O tema de roteamento de veículos é de grande importância na literatura e tem sido amplamente estudada pela sua importância para muitas indústrias. Com a evolução na literatura, mais características foram adicionadas para torná-lo mais próximo de situações reais. Alinhado com esta tendência, este trabalho aborda o problema de roteamento de veículos quando há a terceirização da frota que realiza as entregas. Uma forma de cobrança do frete é por meio de custos escalonados, que são calculados de acordo com o tipo de veículo e a distância percorrida, com valores fixos para cada faixa de distância. Embora seja uma forma comum de trabalho na indústria, nenhum trabalho focado nesta característica foi encontrado na literatura. Este problema é o problema de roteamento de veículos com frota mista, janelas de tempo e custos escalonados (FSMVRPTWSC). Ao abordar este problema, este trabalho apresenta um modelo de programação linear inteira mista que é avaliado em um cenário real da indústria. Além disso, três heurísticas de inserção sequencial são propostas para lidar com problemas maiores. Estes métodos são examinados por meio de testes computacionais em 168 problemas de referência gerados para este problema. Os experimentos numéricos mostram que os métodos são robustos e eficientes, apresentando um bom desempenho em conjuntos de problemas com diversas características. / The theme of vehicle routing is of great importance in the literature and has been widely studied for its relevance to many industries and, throughout the literature, more characteristics have been added to make it closer to real situations. Aligned with this trend, this paper addresses the vehicle routing problem when there is outsourcing of the fleet that delivers goods. One form of freight charging is by scaled costs, which are calculated according to the type of vehicle and the distance traveled, with fixed values for each distance range. Though it is a common form of work in the industry, no work focused on this characteristic was found in the literature. This problem is the fleet size and mix vehicle routing problem with time windows and scaled costs (FSMVRPTWSC). In approaching this problem, this paper presents a mixed integer linear programming model that is evaluated under a real situation scenario. Furthermore, three sequential insertion heuristics are proposed in order to deal with larger problems. These methods are examined through a computational comparative study in 168 benchmark problems generated for this problem. The numerical experiments show that the methods are robust and efficient, performing well in different problem sets.

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.

Les systèmes adaptatifs basés sur les architectures FPGA (Field-Programmable Gate Arrays) peuvent bénéficier grandement de la grande flexibilité offerte par la reconfiguration partielle dynamique (DPR). Grâce au DPR, les tâches matérielles composant un système adaptatif peuvent être allouées et re-allouées à la demande ou en fonction de l'environnement dynamique. Les flots de conceptions disponibles et les outils commerciaux ont évolué pour répondre aux exigences des architectures reconfigurables qui sont toutefois limitées dans leurs fonctionnalités. Ces outils ne permettent pas un placement et une relocation efficaces de tâches matérielles de tailles variables. L'objectif principal de ces travaux de thèse consiste à proposer des nouvelles méthodologies et de nouvelles approches pour faciliter au concepteur la phase de conception d'un système adaptatif reconfigurable opérationnelle, valide, optimisé et adapté aux changements dynamiques de l'environnement. La première contribution de cette thèse porte sur la problématique de la relocation des tâches matérielles de tailles différentes. Une méthodologie de conception est proposée pour répondre à un problème majeur des mécanismes de relogement : le stockage d'une unique bitstream de configuration pour réduire les besoins de la mémoire et pour accroître la réutilisable des modules matériels générés. Une technique de partitionnement de la région reconfigurable est appliquée dans la méthodologie de relogement proposée pour augmenter l'efficacité d'utilisation des ressources matérielles dans le cas des tâches reconfigurables de tailles variables. Cette méthodologie prend en compte aussi la communication entre différentes régions reconfigurables et la région statique. Pour valider la méthode, plusieurs études de cas sont implémentées. Cette validation montre une utilisation efficace des ressources matérielles ainsi une réduction importante du temps de reconfiguration. La deuxième partie de cette thèse présente et détaille une formulation mathématique afin d'automatiser le floorplanning des zones reconfigurables dans les FPGAs. Les algorithmes de recherche présentés dans cette thèse sont basés sur la technique d'optimisation PLMNE (programmation linéaire mixte en nombres entiers). Ces algorithmes permettent de définir automatiquement l'emplacement, la taille et la forme de la zone reconfigurable dynamique. Nous nous intéressons principalement dans cette recherche à la satisfaction des contraintes de placement des zones reconfigurables et celles liées à la relocation. De plus, nous considérons l’optimisation des ressources matérielles dans le FPGA en tenant compte des tâches de tailles variables. Finalement, une évaluation de l'approche proposée est présentée / Adaptive systems based on Field-Programmable Gate Arrays (FPGA) architectures can benefit greatly from the high degree of flexibility offered by dynamic partial reconfiguration (DPR). Thanks to DPR, hardware tasks composing an adaptive system can be allocated and relocated on demand or depending on the dynamically changing environment. Existing design flows and commercial tools have evolved to meet the requirements of reconfigurables architectures, but that are limited in functionality. These tools do not allow an efficient placement and relocation of variable-sized hardware tasks. The main objective of this thesis is to propose a new methodology and a new approaches to facilitate to the designers the design phase of an adaptive and reconfigurable system and to make it operational, valid, optimized and adapted to dynamic changes in the environment. The first contribution of this thesis deals with the issues of relocation of variable-sized hardware tasks. A design methodology is proposed to address a major problem of relocation mechanisms: storing a single configuration bitstream to reduce memory requirements and increasing the reusability of generating hardware modules. A reconfigurable region partitioning technique is applied in this proposed relocation methodology to increase the efficiency of use of hardware resources in the case of reconfigurable tasks of variable sizes. This methodology also takes into account communication between different reconfigurable regions and the static region. To validate the design method, several cases studies are implemented. This validation shows an efficient use of hardware resources and a significant reduction in reconfiguration time. The second part of this thesis presents and details a mathematical formulations in order to automate the floorplanning of the reconfigurable regions in the FPGAs. The algorithms presented in this thesis are based on the optimization technique MILP (mixed integer linear programming). These algorithms allow to define automatically the location, the size and the shape of the dynamic reconfigurable region. We are mainly interested in this research to satisfy the constraints of placement of the reconfigurable zones and those related to the relocation. In addition, we consider the optimization of the hardware resources in the FPGA taking into account the tasks of variable sizes. Finally, an evaluation of the proposed approach is presented

Orientador: John Fredy Franco Baquero / Resumo: A crescente penetração dos Veículos Elétricos (VEs) no setor de transportes representa um novo e grande desafio para o planejamento da expansão e da operação dos Sistemas de Distribuição de Energia Elétrica (SDEEs) devido ao correspondente aumento da demanda associada ao carregamento das baterias. Portanto, devem ser desenvolvidos métodos que ajudem os SDEEs a lidar com esses desafios, considerando as incertezas associadas às demandas convencionais e aos VEs. Nesta tese é proposto um método robusto baseado em um modelo de Programação Linear Inteira-Mista (PLIM) para auxiliar a integração de VEs no SDEE. O método proposto permite resolver o problema de planejamento multi-estágio da expansão do SDEE considerando a alocação e o dimensionamento de Estações de Carregamento de VEs (ECVEs). Restrições probabilísticas são usadas na formulação proposta para lidar com as incertezas associadas à demanda, garantindo o cumprimento da capacidade de potência das subestações com um nível de confiança especificado. O modelo proposto para o planejamento da expansão avalia a construção e/ou reforço de subestações, ECVEs e circuitos, assim como também a alocação de unidades de geração distribuída e bancos de capacitores ao longo do horizonte de planejamento. O modelo de PLIM proposto é resolvido através de técnicas de otimização clássica visando garantir a solução ótima do problema. A eficiência e robustez do modelo são verificadas usando sistemas teste de 18 e 54 nós, junto com simulações de Mo... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The increasing penetration of electric vehicles (EVs) in the transportation sector represents a new challenge for the expansion planning of electrical distribution systems (EDS) due to the corresponding increase of the energy demand. Therefore, methods to support the EDS considering the uncertainties associated with conventional and EV demands should be developed. This thesis presents a methodology to consider the EV integration into the EDS. A mixed-integer linear programming (MILP) model is proposed to solve the multi-stage expansion planning of EDS considering the allocation and sizing of EV charging stations (EVCSs). Chance constraints are used in the formulation to deal with the uncertainties associated with the demands, guaranteeing the fulfilment of the substation capacities within a given confidence level. The proposed model for the expansion planning considers the construction/reinforce of substations, EVCSs and circuits as well as the allocation of distributed generation units and capacitor banks along the planning horizon. The proposed MILP model guarantees optimality using classical optimization techniques. The efficiency and robustness of the model is verified using two test systems with 18-nodes and 54-nodes. Monte Carlo simulations were carried out to verify the compliance of the proposed chance constraint. / Doutor

Nous présentons les enjeux du management environnemental et soulignons l’importance d’une politique d’économie d’énergie pour les entreprises. Nous proposons un modèle pour déterminer le bilan énergétique de la fabrication en intégrant les différentes phases productives et non-productives. Nous définissons un double objectif pour la minimisation de la durée de production et de la consommation d’énergie. Nous appliquons ce modèle à l’ordonnancement d’ateliers job-shop flexibles. Pour déterminer la solution optimale nous utilisons deux classes de méthodes : - La première relève des algorithmes génétiques. Nous proposons différents types d’algorithmes pour résoudre ce problème multicritère. Nous proposons par exemple de faire évoluer deux populations pour minimiser respectivement l’énergie consommée et la durée de production et de les croiser pour atteindre l’objectif global. - La seconde relève de la programmation sous contrainte. Nous proposons de rechercher la solution optimale en développant une double arborescence pour évaluer l’énergie consommée et la durée de production. Nous construisons notre algorithme en partant des tâches à réaliser sur les machines ou en partant des machines qui réaliseront les tâches. Nous discutons de la construction du front de Pareto pour l’obtention de la meilleure solution.Nous terminons en comparant les différentes approches et en discutant leur pertinence pour traiter des problèmes de différentes tailles. Nous proposons également plusieurs améliorations et quelques pistes pour de futures recherches. / We present the challenges of environmental management and underline the importance of an energy saving policy for companies. We propose a model to determine the energy balance of manufacturing by integrating the different productive and non-productive phases. We define two purposes for minimizing production time and energy consumption. We apply this model to the scheduling of flexible job-shop workshops. To determine the optimal solution we use two types of methods: - The first is genetic algorithms. We propose different types of algorithms to solve this multi-criteria problem. For example, we propose to develop two populations to minimize the energy consumed and the production time, and to cross them to achieve the overall objective. - The second is constraint programming. We propose to find the optimal solution by developing a double tree to evaluate the energy consumed and the production time. We build our algorithm starting from the tasks to be performed on the machines or from the machines that will perform the tasks. We discuss the construction of the Pareto front to get the best solution.We finish by comparing the different approaches and discussing their relevance to deal with problems of different sizes. We also offer several improvements and some leads for future research.

Orientador: Marcos Julio Rider Flores / Abstract: Electric distribution networks should be prepared to provide an economic and reliable service to all customers, as well as to integrate technologies related to distributed generation, energy storage, and plug-in electric vehicles. A proper representation of the electric distribution network operation, taking into account smart grid technologies, is key to accomplish these goals. This work presents mathematical formulations for the steady-state operation of electric distribution networks, which consider the unbalance of three-phase grids. Mathematical models of the operation of smart grid-related devices present in electric distribution networks are developed (e.g., volt-var control devices, energy storage systems, and plug-in electric vehicles). Furthermore, features related to the voltage dependency of loads, distributed generation, and voltage and thermal limits are also included. These formulations constitute a mathematical framework for optimization analysis of the electric distribution network operation, which could assist planners in decision-making processes. Different objectives related to technical and/or economic aspects can be pursued within the framework; in addition, the extension to multi-period and multi-scenario optimization is discussed. The presented models are built based on mixed integer linear programming formulations, avoiding the use of conventional mixed integer nonlinear formulations. The application of the presented framework is illustrated throughou... (Complete abstract click electronic access below) / Resumo: As redes de distribuição de energia elétrica devem estar preparadas para fornecer um serviço econômico e confiável a todos os clientes, bem como para integrar tecnologias relacionadas à geração distribuída, armazenamento de energia e veículos elétricos. Uma representação adequada da operação das redes de distribuição, considerando as tecnologias de redes inteligentes, é fundamental para atingir esses objetivos. Este trabalho apresenta formulações matemáticas para a operação em regime permanente das redes de distribuição, que consideram o desequilíbrio de redes trifásicas. Modelos matemáticos da operação de dispositivos relacionados à redes inteligentes presentes em redes de distribuição são desenvolvidos (e.g., dispositivos de controle volt-var, sistemas de armazenamento de energia e veículos elétricos). Além disso, características relacionadas à dependência da tensão das cargas, geração distribuída e limites térmico e de tensão também estão incluídos. Essas formulações constituem um marco matemático para a análise de otimização da operação das redes de distribuição de energia elétrica, o que possibilita modelar os processos de tomada de decisões. Objetivos diferentes relacionados a aspectos técnicos e/ou econômicos podem ser almejados dentro deste marco; Além disso, a extensão para otimização multi-período e multi-cenário é discutida. Os modelos apresentados são construídos com base em formulações de programação linear inteira mista, evitando o uso de formulações não-lineare... (Resumo completo, clicar acesso eletrônico abaixo) / Doutor

To make a difference among the energy intensive process industries, this dissertation addresses production planning and supply chain planning problems related to industrial energy management issues. The energy issue is turning more and more important from different angles, involving price as well as environmental problems due to climate change leading to political pressure on all energy users. The process industry sector is one of the largest users of energy, and thus important to analyse. Process industries are also capital intensive and operate on large and expensive process equipment, making it imperative to plan their production well in order to reach preferable capacity utilisation. Therefore this dissertation strives to locate the most important energy management issues for the long term profitability of process industries, and investigates the  symbiotic effects of including energy issues in production and supply chain planning. Three different studies at three case companies are carried out, analysed, and presented in five papers. The cases represent the process industry sectors: chemicals, pulp, and steel. Both qualitative case study methodologies as well as quantitative mathematical modelling and optimisation approaches have been practiced. The research questions are analysed from both an energy system and from a production process point of view, separately as well as combined. Energy is somewhat considered to be the main workforce for process industries and this dissertation exemplifies some of its most important dimensions in this context. Several prerequisites for putting energy management on the strategic agenda are located in a specialty chemical industry where the importance of introducing a strategic perspective on energy, the way energy is used, and the possibilities of increasing alternative revenue from utilising by- and/or co-products differently are pinpointed. Approaches for including energy issues in planning processes are also suggested in terms of a MILP model for the entire supply chain of a pulp company, including decisions on purchase and transportation of raw maerials, production allocation, energy mix, and distribution. Another example is presented based on the perspectives of economics of scale and lot sizing through economic order quantity principles in a steel company. By using real company data, energy smart approaches in planning and scheduling are developed with respect to the most important intersections between the production processes and their supporting energy system. The accumulated resource intensity and embedded energy could, and probably should, hence be more fairly  reflected in the product price. The research finally shows some possible impact with including energy issues in a production and supply chain planning model. By planning differently, production prioritisations can be done, and it is not only possible without any large investments, but also prosperous with savings on both energy and money within reach. To conclude, planning of production and supply chain has either a direct or an indirect impact on the energy cost-effectiveness of a company. This dissertation argues that such impact also exists in its mutual form, and is very important when the energy issues are large enough, as they often are in the energy intensive process industry sector. Decision makers should thus beware of the short end of the stick that might be  devastating in the long run, but also aware of all the possibilities that can bring success and prosperity when the future begins.

[pt] O problema de roteamento de navios com gestão de estoques (conhecido pelo termo em inglês Maritime inventory routing ou MIR) representa um problema prático de logística onde o transportador da carga também é responsável pela manutenção dos estoques do produto transportado nos portos de carga e descarga. Esta tese estuda um caso real do problema MIR. Um conjunto de testes é apresentado de modo a comparar diferentes formulações matemáticas da literatura, a fim de encontrar aquela mais aderente ao problema real. Em função da complexidade computacional do problema, é apresentada uma abordagem heurística que consegue encontrar soluções similares e reduz consideravelmente o tempo computacional quando comparadas com as formulações baseadas em PLIM. No entanto, problemas reais são muito influenciados por aspectos incertos. Sendo assim, é apresentada uma abordagem robusta para a otimização do problema MIR, que considera incerteza no tempo de estadia do navio nos portos. A abordagem apresentada produz soluções para diferentes níveis de robustez. Em outras palavras, considera o risco de variação no tempo de estadia do navio em um porto durante uma operação de carga ou descarga. Assim, é capaz de determinar a probabilidade de inviabilidade da solução encontrada para cada nível de robustez oferecido, além do impacto no custo de transporte à medida que soluções mais robustas são apresentadas. Esta abordagem oferece ao tomador de decisão a medida do trade-off entre robustez e custo de transporte. Desta forma, o mesmo pode determinar qual o nível de conservadorismo irá adotar em sua programação de navios e quanto isto irá impactar o custo de transporte. Os experimentos apresentados identificaram que, aumentos sutís no nível de robustez (com pequeno impacto no custo de transporte) podem reduzir consideravelmente a probabilidade de inviabilidade de uma solução. / [en] Maritime inventory routing (MIR) problem is an academic name for a practical logistic problem that represents the routing or scheduling of vessels to carry product(s) between ports. Meanwhile, the product(s) inventory levels in these ports must remain between operational bounds during the entire planning horizon. This thesis focus on how to support decision on a real-life MIR problem faced by a Brazilian petroleum company. To do so, we structure a set of tests to compare different formulation from literature and identify which is more adherent to real problem. Due to computational complexity of the problem, we present an heuristic approach that provides reasonably good solutions when compared to deterministic mixed integer linear programming (MILP) formulations and reduces considerably the computational time of solving real-life instances. However, uncertainty events have great impact in the ship scheduling planning. Therefore, we propose a robust optimization approach that considers uncertainty in the time spent at ports in each ship visit. Our approach is able to determine the probability of infeasibility and the impact in the objective function for each level of robustness, helping to measure the uncertain aversion of the decision maker. Our experiments identified that, for a certain instance, varying the level of robustness one may reduce the probability of infeasibility from 87 per cent (of deterministic solution) to 2 per cent and it represents an increase in the transportation costs of about 13 per cent.

La présente thèse se déroule dans le cadre du projet ANR PRODIGE et est axée sur la recherche de stratégies permettant l’optimisation du transport en général et du transport routier de marchandises en particulier. Le problème de transport support de cette étude est le problème de collecte et livraison avec transbordement. Ce problème généralise plusieurs problèmes de transports classiques. Le transbordement y est utilisé comme levier de flexibilité et d’optimisation. Pour analyser et résoudre ce problème, les analyses sont effectuées suivant trois axes : le premier axe concerne l’élaboration d’un modèle analytique plus précisément d’un modèle mathématique en variables mixtes. Ce modèle permet de fournir dessolutions optimales au décisionnaire du transport mais présente l’inconvénient de nécessiter un temps de résolution qui croit exponentiellement avec la taille du problème. Cette limitation est levée par le deuxième axe d’étude qui permet de résoudre le problème de transport étudié par une méthode d’optimisation approchée tout en garantissant des solutions satisfaisantes.La méthode utilisée est une métaheuristique inspirée de la recherche à voisinages variables (VNS). Dans le troisième axe, l’ensemble des résultats obtenus dans la thèse sont testés en situation de transports réels via le projet PRODIGE. / The thesis is conducted under the ANR project PRODIGE and it is focused on seeking strategies allowing the optimization of transport in general and road freight transport in particular. The transportation problem support for this study is the pickup and delivery problem with transshipment.This problem generalizes several classical transportation problems.Transshipment is used as optimization and flexibility leverage. To study and solve this problem, analyzes are performed along three axes :the first objective concerns the development of an analytical model, more accurately a mathematical model with mixed variables. This model allows providing optimal solution to the decision maker, but has the disadvantage of requiring a time resolution that grows exponentially with the size of the problem. This limitation is overcome by the second line of the study that solves the transportation problem studied by an approximate optimization method while ensuring satisfactory solutions. The method used is a mataheuristic broadly followed the variables neighborhoods research principles. In the third objective, the overall results obtained in the thesis are tested in real transport situation via the PRODIGE project.

Cette thèse s’intéresse au fonctionnement cyclique multi-produits des ateliers de traitement de surface, et au problème d’ordonnancement associé (HSP), caractérisé par des contraintes fortes et atypiques, dont certaines sont liées aux ressources de transport. Dans le cas de productions en grandes séries, une commande cyclique de ces systèmes est particulièrement adaptée, permettant notamment de réduire la combinatoire de résolution, et sous réserve que les ratios de produits soient connus à l’avance. Notre objectif est de trouver le meilleur ordonnancement des tâches de traitement et de transport en un temps raisonnable. Pour cela, nous proposons une première approche, basée sur un modèle linéaire et une méthode de résolution arborescente de type séparation et évaluation. Nous présentons des modélisations pour différentes extensions du problème dit de base et nous fournissons des exemples illustratifs et des résultats sur des benchmarks. Par la suite et compte tenu de l’analyse de la littérature relative aux ordonnancements cycliques mono-produit et multi-produits, nous proposons tout d’abord une heuristique dédiée au cas multi-produits étudié, et basée sur un algorithme de liste. Avec ce dernier, nous obtenons un ordonnancement cyclique dont le degré du cycle n’est pas fixé au préalable. Enfin, nous présentons une deuxième modélisation approchée sous la forme d’un algorithme génétique pour résoudre un HSP 2-cyclique. Ces différents modèles sont validés par des tests sur des benchmarks de la littérature pour lesquels nous avons obtenus des résultats prometteurs. Nous terminons par une analyse critique des avantages et inconvénients des modèles élaborés et par quelques propositions de perspectives pour ce travail. / In this thesis, we study the Cyclic Hoist Scheduling Problem (CHSP) in automated electroplating lines, when a mass production must be achieved. The CHSP is characterized by specific constraints related to processing and transport resources. To solve it in a multi-parts context, we first elaborate a 2-degree cyclic model and an associated branch and bound algorithm. Then we extend it to more complex configurations. Then, we develop a dedicated heuristic to find a feasible repetitive sequence of hoist moves that minimizes the cycle time, without a priori fixing the cycle degree. Comparisons with existing algorithms are presented to show the efficiency of the proposed heuristic. To reduce the cycle time, we integrate in the general heuristic an algorithm with a set of Minimum Part Set (MPS) configurations’. This one allows us to find the best order in which jobs should be introduced into the line. Finally, we describe a genetic algorithm approach to find a schedule which can reach the optimal 2-cycle. We finally discuss the interest of those various models, based on the promising results obtained and we provide some perspectives which could be explored.