals exhaustius, concloem que el nou algoritme proposat en aquesta tesi és significativament millor que els altres tres algoritmes existents i que s'han adaptat per resoldre aquest problema. / [EN] In this thesis we study the unrelated parallel machine scheduling problem with setup times and additional limited resources in the setups. In this problem, we have a group of tasks (also called jobs), where each one must be processed on one of the available parallel machines. To process one job after another on the same machine, a setup must be made on the machine. It is assumed that these setups on machines must be made by a limited additional resource (eg, operators). In this thesis two variants of the problem are studied: 1) considering the problem with the objective of minimizing the maximum completion time of all jobs (makespan), and 2) considering the multi-objective problem, minimizing the makespan and the maximum consumption of additional resources. Initially, a complete literature review is carried out on studies related to the problem addressed in this thesis. This review finds that despite numerous parallel machine scheduling studies, there are very few that take into account additional resources. Subsequently, to introduce the problem addressed before proposing resolution methods, a brief explanation of the main parallel machines scheduling problems is made. The problem with a single objective is classified as NP-Hard. Therefore, to solve it, heuristics and metaheuristics have been designed and implemented following two different approaches. For the first approach, which ignores the information on the consumption of resources in the construction phase, two of the best algorithms existing in the literature for the problem of parallel machines with setups without additional resources are adapted. For the second approach, which does take into account information on the consumption of resources in the construction phase, new heuristic and metaheuristic algorithms are proposed to solve the problem. Following the results of the computational experiments, we conclude that there are differences between the two approaches, the approach that takes into account the information on resources being significantly better. As in the case of a single objective, the complexity of the multi-objective problem requires the formulation of heuristic or metaheuristic algorithms to solve it. In this thesis, a new efficient multi-objective metaheuristic algorithm is presented to find good approximations to the Pareto front of the problem. In addition, three other algorithms that have shown good results in different studies of multi-objective machine scheduling problems were adapted. After carrying out exhaustive computational experiments, we concluded that the new algorithm proposed in this thesis is significantly better than the other three adapted algorithms. / Yepes Borrero, JC. (2020). Secuenciación de máquinas con necesidad de ajustes y recursos adicionales [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/158742

<p>Network and system management has always been of concern for telecommunication and computer system operators. The need for standardization was recognised already 20 years ago, hence several standards for network management exist today. However, the ever-increasing number of units connected to networks and the ever-increasing number of services being provided results in significant increased complexity of average network environments. This challenges current management systems. In addition to the general increase in complexity the trend among network owners and operators of merging several single service networks into larger, heterogeneous and complex full service networks challenges current management systems even further. The full service networks will require management systems more powerful than what is possible to realize basing systems purely on todays management standards. This thesis presents a distributed stochastic optimization algorithm which enables implementations of highly robust and efficient management tools. These tools may be integrated into management systems and potentially make the systems more powerful and better prepared for management of full service networks.</p><p>Emergent behavior is common in nature and easily observable in colonies of social insects and animals. Even an old oak tree can be viewed as an emergent system with its collection of interacting cells. Characteristic for any emergent system is how the overall behavior of the system emerge from many relatively simple, restricted behaviors interacting, e.g. a thousand ants building a trail, a flock of birds flying south or millions of cells making a tree grow. No centralized control exist, i.e. no single unit is in charge making global decisions. Despite distributed control, high work redundancy and stochastic behavior components, emergent systems tend to be very efficient problem solvers. In fact emergent systems tend to be both efficient, adaptive and robust which are three properties indeed desirable for a network management system. The algorithm presented in this thesis relates to a class of emergent behavior based systems known as swarm intelligence systems, i.e. the algorithm is potentially efficient, adaptive and robust.</p><p>On the contrary to other related swarm intelligence algorithms, the algorithm presented has a thorough formal foundation. This enables a better understanding of the algorithm’s potentials and limitations, and hence enables better adaptation of the algorithm to new problem areas without loss of efficiency, adaptability or robustness. The formal foundations are based on work by Reuven Rubinstein on cross entropy driven optimization. The transition from Ruinstein’s centralized and synchronous algorithm to a distributed and asynchronous algorithm is described, and the distributed algorithm’s ability to solve complex problems (NP-complete) efficiently is demonstrated.</p><p>Four examples of how the distributed algorithm may be applied in a network management context are presented. A system for finding near optimal patterns of primary/backup paths together with a system for finding cyclic protection paths in mesh networks demonstrate the algorithm’s ability to act as a tool helping management system to ensure quality of service. The algorithm’s potential as a management policy implementation mechanism is also demonstrated. The algorithm’s adaptability is shown to enable resolution of policy conflicts in a soft manner causing as little loss as possible. Finally, the algorithm’s ability to find near optimal paths (i.e. sequences) of resources in networks of large scale is demonstrated.</p>

Network and system management has always been of concern for telecommunication and computer system operators. The need for standardization was recognised already 20 years ago, hence several standards for network management exist today. However, the ever-increasing number of units connected to networks and the ever-increasing number of services being provided results in significant increased complexity of average network environments. This challenges current management systems. In addition to the general increase in complexity the trend among network owners and operators of merging several single service networks into larger, heterogeneous and complex full service networks challenges current management systems even further. The full service networks will require management systems more powerful than what is possible to realize basing systems purely on todays management standards. This thesis presents a distributed stochastic optimization algorithm which enables implementations of highly robust and efficient management tools. These tools may be integrated into management systems and potentially make the systems more powerful and better prepared for management of full service networks. Emergent behavior is common in nature and easily observable in colonies of social insects and animals. Even an old oak tree can be viewed as an emergent system with its collection of interacting cells. Characteristic for any emergent system is how the overall behavior of the system emerge from many relatively simple, restricted behaviors interacting, e.g. a thousand ants building a trail, a flock of birds flying south or millions of cells making a tree grow. No centralized control exist, i.e. no single unit is in charge making global decisions. Despite distributed control, high work redundancy and stochastic behavior components, emergent systems tend to be very efficient problem solvers. In fact emergent systems tend to be both efficient, adaptive and robust which are three properties indeed desirable for a network management system. The algorithm presented in this thesis relates to a class of emergent behavior based systems known as swarm intelligence systems, i.e. the algorithm is potentially efficient, adaptive and robust. On the contrary to other related swarm intelligence algorithms, the algorithm presented has a thorough formal foundation. This enables a better understanding of the algorithm’s potentials and limitations, and hence enables better adaptation of the algorithm to new problem areas without loss of efficiency, adaptability or robustness. The formal foundations are based on work by Reuven Rubinstein on cross entropy driven optimization. The transition from Ruinstein’s centralized and synchronous algorithm to a distributed and asynchronous algorithm is described, and the distributed algorithm’s ability to solve complex problems (NP-complete) efficiently is demonstrated. Four examples of how the distributed algorithm may be applied in a network management context are presented. A system for finding near optimal patterns of primary/backup paths together with a system for finding cyclic protection paths in mesh networks demonstrate the algorithm’s ability to act as a tool helping management system to ensure quality of service. The algorithm’s potential as a management policy implementation mechanism is also demonstrated. The algorithm’s adaptability is shown to enable resolution of policy conflicts in a soft manner causing as little loss as possible. Finally, the algorithm’s ability to find near optimal paths (i.e. sequences) of resources in networks of large scale is demonstrated.

Dans cette thèse, nous apportons la contribution à la conception de robots médicaux, en proposant une démarche de conception simultanée de la structure mécanique du robot. Par opposition à une vision séquentielle naturelle de la conception, la formalisation du processus créatif permet une simultanéité, ouvrant la voie à des structures innovantes dédiées : en robotique médicale, faible masse et faible compacité de la structure mécanique sont souvent recherchées. A partir d’un descriptif de démarches existantes, nous effectuons la conception d’un robot de télé-échographie et d’un robot de chirurgie mini-invasive. Pour les deux applications, de fortes contraintes sont présentes. En télé-échographie, la portabilité est très recherchée, requérant une faible compacité. Pour la chirurgie mini-invasive, les moto-réducteurs du robot in vivo doivent être dimensionnés au plus juste. Ici, nous avons formalisé l’amélioration de la compacité d’une structure parallèle pour la télé-échographie. Les résultats montrent une amélioration de la compacité de l’ordre de 5%. Dans le même esprit, nous avons formalisé la synthèse dimensionnelle de deux robots 2R-R-R de chirurgie mini-invasive in vivo. Nous réalisons l’optimisation simultanée entre le dimensionnement des moto-réducteurs et des longueurs des corps pour tendre vers une simultanéité totale du processus créatif, ce qui nous permet d’améliorer les performances en termes de force et vitesse à l’effecteur. Ces expériences de conception montrent les limites à une simultanéité stricte. Nous indiquons le besoin d’adapter outils et méthodes de conception mécatronique pour une simultanéité en conception robotique tenant compte de l’aspect imparfait du processus créatif. / In this thesis, we propose a contribution to the design of medical robots, by offering a concurrent design or simultaneous approach. As opposed to a natural sequential view of the design process, the formalization of the creative process allows simultaneity, paving the way for innovative structures, dedicated: in the medical robotic field, low mass and low compactness of the mechanical structure are often sought. From a description of existing approaches, we design a tele-ultrasound robot and a minimally invasive surgery robot. For both applications, high physical integration is required. For tele-ultrasound robots, portability is highly sought, requiring low compactness. For minimally invasive surgery, geared motors of the in vivo robot must be sized correctly. Here, we formalized the improvement of compactness of an existing parallel structure for remote ultrasound application. The results show an improvement of compactness of around 5%. In the same way, we formalize the dimensional synthesis of two robots 2R-R-R for in vivo minimally invasive surgery. The results show the under-sizing of some actuators. We perform simultaneous optimization between the design of geared motors and lengths of the body of a robot 2R-RR, tendering towards full simultaneity of the creative process, allowing to improve minimal force and velocity at the end-effector of the robot. These experiments of design show limits to a strict simultaneity. We indicate the need to adapt the tools and methods of mechatronic design for simultaneous robotics design, taking into account the imperfect aspect of the creative process.