Submitted by Nadir Basilio (nadirsb@uninove.br) on 2018-01-24T20:53:58Z No. of bitstreams: 1 Andre Luis Marques Ferreira dos Santos.pdf: 3359520 bytes, checksum: 44628dce3b0bf9344584d99777736b0f (MD5) / Made available in DSpace on 2018-01-24T20:53:58Z (GMT). No. of bitstreams: 1 Andre Luis Marques Ferreira dos Santos.pdf: 3359520 bytes, checksum: 44628dce3b0bf9344584d99777736b0f (MD5) Previous issue date: 2017-08-30 / The internet has contributed to the appearance of new kinds of businesses, which require a peculiar scientific approach in order to enlarge the operational results of the said enterprises. This context gave rise to a new set of organizations, businesses focused on intellectual production, the so-called creative industries. One of the ways to assess these intellectual capital companies is the optimization of human resources time, also known as Human Resources Specialists (HRS). The optimization of HRS’ consists in identifying which resources must be allocated to each project and the order in which the given tasks must be undertaken. In literature, this subject is known as “integrated problem of resources allocation and task scheduling”, commonly studied in manufacture businesses as “job shop problem”, but there is very little reference of the subject in the context of creative industries. Based on this assumption, the goal of this piece of work is to apply heuristic techniques to solve the HRS allocation and task scheduling problems within creative industries in an integrated way. Therefore, the model developed herein becomes relevant to researches involving the use of intellectual capital. The mentioned model consists in representing, through computer simulations, the operation of a competitive intelligence department and, making use of heuristics, determine the best scenarios for system optimization. In other words, to identify which of those scenarios makes viable to perform all projects in the shortest time possible. This model was based in real data, collected in two years of thorough observation of a company, the study object of this work. The outcome was satisfactory and the proposed model has achieved its objective. / A Internet contribuiu para o surgimento de um novo tipo de organização, as indústrias criativas, empresas com negócios focados no capital intelectual, os quais podem ser avaliados por meio da otimização do tempo dos recursos humanos, também intitulado como, recursos humanos especialistas (RHE). A otimização dos RHE consiste em identificar quais os recursos devem ser alocados para cada projeto e em qual ordem as tarefas devem ser realizadas, tema conhecido na literatura como “problema integrado de alocação de recursos e sequenciamento de tarefas”, comumente estudado nas empresas de manufatura como job shop problem, mas com pouca referência no contexto das indústrias criativas. Partindo desse pressuposto o objetivo deste trabalho foi desenvolver um modelo de simulação e otimização computacional, para resolver de forma integrada o problema de alocação de RHE e sequenciamento de tarefas dentro de uma indústria criativa. Assim, este trabalho torna-se relevante para as pesquisas que envolvam o uso de capital intelectual. O modelo desenvolvido neste trabalho consiste em representar por meio de simulação computacional o funcionamento de um departamento de inteligência competitiva e determinar os melhores cenários para otimizar o sistema, ou seja, identificar quais cenários viabilizam realizar todos os projetos em um menor tempo possível. A parametrização do modelo foi realizada com base em informações reais, coletadas em dois anos de observações na empresa objeto de estudo desta pesquisa. Os resultados mostram que a utilização de métodos computacionais de otimização pode contribuir na tomada de decisão para minimizar o tempo de realização dos projetos e para identificar os pontos de ociosidade do sistema em ambientes dinâmicos.

Le besoin croissant de réactivité dans les différents secteurs industriels face à la volatilité des marchés soulève une forte demande de la flexibilité dans leur organisation. Cette flexibilité peut être utilisée pour améliorer la robustesse du planning de référence d’un programme d’activités donné. Les ressources humaines de l’entreprise étant de plus en plus considérées comme le coeur des structures organisationnelles, elles représentent une source de flexibilité renouvelable et viable. Tout d’abord, ce travail a été mis en oeuvre pour modéliser le problème d’affectation multi-périodes des effectifs sur les activités industrielles en considérant deux dimensions de la flexibilité: L’annualisation du temps de travail, qui concerne les politiques de modulation d’horaires, individuels ou collectifs, et la polyvalence des opérateurs, qui induit une vision dynamique de leurs compétences et la nécessité de prévoir les évolutions des performances individuelles en fonction des affectations successives. La nature dynamique de l’efficacité des effectifs a été modélisée en fonction de l’apprentissage par la pratique et de la perte de compétence pendant les périodes d’interruption du travail. En conséquence, nous sommes résolument placés dans un contexte où la durée prévue des activités n’est plus déterministe, mais résulte du nombre des acteurs choisis pour les exécuter, en plus des niveaux de leur expérience. Ensuite, la recherche a été orientée pour répondre à la question : « quelle genre, ou quelle taille, de problème pose le projet que nous devons planifier? ». Par conséquent, les différentes dimensions du problème posé sont classées et analysés pour être évaluées et mesurées. Pour chaque dimension, la méthode d’évaluation la plus pertinente a été proposée : le travail a ensuite consisté à réduire les paramètres résultants en composantes principales en procédant à une analyse factorielle. En résultat, la complexité (ou la simplicité) de la recherche de solution (c’est-à-dire de l’élaboration d’un planning satisfaisant pour un problème donné) peut être évaluée. Pour ce faire, nous avons développé une plate-forme logicielle destinée à résoudre le problème et construire le planning de référence du projet avec l’affectation des ressources associées, plate-forme basée sur les algorithmes génétiques. Le modèle a été validé, et ses paramètres ont été affinés via des plans d’expériences pour garantir la meilleure performance. De plus, la robustesse de ces performances a été étudiée sur la résolution complète d’un échantillon de quatre cents projets, classés selon le nombre de leurs tâches. En raison de l’aspect dynamique de l’efficacité des opérateurs, le présent travail examine un ensemble de facteurs qui influencent le développement de leur polyvalence. Les résultats concluent logiquement qu’une entreprise en quête de flexibilité doit accepter des coûts supplémentaires pour développer la polyvalence de ses opérateurs. Afin de maîtriser ces surcoûts, le nombre des opérateurs qui suivent un programme de développement des compétences doit être optimisé, ainsi que, pour chacun d’eux, le degré de ressemblance entre les nouvelles compétences développées et les compétences initiales, ou le nombre de ces compétences complémentaires (toujours pour chacun d’eux), ainsi enfin que la façon dont les heures de travail des opérateurs doivent être réparties sur la période d’acquisition des compétences. Enfin, ce travail ouvre la porte pour la prise en compte future des facteurs humains et de la flexibilité des effectifs pendant l’élaboration d’un planning de référence. / The growing need of responsiveness for manufacturing companies facing the market volatility raises a strong demand for flexibility in their organization. This flexibility can be used to enhance the robustness of a baseline schedule for a given programme of activities. Since the company personnel are increasingly seen as the core of the organizational structures, they provide the decision-makers with a source of renewable and viable flexibility. First, this work was implemented to model the problem of multi-period workforce allocation on industrial activities with two degrees of flexibility: the annualizing of the working time, which offers opportunities of changing the schedules, individually as well as collectively. The second degree of flexibility is the versatility of operators, which induces a dynamic view of their skills and the need to predict changes in individual performances as a result of successive assignments. The dynamic nature of workforce’s experience was modelled in function of learning-by-doing and of oblivion phenomenon during the work interruption periods. We firmly set ourselves in a context where the expected durations of activities are no longer deterministic, but result from the number and levels of experience of the workers assigned to perform them. After that, the research was oriented to answer the question “What kind of problem is raises the project we are facing to schedule?”: therefore the different dimensions of the project are inventoried and analysed to be measured. For each of these dimensions, the related sensitive assessment methods have been proposed. Relying on the produced correlated measures, the research proposes to aggregate them through a factor analysis in order to produce the main principal components of an instance. Consequently, the complexity or the easiness of solving or realising a given scheduling problem can be evaluated. In that view, we developed a platform software to solve the problem and construct the project baseline schedule with the associated resources allocation. This platform relies on a genetic algorithm. The model has been validated, moreover, its parameters has been tuned to give the best performance, relying on an experimental design procedure. The robustness of its performance was also investigated, by a comprehensive solving of four hundred instances of projects, ranked according to the number of their tasks. Due to the dynamic aspect of the workforce’s experience, this research work investigates a set of different parameters affecting the development of their versatility. The results recommend that the firms seeking for flexibility should accept an amount of extra cost to develop the operators’ multi functionality. In order to control these over-costs, the number of operators who attend a skill development program should be optimised, as well as the similarity of the new developed skills relative to the principal ones, or the number of the additional skills an operator may be trained to, or finally the way the operators’ working hours should be distributed along the period of skill acquisition: this is the field of investigations of the present work which will, in the end, open the door for considering human factors and workforce’s flexibility in generating a work baseline program.