O sequenciamento e a programação da produção trazem grandes benefícios financeiros às empresas se realizados de forma adequada. Atualmente, soluções generalizadas apresentam resultados aceitáveis, porém têm como consequência benefícios inferiores quando comparados a estudos específicos. O ramo da otimização de resultados possui dois tipos de soluções: as exatas para problemas de menores dimensões e não exatas, ou heurísticas, para problemas de médias e grandes dimensões. Este trabalho apresenta algoritmos exatos do tipo Branch & Bound e Modelos de Programação Linear Inteira Mista para solucionar quatro variações de problemas de scheduling: Fm|block|∑Cjm, Fm|block|∑Tj, Fm|block, Sijk|∑Cjm e Fm|block, Sijk|∑Tj. As abordagens utilizadas são inéditas na literatura e apresentaram resultados animadores para a maioria dos cenários. O limitante para o tempo total de fluxo obteve resposta ótima em 100% dos casos para problemas de até 20 tarefas e 4 máquinas em menos de uma hora. Para o tempo total de atraso, o limitante se mostrou mais eficiente quando os valores das due dates apresentam alta taxa de dispersão. Para os casos com setup, foram elaboradas três variações de limitantes para cada problema. O limitante com setup que apresentou o melhor desempenho foi o que obteve a melhor relação entre o seu valor numérico e seu custo computacional. Os modelos MILP solucionaram 100% dos problemas sem setup para até 20 tarefas e 4 máquinas e para os casos com setup, foram solucionados problemas de até 14 tarefas e 4 máquinas no tempo limite de uma hora. Os testes computacionais mostram a eficiência na redução do número de nós e, consequentemente, no tempo de execução. Portanto, o estudo realizado indica que, para problemas de pequeno porte e médio, os métodos em questão possuem grande potencial para aplicações práticas. / Job Sequence and Programming give benefits both financial and organizational to any company when performed properly. Nowadays, there is still a gap between theory and practice due to solutions that are short in specification. The analyzed problems differ in type and dimension thus modifying its complexity. The results optimization field is divided into two types of solution: the exact solution for minor problems and the non-exact solution for greater dimension problems. The present paper presents exact algorithms to solve the problems Fm|block|∑Cjm, Fm|block|∑Tj, Fm|block, Sijk|∑Cjm by the Branch & Bounds and Mixed Integer Linear Program models. The approaches are new and presented good results for most cases. Bounds for the no-setup total flow time scenario solved 100% of the 20 jobs and 4 machines cases. High dispersion range due dates contributed for the effectiveness of the no-setup total tardiness bound\'s effectiveness. Three different approaches were developed for the setup cases. The best approach aimed to optimize the value/effort factor for the B&B. The Mixed Integer Linear Program models solved 100% of the no-setup cases for 20 jobs and 4 machines. The MILPs setup cases solved optimally 14 jobs and 4 machines cases. Computational tests were executed and analyzed and they highlighted the node count reduction and, consequently, the execution time. The present study points out that the exact methods can be applied to small and medium scheduling problems in practice.

Dans ce mémoire, nous nous intéressons à l'étude et la résolution de problèmes d'ordonnancement de type flowshop de permutation, en présence de contraintes d'écarts temporels (ou time lags), définies entre les couples d'opérations consécutives au sein des travaux. De telles contraintes généralisent les contraintes de précédence classiques et peuvent modéliser de nombreuses situations réelles. De nouveaux résultats de complexité sont démontrés et viennent compléter des résultats classiques tirés de la littérature. Nous présentons aussi un état de l'art assez détaillé sur les travaux concernant les problèmes d'ordonnancement avec time lags, qui met en évidence le manque d'attention reçu par ces problèmes. Nous développons ensuite un schéma générique de résolution exacte reposant sur une Procédure par Séparation et Evaluation et nous l'utilisons pour résoudre plusieurs problèmes de flowshop de permutation en présence de time lags. L'efficacité de cette approche de résolution est évaluée grâce à des séries d'expériences numériques. Enfin, des extensions permettant de prendre en compte des contraintes supplémentaires sont proposées.

In cellular manufacturing systems, minimization of the completion time has a great impact on the production time, material flow, and productivity. An effective scheduling is crucial to attaining the advantages of cellular manufacturing systems. This dissertation attempts to solve the Flowshop Manufacturing Cell (cellular flowshop) Scheduling Problem with Sequence Dependent Setup Times (FMCSP with SDSTs) considering two performance measures: the total flow time as a mono objective, and the makespan and total flow time combined as a bi-criteria scheduling problem. The proposed problem is known to be the NP-hard problem because of its complexity. Several metaheuristic algorithms based on Genetic Algorithm (GA), Simulated Annealing (SA), and Particle Swarm Optimization (PSO) are developed for scheduling part families as well as jobs within each part family for FMCSP with SDSTs to minimize the total flow time. A local search method based on SA combined with PSO (named as PSO-SA) is proposed to enhance the intensification and improve the quality of the solution obtained by pure PSO. The effectiveness and efficiency of the proposed metaheuristics are evaluated based on the Relative Percentage Deviation (RPD) from its lower bound, and the robustness. Results indicate PSO-SA is performed similar to best available algorithms for small and medium size test problems. Yet, there is a very small deviation from best results for large problems. A Multi-objective Particle Swarm Optimization (MPSO) and a Multi-objective Simulated Annealing (MOSA) Algorithm are further proposed to solve the bi-criteria optimization problem to minimize the total flow time and makespan simultaneously. An improved PSO is combined with Threshold Acceptance (TA) algorithm to improve effectiveness of the proposed MPSO (named as IMPSO-TA) for the convergence of the obtained Pareto Front. The proposed algorithms are evaluated using several Quality Indicators (QI) measures for multiobjective optimization problems. The proposed algorithms can generate approximated Pareto Fronts in a reasonable CPU time. The proposed IMPSO-SA outperforms MOSA algorithm in terms of CPU time and minimizing the objective functions. / October 2015

Due to the current trends in business as the necessity to have a large catalogue of products, orders that increase in frequency but not in size, globalisation and a market that is increasingly competitive, the production sector faces an ever harder economical environment. All this raises the need for production scheduling with maximum efficiency and effectiveness. The first scientific publications on production scheduling appeared more than half a century ago. However, many authors have recognised a gap between the literature and the industrial problems. Most of the research concentrates on optimisation problems that are actually a very simplified version of reality. This allows for the use of sophisticated approaches and guarantees in many cases that optimal solutions are obtained. Yet, the exclusion of real-world restrictions harms the applicability of those methods. What the industry needs are systems for optimised production scheduling that adjust exactly to the conditions in the production plant and that generates good solutions in very little time. This is exactly the objective in this thesis, that is, to treat more realistic scheduling problems and to help closing the gap between the literature and practice. The considered scheduling problem is called the hybrid flowshop problem, which consists in a set of jobs that flow through a number of production stages. At each of the stages, one of the machines that belong to the stage is visited. A series of restriction is considered that include the possibility to skip stages, non-eligible machines, precedence constraints, positive and negative time lags and sequence dependent setup times. In the literature, such a large number of restrictions has not been considered simultaneously before. Briefly, in this thesis a very realistic production scheduling problem is studied. Various optimisation methods are presented for the described scheduling problem. A mixed integer programming model is proposed, in order to obtai / Urlings ., T. (2010). Heuristics and metaheuristics for heavily constrained hybrid flowshop problems [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/8439 / Palancia

The aim of this thesis is to design and evaluate an ant algorithm for a certain class of (hybrid) flowshop problems. These problems consist of a two-staged production process with two identical machines on the second station and buffers in between the stages. For a given number of jobs, each consisting of a processing time and a deadline, the goal is to create a feasible partition and permutation of these jobs which minimizes the total tardiness. Furthermore, a theoretical investigation on the placement and size of the buffers and its impact on the resulting solution space was done. In order to further improve the swarm intelligence it was combined with a set of different heuristics and pheromone evaluation rules. The resulting variations of the algorithm were later tested and evaluated on a set of benchmark instances. Subsequently, the obtained theoretical insights on the flowshop problems were analyzed in a practical matter and proved to be valuable. Finally, the quality of the solutions found by the designed ant algorithm was analyzed on smaller pro- blem instances. It became apparent that at least for such smaller problems the algorithm creates very good solutions which only differ little from the optimum.

Estimation of Distribution Algorithm (EDA) is a branch of evolutionary computation that learn a probabilistic model of good solutions. Probabilistic models are used to represent relationships between solution variables which may give useful, human-understandable insights into real-world problems. Also, developing an effective PM has been shown to significantly reduce function evaluations needed to reach good solutions. This is also useful for real-world problems because their representations are often complex needing more computation to arrive at good solutions. In particular, many real-world problems are naturally represented as permutations and have expensive evaluation functions. EDAs can, however, be computationally expensive when models are too complex. There has therefore been much recent work on developing suitable EDAs for permutation representation. EDAs can now produce state-of-the-art performance on some permutation benchmark problems. However, models are still complex and computationally expensive making them hard to apply to real-world problems. This study investigates some limitations of EDAs in solving permutation and scheduling problems. The focus of this thesis is on addressing redundancies in the Random Key representation, preserving diversity in EDA, simplifying the complexity attributed to the use of multiple local improvement procedures and transferring knowledge from solving a benchmark project scheduling problem to a similar real-world problem. In this thesis, we achieve state-of-the-art performance on the Permutation Flowshop Scheduling Problem benchmarks as well as significantly reducing both the computational effort required to build the probabilistic model and the number of function evaluations. We also achieve competitive results on project scheduling benchmarks. Methods adapted for solving a real-world project scheduling problem presents significant improvements.

Les algorithmes Branch and Bound (B&B) sont attractifs pour la résolution exacte de problèmes d'optimisation combinatoire (POC) par exploration d'un espace de recherche arborescent. Néanmoins, ces algorithmes sont très gourmands en temps de calcul pour des instances de problèmes de grande taille (exemple : benchmarks de Taillard pour FSP) même en utilisant le calcul sur grilles informatiques [Mezmaz et al., IEEE IPDPS'2007]. Le calcul massivement parallèle fourni à travers les plates-formes de calcul hétérogènes d'aujourd'hui [TOP500 ] est requis pour traiter effi cacement de telles instances. Le dé fi est alors d'exploiter tous les niveaux de parallélisme sous-jacents et donc de repenser en conséquence les modèles parallèles des algorithmes B&B. Dans cette thèse, nous nous attachons à revisiter la conception et l'implémentation des ces algorithmes pour la résolution de POC de grande taille sur (larges) plates-formes de calcul multi-coeurs et multi-GPUs. Le problème d'ordonnancement Flow-Shop (FSP) est considéré comme étude de cas. Une étude expérimentale préliminaire sur quelques grandes instances du FSP a révélé que l'arbre de recherche est hautement irrégulier (en forme et en taille) et très large (milliards de milliards de noeuds), et que l'opérateur d'évaluation des bornes est exorbitant en temps de calcul (environ 97% du temps de B&B). Par conséquent, notre première contribution est de proposer une approche GPU avec un seul coeur CPU (GB&B) dans laquelle seul l'opérateur d'évaluation est exécuté sur GPU. L'approche traite deux dé fis: la divergence de threads et l'optimisation de la gestion de la mémoire hiérarchique du GPU. Comparée à une version séquentielle, des accélérations allant jusqu'à ( 100) sont obtenues sur Nvidia Tesla C2050. L'analyse des performances de GB&B a montré que le surcoût induit par le transfert des données entre le CPU et le GPU est élevé. Par conséquent, l'objectif de la deuxième contribution est d'étendre l'approche (LL-GB&B) a fin de minimiser la latence de communication CPU-GPU. Cet objectif est réalisé grâce à une parallélisation à grain fin sur GPU des opérateurs de séparation et d'élagage. Le défi majeur relevé ici est la divergence de threads qui est due à la nature fortement irrégulière citée ci-dessus de l'arbre exploré. Comparée à une exécution séquentielle, LL-GB&B permet d'atteindre des accélérations allant jusqu'à ( 160) pour les plus grandes instances. La troisième contribution consiste à étudier l'utilisation combinée des GPUs avec les processeurs multi-coeurs. Deux scénarios ont été explorés conduisant à deux approches: une concurrente (RLL-GB&B) et une coopérative (PLL-GB&B). Dans le premier cas, le processus d'exploration est eff ectué simultanément par le GPU et les coeurs du CPU. Dans l'approche coopérative, les coeurs du CPU préparent et transfèrent les sous-problèmes en utilisant le streaming CUDA tandis que le GPU eff ectue l'exploration. L'utilisation combinée du multi-coeur et du GPU a montré que l'utilisation de RLL-GB&B n'est pas bénéfi que et que PLL-GB&B permet une amélioration allant jusqu'à (36%) par rapport à LL-GB&B. Sachant que récemment des grilles de calcul comme Grid5000 (certains sites) ont été équipées avec des GPU, la quatrième contribution de cette thèse traite de la combinaison du calcul sur GPU et multi-coeur avec le calcul distribué à grande échelle. Pour ce faire, les diff érentes approches proposées ont été réunies dans un méta-algorithme hétérofigène qui sélectionne automatiquement l'algorithme à déployer en fonction de la con figuration matérielle cible. Ce méta-algorithme est couplé avec l'approche B&B@Grid proposée dans [Mezmaz et al., IEEE IPDPS'2007]. B&B@Grid répartit les unités de travail (sous-espaces de recherche codés par des intervalles) entre les noeuds de la grille tandis que le méta-algorithme choisit et déploie localement un algorithme de B&B parallèle sur les intervalles reçus. L'approche combinée nous a permis de résoudre à l'optimalité et e fficacement les instances (20 20) de Taillard.

La première partie de ce travail concerne la production cyclique pour l'optimisation du taux de production dans les flowshops robotisés, où un robot est chargé du transport des pièces. Les cellules robotisées peuvent être disposées de façon linéaire ou circulaire. Les principaux résultats théoriques concernant la disposition linéaire ne peuvent être étendus à la configuration circulaire. En particulier, trouver le meilleur cycle de production de une pièce (1-cycle) est un problème polynomial dans le cas des cellules linéaires additives, mais NP-difficile pour la configuration correspondante circulaire.Nous nous concentrons principalement sur le cas des cellules circulaires équilibrées, où le temps d'usinage est identique sur toutes les machines. Après avoir présentés des outils pour l'analyse cyclique dans les cellules circulaires, nous établissons des propriétés nécessaires des 1-cycles performants, ce qui permet de conclure sur le problème du meilleur 1-cycle jusqu'à 8 machines. Toutefois, nous fournissons un contre-exemple pour 6 machines à la conjecture classique des 1-cycles, toujours ouverte dans cette configuration.Ensuite, nous étudions la structure des 1-cycles performants pour des cellules circulaires équilibrées arbitrairement grandes. Nous définissons et étudions les propriétés d'une nouvelle famille de cycles basée sur cette structure et formulons une conjecture sur sa dominance sur les 1-cycles qui conduirait à un algorithme polynomial pour le problème du meilleur 1-cycle dans ce cas. Cette structure permet de déterminer le meilleur 1-cycle jusqu'à 11 machines.Dans la deuxième partie, nous présentons le travail réalisé sur un problème industriel proposé par la SNCF dans le cadre du challenge ROADEF/EURO. Nous proposons un algorithme glouton pour ce problème combinant divers aspects de la gestion des trains au sein d'une gare. / The first part of this work deals with cyclic production for throughput optimization in robotic flow-shops, where a robot is in charge of the material handling of parts. Robotic cells may have a linear or a circular layout. Most theoretical results for the linear layout do not hold for the circular layout. In particular, the problem of finding the best one part production cycle (1-cycle), which is a polynomial problem for linear additive cells, has been proved NP-hard for the corresponding circular configuration.We mainly focus on a special case of circular balanced cells, where the processing times are identical for all machines. After presenting tools for cyclic analysis in circular cells, we study necessary properties of efficient 1-cycles. These results allow to conclude on the best one part production cycle for any parameters in circular balanced cells up to 8 machines. However, we provide a counter-example to the classical 1-cycle conjecture, still open for this configuration.Then, we study the structure of efficient one part production cycles in arbitrarily large circular balanced cells. We introduce and study a new family of cycles based on this structure, and formulate a conjecture on its dominance over one part-production cycles, which would lead to a polynomial algorithm for finding the best 1-cycle for circular balanced cells. This structure allows to settle the best one part production cycle for cells with up to 11 machines.In a second part, we present work on an industrial problem of railway stock scheduling proposed by the French railway company in the context of the ROADEF/EURO competition. We propose a greedy algorithm for this problem combining the various aspects of trains handling inside a station.

[EN] Nowadays, manufacturing systems meet different new global challenges and the existence of a collaborative manufacturing environment is essential to face with. Distributed manufacturing and assembly systems are two manufacturing systems which allow industries to deal with some of these challenges. This thesis studies a production problem in which both distributed manufacturing and assembly systems are considered. Although distributed manufacturing systems and assembly systems are well-known problems and have been extensively studied in the literature, to the best of our knowledge, considering these two systems together as in this thesis is the first effort in the literature. Due to the importance of scheduling optimization on production performance, some different ways to optimize the scheduling of the considered problem are discussed in this thesis. The studied scheduling setting consists of two stages: A production and an assembly stage. Various production centers make the first stage. Each of these centers consists of several machines which are dedicated to manufacture jobs. A single assembly machine is considered for the second stage. The produced jobs are assembled on the assembly machine to form final products through a defined assembly program. In this thesis, two different problems regarding two different production configurations for the production centers of the first stage are considered. The first configuration is a flowshop that results in what we refer to as the Distributed Assembly Permutation Flowshop Scheduling Problem (DAPFSP). The second problem is referred to as the Distributed Parallel Machine and Assembly Scheduling Problem (DPMASP), where unrelated parallel machines configure the production centers. Makespan minimization of the product on the assembly machine located in the assembly stage is considered as the objective function for all considered problems. In this thesis some extensions are considered for the studied problems so as to bring them as close as possible to the reality of production shops. In the DAPFSP, sequence dependent setup times are added for machines in both production and assembly stages. Similarly, in the DPMASP, due to technological constraints, some defined jobs can be processed only in certain factories. Mathematical models are presented as an exact solution for some of the presented problems and two state-of-art solvers, CPLEX and GUROBI are used to solve them. Since these solvers are not able to solve large sized problems, we design and develop heuristic methods to solve the problems. In addition to heuristics, some metaheuristics are also designed and proposed to improve the solutions obtained by heuristics. Finally, for each proposed problem, the performance of the proposed solution methods is compared through extensive computational and comprehensive ANOVA statistical analysis. / [ES] Los sistemas de producción se enfrentan a retos globales en los que el concepto de fabricación colaborativa es crucial para poder tener éxito en el entorno cambiante y complejo en el que nos encontramos. Una característica de los sistemas productivos que puede ayudar a lograr este objetivo consiste en disponer de una red de fabricación distribuida en la que los productos se fabriquen en localizaciones diferentes y se vayan ensamblando para obtener el producto final. En estos casos, disponer de modelos y herramientas para mejorar el rendimiento de sistemas de producción distribuidos con ensamblajes es una manera de asegurar la eficiencia de los mismos. En esta tesis doctoral se estudian los sistemas de fabricación distribuidos con operaciones de ensamblaje. Los sistemas distribuidos y los sistemas con operaciones de ensamblaje han sido estudiados por separado en la literatura. De hecho, no se han encontrado estudios de sistemas con ambas características consideradas de forma conjunta. Dada la complejidad de considerar conjuntamente ambos tipos de sistemas a la hora de realizar la programación de la producción en los mismos, se ha abordado su estudio considerando un modelo bietápico en la que en la primera etapa se consideran las operaciones de producción y en la segunda se plantean las operaciones de ensamblaje. Dependiendo de la configuración de la primera etapa se han estudiado dos variantes. En la primera variante se asume que la etapa de producción está compuesta por sendos sistemas tipo flowshop en los que se fabrican los componentes que se ensamblan en la segunda etapa (Distributed Assembly Permutation Flowshop Scheduling Problem o DAPFSP). En la segunda variante se considera un sistema de máquinas en paralelo no relacionadas (Distributed Parallel Machine and Assembly Scheduling Problem o DPMASP). En ambas variantes se optimiza la fecha de finalización del último trabajo secuenciado (Cmax) y se contempla la posibilidad que existan tiempos de cambio (setup) dependientes de la secuencia de trabajos fabricada. También, en el caso DPMASP se estudia la posibilidad de prohibir o no el uso de determinadas máquinas de la etapa de producción. Se han desarrollado modelos matemáticos para resolver algunas de las variantes anteriores. Estos modelos se han resuelto mediante los programas CPLEX y GUROBI en aquellos casos que ha sido posible. Para las instancias en los que el modelo matemático no ofrecía una solución al problema se han desarrollado heurísticas y metaheurísticas para ello. Todos los procedimientos anteriores han sido estudiados para determinar el rendimiento de los diferentes algoritmos planteados. Para ello se ha realizado un exhaustivo estudio computacional en el que se han aplicado técnicas ANOVA. Los resultados obtenidos en la tesis permiten avanzar en la comprensión del comportamiento de los sistemas productivos distribuidos con ensamblajes, definiendo algoritmos que permiten obtener buenas soluciones a este tipo de problemas tan complejos que aparecen tantas veces en la realidad industrial. / [CAT] Els sistemes de producció s'enfronten a reptes globals en què el concepte de fabricació col.laborativa és crucial per a poder tindre èxit en l'entorn canviant i complex en què ens trobem. Una característica dels sistemes productius que pot ajudar a aconseguir este objectiu consistix a disposar d'una xarxa de fabricació distribuïda en la que els productes es fabriquen en localitzacions diferents i es vagen acoblant per a obtindre el producte final. En estos casos, disposar de models i ferramentes per a millorar el rendiment de sistemes de producció distribuïts amb acoblaments és una manera d'assegurar l'eficiència dels mateixos. En esta tesi doctoral s'estudien els sistemes de fabricació distribuïts amb operacions d'acoblament. Els sistemes distribuïts i els sistemes amb operacions d'acoblament han sigut estudiats per separat en la literatura però, en allò que es coneix, no s'han trobat estudis de sistemes amb ambdós característiques conjuntament. Donada la complexitat de considerar conjuntament ambdós tipus de sistemes a l'hora de realitzar la programació de la producció en els mateixos, s'ha abordat el seu estudi considerant un model bietàpic en la que en la primera etapa es consideren les operacions de producció i en la segona es plantegen les operacions d'acoblament. Depenent de la configuració de la primera etapa s'han estudiat dos variants. En la primera variant s'assumix que l'etapa de producció està composta per sengles sistemes tipus flowshop en els que es fabriquen els components que s'acoblen en la segona etapa (Distributed Assembly Permutation Flowshop Scheduling Problem o DAPFSP). En la segona variant es considera un sistema de màquines en paral.lel no relacionades (Distributed Parallel Machine and Assembly Scheduling Problem o DPMASP). En ambdós variants s'optimitza la data de finalització de l'últim treball seqüenciat (Cmax) i es contempla la possibilitat que existisquen temps de canvi (setup) dependents de la seqüència de treballs fabricada. També, en el cas DPMASP s'estudia la possibilitat de prohibir o no l'ús de determinades màquines de l'etapa de producció. S'han desenvolupat models matemàtics per a resoldre algunes de les variants anteriors. Estos models s'han resolt per mitjà dels programes CPLEX i GUROBI en aquells casos que ha sigut possible. Per a les instàncies en què el model matemàtic no oferia una solució al problema s'han desenrotllat heurístiques i metaheurísticas per a això. Tots els procediments anteriors han sigut estudiats per a determinar el rendiment dels diferents algoritmes plantejats. Per a això s'ha realitzat un exhaustiu estudi computacional en què s'han aplicat tècniques ANOVA. Els resultats obtinguts en la tesi permeten avançar en la comprensió del comportament dels sistemes productius distribuïts amb acoblaments, definint algoritmes que permeten obtindre bones solucions a este tipus de problemes tan complexos que apareixen tantes vegades en la realitat industrial. / Hatami, S. (2016). The Distributed and Assembly Scheduling Problem [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/64072 / TESIS

In today's competitive environment, the importance of continuous production, quality improvement, and fast delivery has forced production and delivery processes to become highly reliable. Keeping equipment in good condition through maintenance activities can ensure a more reliable system. However, maintenance leads to temporary reduction in capacity that could otherwise be utilized for production. Therefore, the coordination of maintenance and production is important to guarantee good system performance. The central thesis of this dissertation is that integrating maintenance and production decisions increases efficiency by ensuring high quality production, effective resource utilization, and on-time deliveries. Firstly, we study the problem of integrated maintenance and production planning where machines are preventively maintained in the context of a periodic review production system with uncertain yield. Our goal is to provide insight into the optimal maintenance policy, increasing the number of finished products. Specifically, we prove the conditions that guarantee the optimal maintenance policy has a threshold type. Secondly, we address the problem of integrated maintenance planning and production scheduling where machines are correctively maintained in the context of a dynamic aircraft repair shop. To solve the problem, we view the dynamic repair shop as successive static repair scheduling sub-problems over shorter periods. Our results show that the approach that uses logic-based Benders decomposition to solve the static sub-problems, schedules over longer horizon, and quickly adjusts the schedule increases the utilization of aircraft in the long term. Finally, we tackle the problem of integrated maintenance planning and production scheduling where machines are preventively maintained in the context of a multi-machine production system. Depending on the deterioration process of machines, we design decomposed techniques that deal with the stochastic and combinatorial challenges in different, coupled stages. Our results demonstrate that the integrated approaches decrease the total maintenance and lost production cost, maximizing the on-time deliveries. We also prove sufficient conditions that guarantee the monotonicity of the optimal maintenance policy in both machine state and the number of customer orders. Within these three contexts, this dissertation demonstrates that the integrated maintenance and production decision-making increases the process efficiency to produce high quality products in a timely manner.