Les problèmes de tournées de véhicules cumulatives avec capacité (CCVRP) sont étudiés dans cette thèse, où la minimisation de la somme des temps d'arrivée reflète mieux les objectifs stratégiques de la logistique humanitaire.Dans le problème de multiples tournées d’un véhicule cumulatif avec capacité (mt-CCSVRP), un seul véhicule est disponible et il peut effectuer plusieurs voyages. Un algorithme du plus court chemin avec contrainte de ressources est proposé pour résoudre ce problème, dans lequel les tournées deviennent des nœuds et les sites sont des ressources. Le réseau est orienté et acyclique en raison des propriétés particulières du mt-CCSVRP.Le problème de multiples tournées de véhicules cumulatives avec capacité (mt-CCVRP) est introduit, où plusieurs véhicules peuvent effectuer multiples voyages. Quatre programmes linéaires en nombre entiers (PLNE) sont proposés pour résoudre le CCVRP. Un PLNE pour le mt-CCVRP est proposé ainsi que trois métaheuristiques : une recherche locale itéré à démarrages multiples (MS-ILS), un algorithme mémétique avec gestion de la population (MA|PM) et une recherche locale évolutive à démarrages multiples (MS-ELS), qui appellent un algorithme de recherche local à voisinages variables (VND). Une méthode split à deux phases permet MA|PM et MS-ELS d'alterner entre deux espaces de solutions.Le problème de tournées de véhicules cumulatif avec capacité et des livraisons indirectes (CCVRP-ID) permet aux sites non visités si leurs demandes sont fournies par un véhicule auxiliaire. Un PLNE et un MS-ELS sont développés / The cumulative capacitated vehicle routing problems (CCVRP) are studied in this thesis, where the minimization of the sum of arrival times better reflects the strategic objectives of humanitarian logistics.In the multitrip cumulative capacitated single-vehicle routing problem (mt-CCSVRP), only one vehicle is available and it can perform multiple trips. An exact resource constrained shortest path algorithm is proposed for this problem, in which trips become nodes and sites are resources. The resulting network is proven to be directed and acyclic due to the special properties of the mt-CCSVRP.The multitrip cumulative capacitated vehicle routing problem (mt-CCVRP) is introduced, where several vehicles can do multiple trips. Four mixed integer linear programs (MILP) are proposed to solve the CCVRP. For the mt-CCVRP a MILP is also given as well as three metaheuristics: a multi-start iterated local search (MS-ILS), a memetic algorithm with population management (MA|PM) and a multi-start evolutionary local search (MS-ELS), which call a variable neighborhood descent algorithm (VND). A two phases split method allows MA|MS and MS-ELS to alternate between two spaces of solutions.The cumulative capacitated vehicle routing problem with indirect deliveries (CCVRP-ID) allows unvisited sites if their demands are provided by an auxiliary vehicle. An MILP and an MS-ELS are developed

Cette thèse aborde le problème de tournées de véhicules (VRP) adressant des incertitudes via l'optimisation robuste, en donnant le VRP Robuste (RVRP). D'abord, les incertitudes sont intégrées sur les temps de trajet. Ensuite, une version bi-objectif du RVRP (bi-RVRP) est considérée en prenant en compte les incertitudes sur les temps de trajet et les demandes. Pour résoudre le RVRP et le bi-RVRP, différentes méthodes sont proposées pour déterminer des solutions robustes en minimisant le pire cas. Un Programme Linéaire à Variables Mixtes Entières (MILP), six heuristiques constructives, un algorithme génétique (GA), une procédure de recherche locale et quatre stratégies itératives à démarrage multiple sont proposées : une procédure de recherche constructive adaptive randomisée (GRASP), une recherche locale itérée (ILS), une ILS à démarrage multiple (MS-ILS), et une MS-ILS basée sur des tours géants (MS-ILS-GT) convertis en tournées réalisables grâce à un découpage lexicographique. Concernant le bi-RVRP, le coût total des arcs traversés et la demande totale non satisfaite sont minimisés sur tous les scénarios. Pour résoudre le problème, différentes versions de métaheuristiques évolutives multi-objectif sont proposées et couplées à une recherche locale : l'algorithme évolutionnaire multi-objectif (MOEA) et l'algorithme génétique avec tri par non-domination version 2 (NSGAII). Différentes métriques sont utilisées pour mesurer l’efficience, la convergence, ainsi que la diversité des solutions pour tous ces algorithmes / This work extends the Vehicle Routing Problem (VRP) for addressing uncertainties via robust optimization, giving the Robust VRP (RVRP). First, uncertainties are handled on travel times/costs. Then, a bi-objective version (bi-RVRP) is introduced to handle uncertainty in both, travel times and demands. For solving the RVRP and the bi-RVRP different models and methods are proposed to determine robust solutions minimizing the worst case. A Mixed Integer Linear Program (MILP), several greedy heuristics, a Genetic Algorithm (GA), a local search procedure and four local search based algorithms are proposed: a Greedy Randomized Adaptive Search Procedure (GRASP), an Iterated Local Search (ILS), a Multi-Start ILS (MS-ILS), and a MS-ILS based on Giant Tours (MS-ILS-GT) converted into feasible routes via a lexicographic splitting procedure. Concerning the bi-RVRP, the total cost of traversed arcs and the total unmet demand are minimized over all scenarios. To solve the problem, different variations of multiobjective evolutionary metaheuristics are proposed and coupled with a local search procedure: the Multiobjective Evolutionary Algorithm (MOEA) and the Non-dominated Sorting Genetic Algorithm version 2 (NSGAII). Different metrics are used to measure the efficiency, the convergence as well as the diversity of solutions for all these algorithms

Le chargement/déchargement des conteneurs et leurs stockages provisoires dans le port est la plus importante et complexe tâche dans les terminaux portuaires. Elle est fortement liée au routage des grues de quai et son coût augmente considérablement surtout en absence d’une gestion efficace du terminal. Dans ce travail, nous étudions le problème de stockage des conteneurs (PSC). Il appartient à la catégorie des problèmes NP-difficiles et NP-complets. PSC consiste à déterminer un plan d’arrangement des conteneurs destinés à l’import et à l’export dans le port qui minimise les remaniements ultérieurs lors de leur transfert vers le bateau, camion ou train. En effet, le temps d'attente des camions des clients, le temps de transfert des grues de quai et le temps nécessaire au chargement/déchargement du navire sont avantageusement réduits. PSC est généralement étudié en considérant un seul type de conteneur. Cependant, plusieurs types de conteneurs sont utilisés dans les ports maritimes (dry, réfrigérés, toit ouvert,...). En outre, le problème de stockage de conteneurs peut être traité de façon statique ou dynamique (date d’arrivée et de départ des conteneurs incertains).L’objectif de cette thèse est de résoudre le PSC statique et le PSC dynamique pour un seul et plusieurs types de conteneurs en utilisant deux métaheuristiques : l’algorithme génétique, la recherche harmoniquePour vérifier la performance de chacune des approches proposées, une étude comparative des résultats générés par chaque méthode ainsi que celle de l’algorithme LIFO est établie / The loading and unloading of containers and their temporary storage in the container terminal are the most important and complex operation in seaport terminals. It is highly inter-related with the routing of yard crane and truck and their costs increased significantly especially without an efficient terminal management. To improve this process, an efficiency decision for the container storage space allocation must be taken.In this thesis, we studied the container storage problem (CSP). It falls into the category of NP hard and NP complete problems. CSP consists on finding the most suitable storage location for incoming containers that minimizes rehandling operations of containers during their transfer to the ship, truck or train. In fact, the wait time of customer trucks, the transfer time of yard crane and the Ship turnaround time are advantageously reduced.Generally, this problem is studied considering a single container type. However, this does not stand the problem under its real-life statement as there are multiple container types that should be considered, (refrigerated, open side, empty, dry, open top and tank). Often, containers arrive at the port dynamically over time and have an uncertain departure date (ship delayed, a ship down, delayed arrival of customer trucks…). Indeed, CSP must be studied in dynamic aspectThe objective of this thesis is to study Static CSP for a single and various container type and dynamic CSP for ONE and several container types and to propose solutions for each of them. Genetic algorithm and Harmony Search algorithm are used to solve these problems and we compare the results of each approach with the LIFO algorithm

Avec plus de 345 millions de tonnes de déchets produits en France en 2012, la performance de la chaîne logistique de collecte, transport et traitement de ces produits et matériaux est devenue un enjeu économique et écologique majeur dans notre société. Dans cette thèse, nous nous intéressons à l’optimisation de la chaîne de collecte et transport des déchets sur le plan tactique et opérationnel. Nous modélisons dans un premier temps un nouveau problème tactique d’optimisation de flux de déchets avec sites de transfert et de traitement sur un horizon mono-périodique puis multi-périodique, afin d’exploiter un réseau logistique existant de manière optimale. Nous résolvons différentes variantes de ce problème linéaire mixte à l’aide d’un solveur. Nous étudions dans un second temps la planification opérationnelle de la collecte de conteneurs d’apport volontaire et des tournées de véhicules associées en résolvant un problème riche de tournées avec gestion de stocks et plateformes de vidage intermédiaires. Nous proposons un modèle d’optimisation de ce nouveau problème et le résolvons par un algorithme à voisinages larges (ALNS) dans un cadre déterministe puis stochastique, dans lequel le remplissage des conteneurs est aléatoire et plus conforme à la réalité. Nous obtenons des résultats compétitifs en évaluant notre approche sur des instances de la littérature proches de notre problème riche. En réalisant un logiciel d’optimisation à destination d’une entreprise de collecte et transport de déchets, nous améliorons également de manière significative les tournées de véhicules en application réelle. / With more than 345 million tons produced in France in2012, waste supply chain management is an important economical and ecological issue for our society. In this thesis, we focus on optimizing waste supply chain on both the tactical and operational decision levels. In order to optimize an existing waste logistic network in medium term, we first solve a multimodal flow problem where products are transferred and transformed in sites of various size, in a mono-periodic then multi-periodic horizon. At an operational level, we study the planning and routing of vehicles used for voluntary drop-off waste container collection by solving a complex inventory routing problem with intermediate facilities. We use a large neighborhoods search metaheuristic to solve both the deterministic and stochastic approaches, where waste supply quantity is also subject to uncertainty. We obtain competitive results on instances coming from the literature on classical routing problems close to our rich case. We also develop an optimization software used by a French waste management company and significantly improve routes in a real application.

Les travaux présentés dans cette thèse visent à proposer des méthodes permettant de résoudre un problème de Transport à la Demande multicritère. Le premier travail réalisé dans cette thèse est l'étude d'un problème de Dial-a-Ride (DARP) statique multicritère. Trois critères qui peuvent être conflictuels ont été définis : le premier consiste à minimiser le coût de transport, le deuxième critère consiste à minimiser l'insatisfaction des passagers et enfin le troisième critère consiste à minimiser la quantité de CO2 émise par l'ensemble des véhicules. Nous avons développé une méthode évolutionnaire NSGA-II pour chercher un ensemble approximatif d'optimas de Pareto. Le second travail réalisé est l'étude d'un problème d'Optimal Timing dans une tournée. Ce problème consiste à calculer les dates de début de service optimales des points d'arrêts d'une tournée afin de minimiser l'insatisfaction des passagers. Le dernier travail de cette thèse a porté sur l'étude d'un problème de Transport à la Demande dynamique dans lequel de nouvelles requêtes à traiter arrivent en cours de journée. Deux méthodes ont été proposées pour résoudre ce problème : la première est une heuristique d'insertion rapide et la seconde est une méthode arborescente tronquée connue sous le nom de Recovering Beam Search. / The work presented in this thesis aims to propose methods to solve a multicriteria dial-a-ride problem (DARP). Three objective functions that have to be optimized in order to measure the potential efficiency of the DARP solution on different aspects : the cost for the transportation operator, the quality of service for users and the impact on the environment. The first work in this thesis is the study of static DARP for which a NSGA-II algorithm is developped to identify a good approximation of the Pareto optimal set. The second work deals with an optimal timing algorithm which computes pickup and delivery dates when the requests are sequenced on the vehicles, the objective is to minimize the total customer' dissatisfaction. The last problem studied in this thesis aims to solve the dynamic version of DARP for which two methods are proposed. The first one is a fast insertion heuristic based on an attractive index. However, the second methode uses a recovering beam search heuristic which unlike the insertion heuristic allows to modify the structure of the routes previously scheduled in order to schedule the new requests.

Submitted by Lara Oliveira (lara@ufersa.edu.br) on 2018-03-15T21:26:01Z No. of bitstreams: 1 JonathanLS_DISSERT.pdf: 6143092 bytes, checksum: 68ad13bf204320bdcea5907ddb8d2102 (MD5) / Approved for entry into archive by Vanessa Christiane (referencia@ufersa.edu.br) on 2018-06-18T16:59:44Z (GMT) No. of bitstreams: 1 JonathanLS_DISSERT.pdf: 6143092 bytes, checksum: 68ad13bf204320bdcea5907ddb8d2102 (MD5) / Approved for entry into archive by Vanessa Christiane (referencia@ufersa.edu.br) on 2018-06-18T16:59:51Z (GMT) No. of bitstreams: 1 JonathanLS_DISSERT.pdf: 6143092 bytes, checksum: 68ad13bf204320bdcea5907ddb8d2102 (MD5) / Made available in DSpace on 2018-06-18T16:59:58Z (GMT). No. of bitstreams: 1 JonathanLS_DISSERT.pdf: 6143092 bytes, checksum: 68ad13bf204320bdcea5907ddb8d2102 (MD5) Previous issue date: 2017-08-23 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / 2018-03-15 / Os problemas de corte de materiais são recorrentes no cotidiano da indústria, sendo encontrados nas mais diferentes formas.Oproblema de corte bidimensional guilhotinado é uma dessas formas. Ele surge pelas restrições da ferramenta de corte, tipicamente a guilhotina. Este trabalho apresenta três abordagens para solucionar o problema em questão: uma abordagem matemática, uma abordagem exata computacional e uma abordagem heurística. A abordagem matemática consiste em um modelo de programação linear baseado em listas de itens e montagem do arranjo de corte partindo dos itens, unindo-os dois a dois, tentando maximizar o número de uniões sem ultrapassar as dimensões da placa. A abordagem exata computacional tratá-se de um algoritmo Branch-and-Bound modificado para permitir que estados mais promissores possam ser analisados antes, comportando-se como um algoritmo de busca em profundidade com uma pequena etapa em largura, na qual ordena os filhos na árvore de decisão pelo desperdício gerado. Por fim, a abordagem heurística é composta das metaheurísticas GRASP, Busca Tabu, Algoritmo Genético, BRKGA e Religação de Caminhos combinados com uma heurística de montagem baseada nos algoritmos propostos por Nascimento, Longo e Aloise (1999). Essas metaheurísticas foram combinadas em um time assíncrono para alcançar melhores resultados que os já encontrados na literatura. Além de melhorar os resultados conhecidos, a pesquisa também tinha como objetivo apresentar um modelo viável, em número de variáveis, e resultados ótimos para instâncias comumente utilizadas para o problema supracitado e novas opções de obtê-los em instâncias que venham a surgir no futuro. Testes mostraram a competividade dos algoritmos propostos frente aos melhores resultados encontrados, reduzindo inclusive o número total de placas, bem como a capacidade dos métodos exatos propostos de encontrar as soluções ótimas para as instâncias testadas. Cerca de de 25% dos resultados ótimos foram encontrados, passando esse número para 75%, quando considerados os resultados dos algoritmos metaheurísticos que atingiram o limite inferior das instâncias

Cette thèse s'intéresse au problème de conception optimale des routes de départ et d'arrivée dans une zone terminale autour d'un aéroport. Cette conception prend en compte la configuration et l'environnement autour des aéroports, et les différentes contraintes sous-jacentes, notamment l'évitement des obstacles et la séparation des routes. Nous proposons une formulation mathématique conduisant à un problème d'optimisation combinatoire, ainsi que des méthodes de résolution ad hoc efficaces pour le problème. Pour la résolution du problème, nous procédons en deux étapes. Nous considérons d'abord la conception d'une route de longueur minimale évitant les obstacles, en utilisant la méthode de Branch and Bound (B&B). Ensuite, nous nous intéressons à la conception de plusieurs routes en assurant en plus la séparation des routes. Deux approches différentes sont appliquées : une méthode basée sur la méthode B&B pour construire les routes séquentiellement suivant un ordre fixé à l'avance, et une méthode de recuit simulé pour construire les routes simultanément. Les résultats sur un ensemble de problèmes tests (artificiels et réels) montrent l'efficacité de notre approche. / This thesis proposes a methodology for the optimization of departure and arrival routes in the Terminal Maneuvering Area (TMA). The design of these routes takes into account the configuration and environment around airports, and the related constraints, in particular the avoidance of obstacles and the separation between routes. We propose a mathematical formulation leading to a combinatorial optimization problem, as well as efficient ad hoc resolution methods for the problem. The problem is solved in two steps. First, we design an individual route avoiding obstacles with respect to minimum route length by using a Branch and Bound (B&B) method. Afterwards, the design of multiple routes is solved by two different approaches: a B&B-based approach (where routes are generated sequentially in a given order) and a Simulated Annealing approach (where routes are generated simultaneously). The simulation results of a set of (artificial and real) test problems show the efficiency of our approach.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The generalized minimum spanning tree problem is present in several situations of the real world, such as in the context of the telecommunications, transports and grouping of data, where a net of necessary clusters to be connected using a node of each cluster. In that work it is presented the project and the implementation of an algorithm of tabu search with path relinking and iterated local search for the generalized minimum spanning tree problem and your variant with at least one vertex by group. In the computational tests 271 instances of TSPLIB were used generated through the grouping methods Center Clustering and Grid Clustering, and more 20 instances for the extension of the problem with at least one vertex by group. The results demonstrate the efficiency of the algorithm proposed in the obtaining of satisfactory solutions for the two problems. / O problema da árvore geradora mínima generalizado está presente em várias situações do mundo real, tais como no contexto das telecomunicações, transportes e agrupamento de dados, nas quais uma rede de grupos precisa ser conectada utilizando um nodo de cada grupo. Nesse trabalho é apresentado o projeto e a implementação de um algoritmo de busca tabu com reconexão de caminhos e busca local iterativa para o problema da árvore geradora mínima generalizado e sua variante com pelo menos um vértice por grupo. Nos testes computacionais foram utilizadas 271 instâncias da TSPLIB geradas através dos métodos de agrupamento Center Clustering e Grid Clustering, e mais 20 instâncias para a extensão do problema com pelo menos um vértice por grupo. Os resultados demonstram a eficiência do algoritmo proposto na obtenção de soluções satisfatórias para os dois problemas.

Submitted by Fernando Souza (fernandoafsou@gmail.com) on 2017-08-15T11:46:12Z No. of bitstreams: 1 arquivototal.pdf: 884446 bytes, checksum: 92314027dddef8365b4a2e655b65bd78 (MD5) / Made available in DSpace on 2017-08-15T11:46:13Z (GMT). No. of bitstreams: 1 arquivototal.pdf: 884446 bytes, checksum: 92314027dddef8365b4a2e655b65bd78 (MD5) Previous issue date: 2016-05-20 / The Static Bike Rebalancing Problem (SBRP) is a recent problem motivated by the task of repositioning bikes among stations in a self-service bike-sharing systems. This problem can be seen as a variant of the one-commodity pickup and delivery vehicle routing problem, where multiple visits are allowed to be performed at each station, i.e., the demand of a station is allowed to be split. Moreover, a vehicle may temporarily drop its load at a station, leaving it in excess or, alternatively, collect more bikes (even all of them) from a station, thus leaving it in default. Both cases require further visits in order to meet the actual demands of such station. This work deals with a particular case of the SBRP, in which only a single vehicle is available and the objective is to nd a least-cost route that meets the demand of all stations and does not violate the minimum (zero) and maximum (vehicle capacity) load limits along the tour. Therefore, the number of bikes to be collected or delivered at each station should be appropriately determined in order to respect such constraints. This is a NP-Hard problem since it contains other NP-Hard problems as special cases, hence, using exact methods to solve it is intractable for larger instances. Several methods have been proposed by other authors, providing optimal values for small to medium sized instances, however, no work has consistently solved instances with more than 60 stations. The proposed algorithm to solve the problem is an iterated local search (ILS) based heuristic combined with a randomized variable neighborhood descent (RVND) as local search procedure. The algorithm was tested on 980 benchmark instances from the literature and the results obtained are quite competitive when compared to other existing methods. Moreover, the method was capable of nding most of the known optimal solutions and also of improving the results on a number of open instances. / O Problema do Rebalanceamento Est atico de Bicicletas (Static Bike Rebalancing Problem, SBRP) e um recente problema motivado pela tarefa de reposicionar bicicletas entre esta c~oes em um sistema self-service de compartilhamento de bicicletas. Este problema pode ser visto como uma variante do problema de roteamento de ve culos com coleta e entrega de um unico tipo de produto, onde realizar m ultiplas visitas a cada esta c~ao e permitido, isto e, a demanda da esta c~ao pode ser fracionada. Al em disso, um ve culo pode descarregar sua carga temporariamente em uma esta c~ao, deixando-a em excesso, ou, de maneira an aloga, coletar mais bicicletas (at e mesmo todas elas) de uma esta c~ao, deixando-a em falta. Em ambos os casos s~ao necess arias visitas adicionais para satisfazer as demandas reais de cada esta c~ao. Este trabalho lida com um caso particular do SBRP, em que apenas um ve culo est a dispon vel e o objetivo e encontrar uma rota de custo m nimo que satisfa ca as demandas de todas as esta c~oes e n~ao viole os limites de carga m nimo (zero) e m aximo (capacidade do ve culo) durante a rota. Portanto, o n umero de bicicletas a serem coletadas ou entregues em cada esta c~ao deve ser determinado apropriadamente a respeitar tais restri c~oes. Trata-se de um problema NP-Dif cil uma vez que cont em outros problemas NP-Dif cil como casos particulares, logo, o uso de m etodos exatos para resolv^e-lo e intrat avel para inst^ancias maiores. Diversos m etodos foram propostos por outros autores, fornecendo valores otimos para inst^ancias pequenas e m edias, no entanto, nenhum trabalho resolveu de maneira consistente inst^ancias com mais de 60 esta c~oes. O algoritmo proposto para resolver o problema e baseado na metaheur stica Iterated Local Search (ILS) combinada com o procedimento de busca local variable neighborhood descent com ordena c~ao aleat oria (randomized variable neighborhood descent, RVND). O algoritmo foi testado em 980 inst^ancias de refer^encia na literatura e os resultados obtidos s~ao bastante competitivos quando comparados com outros m etodos existentes. Al em disso, o m etodo foi capaz de encontrar a maioria das solu c~oes otimas conhecidas e tamb em melhorar os resultados de inst^ancias abertas.

Made available in DSpace on 2014-12-17T14:55:11Z (GMT). No. of bitstreams: 1 JoaoPQS.pdf: 1464588 bytes, checksum: ad1e7b6af306b0ce9b1ccb1fb510c4ab (MD5) Previous issue date: 2009-03-06 / The metaheuristics techiniques are known to solve optimization problems classified as NP-complete and are successful in obtaining good quality solutions. They use non-deterministic approaches to generate solutions that are close to the optimal, without the guarantee of finding the global optimum. Motivated by the difficulties in the resolution of these problems, this work proposes the development of parallel hybrid methods using the reinforcement learning, the metaheuristics GRASP and Genetic Algorithms. With the use of these techniques, we aim to contribute to improved efficiency in obtaining efficient solutions. In this case, instead of using the Q-learning algorithm by reinforcement learning, just as a technique for generating the initial solutions of metaheuristics, we use it in a cooperative and competitive approach with the Genetic Algorithm and GRASP, in an parallel implementation. In this context, was possible to verify that the implementations in this study showed satisfactory results, in both strategies, that is, in cooperation and competition between them and the cooperation and competition between groups. In some instances were found the global optimum, in others theses implementations reach close to it. In this sense was an analyze of the performance for this proposed approach was done and it shows a good performance on the requeriments that prove the efficiency and speedup (gain in speed with the parallel processing) of the implementations performed / As metaheur?sticas s?o t?cnicas conhecidas para a resolu??o de problemas de otimiza??o, classificados como NP-Completos e v?m obtendo sucesso em solu??es aproximadas de boa qualidade. Elas fazem uso de abordagens n?o determin?sticas que geram solu??es que se aproximam do ?timo, mas no entanto, sem a garantia de que se encontre o ?timo global. Motivado pelas dificuldades em torno da resolu??o destes problemas, este trabalho prop?s o desenvolvimento de m?todos paralelos h?bridos utilizando a aprendizagem por refor?o e as metaheur?sticas GRASP e Algoritmos Gen?ticos. Com a utiliza??o dessas t?cnicas em conjunto, objetivou-se ent?o, contribuir na obten??o de solu??es mais eficientes. Neste caso, ao inv?s de utilizar o algoritmo Q-learning da aprendizagem por refor?o, apenas como t?cnica de gera??o das solu??es iniciais das metaheur?sticas, este tamb?m aplicado de forma cooperativa e competitiva com o Algoritmo Gen?tico e o GRASP, em uma implementa??o paralela. Neste contexto, foi poss?vel verificar que as implementa??es realizadas neste trabalho apresentaram resultados satisfat?rios, tanto na parte de coopera??o e competi??o entre os algoritmos Q-learning, GRASP a Algoritmos Gen?ticos, quanto na parte de coopera??o e competi??o entre grupos destes tr?s algoritmos. Em algumas inst?ncias foi encontrado o ?timo global; quando n?o encontrado, conseguiu-se chegar bem pr?ximo de seu valor. Neste sentido foi realizada uma an?lise do desempenho da abordagem proposta e verificou-se um bom comportamento em rela??o aos quesitos que comprovam a efici?ncia e o speedup (ganho de velocidade com o processamento paralelo) das implementa??es realizadas