discrete parts manufacturing industries. We are motivated by the production environment of Roketsan Missiles Industries Incorporation, operating at Turkish defense industry. Our objective is to minimize the total weighted completion times of the jobs in the system. We formulate the problem as a mixed integer linear program and find that our model could find optimal solutions only to small sized problem instances. For medium and large sized problem instances, we develop heuristic algorithms with high quality approximate solutions in reasonable solution time. Our proposed heuristic algorithm has hierarchical approach and benefits from optimization models and priority rules. We improve the heuristic method via best move with non-blocking strategy and design several experiments to test the performances. Our computational results have revealed that proposed heuristic algorithm can find high quality solutions to large sized instances very quickly.

Bien que la gestion des ressources humaines soit une problématique bien étudiée, elle reste d’actualité encore aujourd’hui, notamment en raison de la grande diversité des contextes applicatifs. De plus, les outils d’aide à la décision adressant ces problèmes peuvent encore être améliorés. Dans cette thèse, nous nous intéressons au contexte particulier où les activités des employés correspondent à des tâches fixées dans le temps, requérant des compétences précises et ne pouvant être préemptées. Nous étudions tout d’abord un problème issu de l’industrie pharmaceutique où il s’agit non seulement de trouver une affectation équitable des tâches, mais également de construire les horaires de travail du personnel de manière à respecter les contraintes légales et organisationnelles. Pour résoudre ce problème, nous proposons et comparons deux méthodes exactes, l’une fondée sur un modèle PLNE, l’autre sur un modèle PPC, ainsi que deux méta-heuristiques, l’une reposant sur une décomposition du problème, l’autre reposant sur une recherche par voisinages larges. Nous discutons ensuite de l’intégration de la meilleure de ces méthodes au sein d’un outil d’aide à la décision. Nous nous intéressons ensuite à un problème d’affectation de tâches fixées visant à minimiser le nombre d’employés requis. Pour résoudre ce problème, nous proposons une approche PPC tirant parti de la structure du problème. Nous montrons que cette approche permet d’obtenir rapidement de bonnes bornes, permettant ainsi de prouver l’optimalité sur les instances de la littérature dans un temps raisonnable. / Although workforce scheduling has been studied for decades, it remains highly relevant. In particular, applications and contexts are numerous, and they are always changing. Moreover, decision-support tools dedicated to workforce scheduling could still be improved. In this thesis, we focus on the particular context where workers are assigned to fixed tasks which cannot be preempted and require specific skills. First, we study a problem arising in a company specialized in drug evaluation where fixed tasks have to be assigned in a fair way to qualified employees so that the resulting individual shifts and plannings respect legal and organizational constraints. To handle this problem, we design and compare two exact methods, one based on a MIP model, the other on a CP approach, but also two meta-heuristics, one based on a decomposition strategy, and the other on a large neighborhood search. The best method is integrated within a decision support system. Second, we study a fixed tasks assignment problem, where the objective is to minimize the number of resources required to perform all the tasks. To tackle this problem, we suggest a constraint based approach which takes advantage of the structure of the problem. This approach enables to compute good bounds quickly, and thus, it proves optimality over state-of-the-art instances within a reasonable time limit.

Orientador: Edilaine Martins Soler / Resumo: Neste trabalho, o problema de Fluxo de Potência Ótimo Reativo problema é modelado como um problema de Programação Não Linear Inteira Mista que tem como objetivo minimizar as perdas de potência ativa nas linhas de transmissão de energia elétrica e satisfazer as restrições físicas e operacionais do Sistema Elétrico de Potência. Afim de solucionar o problema, propõem-se três abordagens heurísticas de solução, denominadas de heurística de factibilidade, heurística de melhoria de solução e gap de integralidade como restrição de igualdade. As duas primeiras abordagens são baseadas na minimização do gap de integralidade das variáveis discretas. A heurística de factibilidade objetiva encontrar uma solução factível para o problema por meio de uma busca local. Já a heurística de melhoria de solução objetiva encontrar soluções factíveis melhores a cada iteração até que não seja mais possível, por meio de uma restrição de corte de nível da função objetivo. A terceira abordagem considera a função gap de integralidade como uma restrição do problema de Fluxo de Potência Ótimo Reativo contínuo. Em todas as abordagens, o problema de Fluxo de Potência Ótimo Reativo original é transformado em um problema contínuo resolvido pelo método de pontos interiores com filtro disponibilizado no solver Interior Point OPTimizer em interface com o software General Algebraic Modeling System. Testes numéricos com os sistemas elétricos IEEE 14, 30, 118 e 300 barras e PEGASE 1354 barras são realizados para comp... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: In this work, the Reactive Optimal Power Flow problem is modeled as a Mixed-IntegerNon-Linear Programming problem and aims to minimize the active power losses throughoutthe transmission system, while satisfying the physical and technical constraints of thePower System. In order to solve the problem, three heuristics approaches are proposed,namely feasibility and solution improvement heuristics. The first and the second proposedheuristics are based on the minimization of the integrality gap of the discrete variables. Thefeasibility heuristic aims to find a feasible solution to the problem through a local search.The solution improvement heuristic aims to find better feasible solution iteratively until itis no longer possible, by adding level cuts in the objective function. The third approachconsiders the proposed integrality gap function as a new constraint of the continuousReactive Optimal Power Flow problem. In both approaches, the original Reactive OptimalPower Flow problem is modeled as a continuous problem and solved by the interior pointmethod with filter implemented in the Interior Point OPTimizer solver under the GeneralAlgebraic Modeling System interface. Numerical tests with the IEEE 14-, 30-, 118 and300-bus and the PEGASE 1354-bus electrical power systems are performed to show theefficiency of the proposed approaches. The numerical results indicate that the proposedapproaches showed to be competitive when compared to exact methods published in theliterature. / Doutor