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Otsubo, Hironori. "Dynamic Volunteer's Dilemmas, Unique Bid Auctions, and Discrete Bottleneck Games: Theory and Experiments." Diss., The University of Arizona, 2008. http://hdl.handle.net/10150/194255.
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The main theme of my dissertation is the analysis of several interactive decision making situations with multiple decision makers whose interests do not fully coincide. Non-cooperative game theory is invoked to carry on this analysis.The first chapter describes an experimental study of volunteer's dilemmas that evolve over time. Only a single volunteer is required for the public good to be provided. Because volunteering is costly, each prefers that some other players bear the full costs of volunteering. Reflecting on the observation that in many naturally occurring social dilemmas it is beneficial to volunteer earlier than later, I assume that the payoff to the volunteer and the (higher) payoff to each of the non-volunteers decrease monotonically over time. I derive symmetric and asymmetric subgame perfect equilibria. The experimental results provide little support to asymmetric equilibria in which only a single subject volunteers immediately. In comparison to the symmetric subgame perfect equilibrium, they show that subjects volunteer, on average, earlier than predicted.The second chapter explores a new type of online auction, called the unique bid auction, that has recently emerged on the Internet and gained widespread popularity in many countries. In a sharp contrast to traditional auctions, the winner in this class of auctions is the bidder who submits the lowest (highest) unique bid; all ties are discarded. I propose an algorithm to numerically compute the symmetric mixed-strategy Nash equilibrium solution and then conduct a series of experiments to assess the predictive power of the equilibrium solution. The experimental results show that the solution accounts quite well for the subjects' bidding behavior on the aggregate level, but not on the individual level.The last chapter proposes a discrete version of William Vickrey's model of traffic congestion on a single road with a single bottleneck. In my model, both the strategy space and number of commuters are finite. An algorithm similar to the one used in the second chapter is proposed to numerically calculate the symmetric mixed-strategy Nash equilibrium. The discrete model is then compared with the original continuous model of Vickrey in terms of the equilibrium solution and its implications.
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Atienza, Nicolas. "Towards Reliable ML : Leveraging Multi-Modal Representations, Information Bottleneck and Extreme Value Theory." Electronic Thesis or Diss., université Paris-Saclay, 2025. http://www.theses.fr/2025UPASG025.
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Cette thèse de doctorat porte sur l'amélioration de la fiabilité de l'apprentissage automatique, en particulier pour les applications à forts enjeux. Les modèles d'apprentissage profond actuels, bien que très performants, restent difficiles à appréhender et à déployer de manière sûre en raison de leur opacité, de leur vulnérabilité aux attaques adverses, de leur sensibilité aux changements de distribution, et de leur inefficacité en contexte de données ou de ressources limitées. Pour surmonter ces limites, ce travail explore trois dimensions complémentaires : l'explicabilité, la robustesse et la frugalité.Sur le plan de l’explicabilité, il propose une méthode appelée CB2, qui introduit une forme d’interprétabilité par concepts pour les réseaux neuronaux profonds. CB2 s’appuie sur des embeddings multi-modaux et la théorie de la décision pour aligner les représentationsinternes du modèle sur des concepts compréhensibles par l’humain. Cette technique permet de mieux comprendre pourquoi un modèle produit une prédiction donnée et d’inspecter les biais potentiels dans le processus de décision. Par rapport aux méthodes post-hoc classiques, CB2 fournit des explications plus structurées et sémantiquement riches, validées sur plusieurs jeux de données en vision par ordinateur.Sur le plan de la robustesse, deux approches sont proposées pour renforcer la fiabilité des modèles. La première, nommée POSIB, est une méthode post-entraînement fondée sur le principe de l’Information Bottleneck, qui restructure l’espace latent du modèle afin de dissocier les caractéristiques informatives du bruit et des corrélations non pertinentes. Cela améliore la robustesse sans compromettre la précision prédictive. La seconde approche, appelée SPADE, traite de la détection des échantillons hors distribution (OOD) et des entrées adverses. SPADE exploite la théorie des valeurs extrêmes pour caractériser le comportement des queues de distribution latente, offrant ainsi une manière rigoureuse de détecter les entrées inconnues ou malveillantes et de s’abstenir de prédictions peu fiables. Les expériences menées sur différentes architectures et jeux de données montrent que SPADE atteint des performances de pointe en détection OOD et en défense contre les attaques adverses.Enfin, ce travail s’intéresse aussi à la frugalité, en reconnaissant que les modèles déployés dans des contextes industriels ou critiques fonctionnent souvent sous des contraintes sévères en données et en ressources de calcul. Pour relever ces défis, il développe des techniques d’apprentissage de représentations frugales qui optimisent le contenu informationnel des espaces latents, en ne conservant que les caractéristiques essentielles. Combiné avec le cadre de robustesse, il propose F-STUDENT, une version distillée des modèles robustes, qui compresse le réseau tout en préservant sa capacité à résister aux attaques adverses. Cette approche surpasse les méthodes classiques d’élagage en s’appuyant sur une distillation multi-étapes et une régularisation par goulot d’étranglement informationnel.Dans l’ensemble, cette thèse contribue à combler le fossé entre les avancées théoriques de l’apprentissage automatique moderne et les exigences pratiques du déploiement de l’IA dans des environnements critiques. En abordant conjointement l’explicabilité, la robustesse et la frugalité, elle propose un cadre complet pour le développement de systèmes d’apprentissage fiables, dignes de confiance dans des applications réelles à forts enjeux<br>This PhD research focuses on making machine learning more reliable, particularly for high-stakes applications. Current deep learning models, while highly performant, remain difficult to trust because of their opacity, vulnerability to adversarial attacks, sensitivity to distribution shifts, and inefficiency when faced with limited data or resources. To address these limitations, this work explores three complementary dimensions: explainability, robustness, and frugality. On the explainability side, it proposes a method called CB2, which introduces concept-based interpretability for deep neural networks. CB2 relies on multi-modal embeddings and decision theory to align internal model representations with human-interpretable concepts. This technique allows us to better understand why a model makes a given prediction and inspect potential biases in the decision process. Compared to traditional post-hoc attribution methods, CB2 offers more structured and semantically meaningful explanations, validated across several computer vision datasets. In terms of robustness, it proposes two approaches to enhance model reliability. The first is POSIB, a post-training method based on the Information Bottleneck principle, which reshapes a model's latent space to disentangle informative features from noise and irrelevant correlations. This improves robustness without sacrificing predictive accuracy. The second approach, called SPADE, addresses the detection of out-of-distribution samples and adversarial inputs. SPADE leverages Extreme Value Theory to characterize the tail behavior of latent distributions, providing a principled way to detect unfamiliar or malicious inputs and abstain from unreliable predictions. Experiments across different architectures and datasets show that SPADE achieves state-of-the-art performance in both OOD detection and adversarial defense. Finally, this work also focuses on frugality, recognizing that models deployed in industrial or safety-critical contexts often operate under severe data and computational constraints. To meet these challenges, it develops frugal representation learning techniques that optimize the information content of latent spaces, keeping only the most essential features. Combined with the robustness framework, it proposes F-STUDENT, a distilled version of robust models that compresses the network while preserving its ability to withstand adversarial attacks. This approach outperforms standard pruning methods by leveraging multi-step distillation and information bottleneck regularization. Overall, this PhD contributes to closing the gap between the theoretical progress of modern machine learning and the practical requirements of deploying AI in safety-critical environments. By addressing explainability, robustness, and frugality together, it offers a comprehensive framework for developing reliable machine learning systems that can be trusted in real-world high-stakes applications
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Shinn, Tong-Wook. "Combining Shortest Paths, Bottleneck Paths and Matrix Multiplication." Thesis, University of Canterbury. Computer Science and Software Engineering, 2014. http://hdl.handle.net/10092/9740.
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We provide a formal mathematical definition of the Shortest Paths for All Flows (SP-AF) problem and provide many efficient algorithms. The SP-AF problem combines the well known Shortest Paths (SP) and Bottleneck Paths (BP) problems, and can be solved by utilising matrix multiplication. Thus in our research of the SP-AF problem, we also make a series of contributions to the underlying topics of the SP problem, the BP problem, and matrix multiplication.
For the topic of matrix multiplication we show that on an n-by-n two dimensional (2D) square mesh array, two n-by-n matrices can be multiplied in exactly 1.5n ‒ 1 communication steps. This halves the number of communication steps required by the well known Cannon’s algorithm that runs
on the same sized mesh array.
We provide two contributions for the SP problem. Firstly, we enhance the breakthrough algorithm by Alon, Galil and Margalit (AGM), which was the first algorithm to achieve a deeply sub-cubic time bound for solving the All Pairs Shortest Paths (APSP) problem on dense directed graphs. Our enhancement allows the algorithm by AGM to remain sub-cubic for larger upper bounds on integer edge costs. Secondly, we show that for graphs with n vertices, the APSP problem can be solved in exactly 3n ‒ 2 communication steps on an n-by-n 2D square mesh array. This improves on the previous result of 3.5n communication steps achieved by Takaoka and Umehara.
For the BP problem, we show that we can compute the bottleneck of the entire graph without solving the All Pairs Bottleneck Paths (APBP) problem, resulting in a much more efficient time bound.
Finally we define an algebraic structure called the distance/flow semi-ring to formally introduce the SP-AF problem, and we provide many algorithms for solving the Single Source SP-AF (SSSP-AF) problem and the All Pairs SP-AF (APSP-AF) problem. For the APSP-AF problem, algebraic algorithms are given that utilise faster matrix multiplication over a ring.
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Chen, Zhenyu. "Discrete-time queueing model for responsive network traffic and bottleneck queues." Thesis, Loughborough University, 2016. https://dspace.lboro.ac.uk/2134/21314.
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The Internet has been more and more intensively used in recent years. Although network infrastructure has been regularly upgraded, and the ability to manage heavy traffic greatly increased, especially on the core networks, congestion never ceases to appear, as the amount of traffic that flow on the Internet seems to be increasing at an even faster rate. Thus, congestion control mechanisms play a vital role in the functioning of the Internet. Active Queue Management (AQM) is a popular type of congestion control mechanism that is implemented on gateways (most notably routers), which can predict and avoid the congestion before it happens. When properly configured, AQMs can effectively reduce the congestion, and alleviate some of the problems such as global synchronisation and unfairness to bursty traffic. However, there are still many problems regarding AQMs. Most of the AQM schemes are quite sensitive to their parameters setting, and these parameters may be heavily dependent on the network traffic profile, which the administrator may not have intensive knowledge of, and is likely to change over time. When poorly configured, many AQMs perform no better than the basic drop-tail queue. There is currently no effective method to compare the performance of these AQM algorithms, caused by the parameter configuration problem. In this research, the aim is to propose a new analytical model, which mainly uses discrete-time queueing theory. A novel transient modification to the conventional equilibrium-based method is proposed, and it is utilised to further develop a dynamic interactive model of responsive traffic and bottleneck queues. Using step-by-step analysis, it represents the bursty traffic and oscillating queue length behaviour in practical network more accurately. It also provides an effective way of predicting the behaviour of a TCP-AQM system, allowing easier parameter optimisation for AQM schemes. Numerical solution using MATLAB and software simulation using NS-2 are used to extensively validate the proposed models, theories and conclusions.
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Tůmová, Romana. "Implementace technik lean managementu na základě analýzy úzkých míst ve vybrané společnosti." Master's thesis, Vysoká škola ekonomická v Praze, 2015. http://www.nusl.cz/ntk/nusl-206274.
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The aim of thesis is implemention the chosen techniques of lean management in the company named European Trailer Systems Ltd. based on the identification of bottlenecks. The theoretical part provides basic definitions of bottleneck, Theory of Constraints, Lean management and selected methods of lean management. The practical part begins with the company's European Trailer Systems s.r.o characteristic while describe the current situation. Furthermore, the practical part will focus on the identification of bottlenecks that occur in company European Trailer Systems Ltd. in the production process of sliding roofs, will be followed by a proposal to eliminate found bottlenecks with using methods of lean management and possibly their implementation.
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Moldoveanu, Matei. "In-Network Learning : Distributed Training and Inference in Communication Networks." Electronic Thesis or Diss., Université Gustave Eiffel, 2023. http://www.theses.fr/2023UEFL2003.
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Nous étudions le problème de l'apprentissage statistique distribué. Plus précisément, nous considérons le cadre d'apprentissage distribué et d'inférence. Dans le scénario considéré, plusieurs nœuds doivent travailler ensemble pour prédire une certaine quantité d'intérêt/d'événement au niveau d'un nœud central. Certains nœuds observent les données liées à la quantité cible, tandis que d'autres ne le font pas ; cependant, les nœuds qui n'ont pas accès aux données forment un lien entre le nœud central et les nœuds qui observent les données. Nous considérons le cas où un graphe orienté acyclique peut modéliser un tel réseau. Nous étudions comment on peut entraîner un réseau aussi complexe de manière distribuée, c'est-à-dire sans échange de données brutes, pour le cas où chaque nœud est équipé d'un réseau de neurones pour traiter les données. Inspirés par le fameux problème de goulot d'étranglement de l'information, nous utilisons d'abord la théorie de la distorsion du débit pour dériver un compromis réalisable entre les performances du réseau sous perte logarithmique et le débit des messages transmis entre les nœuds. Ensuite, en utilisant le compromis obtenu, nous montrons comment on peut dériver une fonction de perte qui peut entraîner conjointement les réseaux de neurones aux nœuds de manière distribuée. Nous étudions également le problème d'ordonnancement et d'allocation de puissance pour le modèle proposé pour les topologies de réseau en étoile, c'est-à-dire dans lequel les nœuds d'observation des données sont connectés directement au nœud central faisant la prédiction. En raison de la nature distribuée des données et de l'absence d'a priori connu, aucun nœud ne peut fournir une image définitive du système et décider correctement de l'allocation des ressources. Pour surmonter ce problème, le professeur Abdellatif Zaidi a breveté une solution dans laquelle 1. Chaque appareil mesure sa propre évaluation locale de la pertinence des données qu'il détient pour la tâche d'inférence en cours et la transmet au nœud de décision. 2. Cet appareil envoie également simultanément les valeurs d'activation de sortie au nœud de décision. 3. Le nœud de décision combine toutes les informations reçues (valeurs d'activation des différents appareils ainsi que leurs évaluations locales individuelles) et forme ensuite sa propre évaluation (globale) de la pertinence de l'observation de chaque appareil. 4. Les nœuds centraux ont utilisé les évaluations obtenues pour planifier l'allocation de puissance. Dans cette thèse, nous nous appuyons sur le brevet en présentant une méthode de calcul des évaluations locales et globales et en proposant de nouveaux algorithmes d'ordonnancement et d'allocation de puissance<br>We study the problem of distributed statistical learning. More specifically, we consider the distributed training and inference setting. In the considered scenario, multiple nodes need to work together to predict some quantity of interest/event at a central node. Some nodes observe data related to the target quantity, while others do not; however, the nodes that do not have access to data form a link between the central node and the nodes that observe data. We consider the case in which a directed acyclic graph can model such a network. We study how one can train such a complex network in a distributed manner, i.e., without the exchange of raw data, for the case in which each node is equipped with a neural network to process the data. Inspired by the famous information bottleneck problem, we first use rate-distortion theory to derive an achievable trade-off between the network's performance under logarithmic loss and the rate of the messages passed between the nodes. Then, using the obtained trade-off, we showcase how one can derive a loss function that can jointly train the neural networks at the nodes in a distributed manner. We also study the problem of scheduling and power allocation for the proposed model for the star network topologies, i.e., in which the data observing nodes are connected directly to the central node making the prediction. Due to the distributed nature of the data and the lack of a known prior, no node can provide a definitive picture of the system and correctly decide the allocation of the resources. To overcome this issue, Prof. Abdellatif Zaidi patented a solution in which 1. Each device measures its own local assessment of how relevant is the data it holds for the inference task at hand and transmits it to the decision node. 2. That device also simultaneously sends the output activation values to the decision node. 3. The decision node combines all received information (activation values from the various devices as well as their individual local assessments) and then forms its own (global) assessment of how relevant each device's observation is. 4. The central nodes used the obtained assessments for scheduling for power allocation. In this thesis, we build upon the patent by presenting a method for computing the local and global assessments and proposing new scheduling and power allocation algorithms
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Ogle, Curtis Taylor. "Theoretical Investigation of Biological Networks Coupled via Bottlenecks in Enzymatic Processing." Diss., Virginia Tech, 2016. http://hdl.handle.net/10919/71319.
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Cell biology is a branch of science with a seemingly infinite abundance of interesting phenomena which are essential to our understanding of life and which may potentially drive the development of technology that improves our lives. Among the open ended questions within the field, an understanding of how gene networks are affected by limited cellular components is both broad and rich with interest. Common to all cellular systems are enzymes which perform many tasks within cells without which organisms could not remain healthy. Here are presented several explorations of enzymatic processing as well as a tool constructed for this purpose. More specifically, these works consider the effect of coupling of gene networks via competition for enzymes found within the cell. It is shown that a limitation on the number of available enzymes permits the formation of bottlenecks which drastically affect molecular dynamics within cells. These effects potentially afford cell behaviors that in part explain the impressive robustness of life to constantly fluctuating environments.<br>Ph. D.
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Krause, Thomas. "Dynamische Straßenbenutzungsgebühren zur Reduzierung von Staus /." Frankfurt am Main [u.a.] : Lang, 2003. http://www.gbv.de/dms/zbw/36772944X.pdf.
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Wojahn, Oliver W. "Airline networks /." Frankfurt am Main [u.a.] : Lang, 2001. http://www.gbv.de/dms/goettingen/330622722.pdf.
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Králik, Miroslav. "Improvement of digital support process using ITIL best practices, Kanban and TOC in multicultural environment." Master's thesis, Vysoká škola ekonomická v Praze, 2013. http://www.nusl.cz/ntk/nusl-193644.
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Many companies today have to deal with business processes optimization, ongoing removal of system obstacles and identifying any bottlenecks laying on the way which are preventing us to reach our goals. I would like to show how we have dealt with similar problems in our case applied in the department of web application maintenance. In the first chapter I will introduce the basic information about the history, environment the company operate in and maintenance activities which are part of the process. Following with description all of the system obstacles and bottlenecks identified in the process and possible solutions or improvements for their elimination. In the last chapter I will present the achieved results after my executing of the proposed improvements and if the expectations have been met or not and what positive or negative influence it has brought.
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Lagreca, Fabio Rezende. "Aplicação da Teoria das Restrições (TDR) na gestão da cadeia produtiva de uma indústria farmacêutica." reponame:Repositório Institucional da FIOCRUZ, 2012. http://beta.arca.fiocruz.br/handle/icict/14549.
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Previous issue date: 2012<br>Fundação Oswaldo Cruz. Instituto de Tecnologia em Fármacos/Farmanguinhos. Rio de Janeiro, RJ, Brasil.<br>A busca por técnicas de gestão que possibilitem um melhor aproveitamento da capacidade instalada de plantas produtivas é o desafio constante de todos os gestores. A utilização da Teoria das Restrições (TDR) como ferramenta de gestão no ambiente produtivo deste estudo possibilitou evidenciar o uso racional dos equipamentos do parque fabril a partir da identificação dos gargalos dos processos produtivos dos produtos mapeados. O dimensionamento dos pulmões de proteção da restrição e de espaço demonstrou como é possível manter o fluxo constante de produção sem a necessidade de elevados estoques em processo entre os centros de trabalho que compõem os sistemas produtivos. A análise da capacidade global do sistema pode evidenciar os centros de trabalho com restrição de capacidade frente à demanda posta.<br>The quest for management techniques that enable a better utilization of productive capacity of plants is the constant challenge for all managers. Using the Theory of Constraints (TOC) as a management tool in the production environment of this study highlight the possible rational use of the equipment of the industrial park from the identification of “bottlenecks” of the production processes of products mapped. The sizing of the lungs to protect the space restriction and demonstrated
how you can keep a steady flow of production without the need for high in-process inventories between the work centers that compose the productive systems. The analysis of the overall capacity of the system can highlight the work centers capacity constraint put forward the demand.
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Ballout, Ali. "Apprentissage actif pour la découverte d'axiomes." Electronic Thesis or Diss., Université Côte d'Azur, 2024. http://www.theses.fr/2024COAZ4026.
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Cette thèse aborde le défi de l'évaluation des formules logiques candidates, avec un accent particulier sur les axiomes, en combinant de manière synergique l'apprentissage automatique et le raisonnement symbolique. Cette approche innovante facilite la découverte automatique d'axiomes, principalement dans la phase d'évaluation des axiomes candidats générés. La recherche vise à résoudre le problème de la validation efficace et précise de ces candidats dans le contexte plus large de l'acquisition de connaissances sur le Web sémantique.Reconnaissant l'importance des heuristiques de génération existantes pour les axiomes candidats, cette recherche se concentre sur l'avancement de la phase d'évaluation de ces candidats. Notre approche consiste à utiliser ces candidats basés sur des heuristiques, puis à évaluer leur compatibilité et leur cohérence avec les bases de connaissances existantes. Le processus d'évaluation, qui nécessite généralement beaucoup de calculs, est révolutionné par le développement d'un modèle prédictif qui évalue efficacement l'adéquation de ces axiomes en tant que substitut du raisonnement traditionnel. Ce modèle innovant réduit considérablement les exigences en matière de calcul, en utilisant le raisonnement comme un "oracle" occasionnel pour classer les axiomes complexes lorsque cela est nécessaire.L'apprentissage actif joue un rôle essentiel dans ce cadre. Il permet à l'algorithme d'apprentissage automatique de sélectionner des données spécifiques pour l'apprentissage, améliorant ainsi son efficacité et sa précision avec un minimum de données étiquetées. La thèse démontre cette approche dans le contexte du Web sémantique, où le raisonneur joue le rôle d'"oracle" et où les nouveaux axiomes potentiels représentent des données non étiquetées.Cette recherche contribue de manière significative aux domaines du raisonnement automatique, du traitement du langage naturel et au-delà, en ouvrant de nouvelles possibilités dans des domaines tels que la bio-informatique et la preuve automatique de théorèmes. En mariant efficacement l'apprentissage automatique et le raisonnement symbolique, ces travaux ouvrent la voie à des processus de découverte de connaissances plus sophistiqués et autonomes, annonçant un changement de paradigme dans la manière dont nous abordons et exploitons la vaste étendue de données sur le web sémantique<br>This thesis addresses the challenge of evaluating candidate logical formulas, with a specific focus on axioms, by synergistically combining machine learning with symbolic reasoning. This innovative approach facilitates the automatic discovery of axioms, primarily in the evaluation phase of generated candidate axioms. The research aims to solve the issue of efficiently and accurately validating these candidates in the broader context of knowledge acquisition on the semantic Web.Recognizing the importance of existing generation heuristics for candidate axioms, this research focuses on advancing the evaluation phase of these candidates. Our approach involves utilizing these heuristic-based candidates and then evaluating their compatibility and consistency with existing knowledge bases. The evaluation process, which is typically computationally intensive, is revolutionized by developing a predictive model that effectively assesses the suitability of these axioms as a surrogate for traditional reasoning. This innovative model significantly reduces computational demands, employing reasoning as an occasional "oracle" to classify complex axioms where necessary.Active learning plays a pivotal role in this framework. It allows the machine learning algorithm to select specific data for learning, thereby improving its efficiency and accuracy with minimal labeled data. The thesis demonstrates this approach in the context of the semantic Web, where the reasoner acts as the "oracle," and the potential new axioms represent unlabeled data.This research contributes significantly to the fields of automated reasoning, natural language processing, and beyond, opening up new possibilities in areas like bioinformatics and automated theorem proving. By effectively marrying machine learning with symbolic reasoning, this work paves the way for more sophisticated and autonomous knowledge discovery processes, heralding a paradigm shift in how we approach and leverage the vast expanse of data on the semantic Web
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Guevara, Sánchez Edwar Paul, and Guardamino Rosa Albina Zegarra. "Aplicación de un modelo integrado de gestión de la producción para mejorar la productividad de la línea de fabricación de llaves de cerradura." Bachelor's thesis, Universidad Ricardo Palma, 2015. http://cybertesis.urp.edu.pe/handle/urp/1294.
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La investigación está orientada al diseño e implementación de un Modelo Integrado de Gestión de la Producción para la fabricación de llaves de cerradura, este modelo integra la teoría de restricciones para resolver los cuellos de botella y utiliza algunas herramientas de Lean Manufacturing para eliminar los desperdicios que se generan en los procesos que generan los cuellos de botella. El objetivo de la aplicación del modelo es el mejorar la productividad de la línea de fabricación de llaves de cerradura, la reducción de costos mediante la mejora de la eficiencia de sus procesos que permitan a la empresa ser más competitiva en el mercado.
The research is focused on the design and implementation of an integrated management of production for the manufacture of keys lock model, this model integrates the theory of constraints to solve bottlenecks and used some tools of lean manufacturing to eliminate waste that is generated in the processes that create bottlenecks. The purpose of applying the model is to improve the productivity of the manufacturing line lock keys, reducing costs by improving the efficiency of their processes that enable the company to be more competitive in the market.
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Teng, Sin Yong. "Intelligent Energy-Savings and Process Improvement Strategies in Energy-Intensive Industries." Doctoral thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2020. http://www.nusl.cz/ntk/nusl-433427.
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S tím, jak se neustále vyvíjejí nové technologie pro energeticky náročná průmyslová odvětví, stávající zařízení postupně zaostávají v efektivitě a produktivitě. Tvrdá konkurence na trhu a legislativa v oblasti životního prostředí nutí tato tradiční zařízení k ukončení provozu a k odstavení. Zlepšování procesu a projekty modernizace jsou zásadní v udržování provozních výkonů těchto zařízení. Současné přístupy pro zlepšování procesů jsou hlavně: integrace procesů, optimalizace procesů a intenzifikace procesů. Obecně se v těchto oblastech využívá matematické optimalizace, zkušeností řešitele a provozní heuristiky. Tyto přístupy slouží jako základ pro zlepšování procesů. Avšak, jejich výkon lze dále zlepšit pomocí moderní výpočtové inteligence. Účelem této práce je tudíž aplikace pokročilých technik umělé inteligence a strojového učení za účelem zlepšování procesů v energeticky náročných průmyslových procesech. V této práci je využit přístup, který řeší tento problém simulací průmyslových systémů a přispívá následujícím: (i)Aplikace techniky strojového učení, která zahrnuje jednorázové učení a neuro-evoluci pro modelování a optimalizaci jednotlivých jednotek na základě dat. (ii) Aplikace redukce dimenze (např. Analýza hlavních komponent, autoendkodér) pro vícekriteriální optimalizaci procesu s více jednotkami. (iii) Návrh nového nástroje pro analýzu problematických částí systému za účelem jejich odstranění (bottleneck tree analysis – BOTA). Bylo také navrženo rozšíření nástroje, které umožňuje řešit vícerozměrné problémy pomocí přístupu založeného na datech. (iv) Prokázání účinnosti simulací Monte-Carlo, neuronové sítě a rozhodovacích stromů pro rozhodování při integraci nové technologie procesu do stávajících procesů. (v) Porovnání techniky HTM (Hierarchical Temporal Memory) a duální optimalizace s několika prediktivními nástroji pro podporu managementu provozu v reálném čase. (vi) Implementace umělé neuronové sítě v rámci rozhraní pro konvenční procesní graf (P-graf). (vii) Zdůraznění budoucnosti umělé inteligence a procesního inženýrství v biosystémech prostřednictvím komerčně založeného paradigmatu multi-omics.
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Cheng, Chih-Jen, and 鄭智仁. "Investigating the Impact of Products Mixed on Bottleneck Load by the Theory of Constraints." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/40115590983573392801.
Full textAbstract:
碩士<br>元智大學<br>工業工程與管理學系<br>95<br>The research is based on the theory of constraints and procedures of group technology to simplify the products mixed. Capacity planning is applied considering the factor of cycle time to display the stacking condition of bottleneck resources by Visual Basic algorithms, and then the impact of the changes of products mixed can be found out for optimal adjustment of products mixed.
The objective of the research is to help PCB (Printed Circuit Board) factories decide products mixed in the shortest time during production planning stage for optimal capacity adjustment and preparation, and to avoid any changes of bottleneck resources made during the execution stage caused by inappropriate planning which can affect the output of production systems.
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Calletti, Riccardo. "The Attentional Bottleneck: Constraints, Neural Correlates and Reward-Dependent Plasticity." Doctoral thesis, 2015. http://hdl.handle.net/11562/915588.
Full textAbstract:
Attraverso questa serie di esperimenti, abbiamo presentato i principali fattori per la selezione di target e definito le caratteristiche che consentono a un target di vincere la competizione per le risorse attenzionali. Abbiamo poi rivelato i correlati elettrofisiologici (ERP) del bottleneck attenzionale. In seguito abbiamo provocato cambiamenti durevoli, indotti da ricompensa, nella priorità attenzionale di specifiche posizioni spaziali e rivelato un'interessante influenza di caratteristiche individuali nella modulazione della performance mediata dalla ricompensa.
Inizialmente abbiamo rilevato un'influenza generale di posizione del target nell’array, con migliori prestazioni per le posizioni più laterali, risultando in un’anisotropia del campo visivo. Abbiamo poi osservato un effetto di posizione relativa dei target, ovvero un significativo vantaggio nella performance quando i target sono presentati nei due emicampi. Infine abbiamo dimostrato che la relativa forza competitiva di due posizioni target in una coppia è fortemente predetta sulla base della performance misurata nella condizione di target singolo per le date posizioni.
Nel secondo esperimento, abbiamo misurato i potenziali evento-correlati (ERP) al fine di svelare i correlati neurali del bottleneck attenzionale. L’N2pc non era modulata dal numero di target presentati, ma solo dal numero di target consciamente identificati, nonché dalla loro relativa posizione spaziale. Inoltre abbiamo dimostrato che la migliore performance a livello comportamentale (corrispondente al riportare entrambi i target, rispetto a solo uno, nella condizione di doppio target) potrebbe essere spiegata da un precoce impegno attenzionale nella data prova. Infine abbiamo rivelato una suggestiva modulazione dell'ampiezza dell’N2pc a seconda del numero di target individuati.
Abbiamo poi studiato l'influenza di un protocollo di apprendimento mediato dalla ricompensa monetaria sulla priorità attenzionale delle posizioni nello spazio. Attraverso l'utilizzo di un protocollo di training basato su di una ricompensa, siamo stati in grado di produrre cambiamenti duraturi nelle mappe di priorità, che sono responsabili di dirigere l'attenzione spaziale e di mediare la selezione di target. In particolare, posizioni spaziali associate ad un risultato positivo durante il training hanno acquisito una priorità maggiore rispetto alle posizioni spaziali associate ad un risultato meno positivo. La variazione descritta nella priorità attenzionale di posizioni specifiche è risultata evidente solo in presenza di una competizione tra target. È importante sottolineare che i cambiamenti osservati in termini di prestazioni sono stati misurati dopo quattro giorni dalla fase di training, probabilmente riflettendo cambiamenti plastici durevoli nelle mappe di priorità spaziali.
Infine, abbiamo indagato se l'entità del bias attenzionale derivato dalla ricompensa potesse dipendere da specifici attributi individuali e tratti di personalità. Un'interessante influenza di alcuni tratti è apparsa influenzare le prestazioni durante la fase di training. Specificamente, differenze di prestazioni (in termini di precisione e di tempi di reazione) nel riportare un target presentato in una posizione altamente ricompensata e un target presentato in una posizione scarsamente ricompensata erano predette da fattori riguardanti il profilo dei soggetti. In particolare, abbiamo identificato due principali tratti individuali aventi un’influenza sulle prestazioni, ovvero il sesso dei soggetti e il punteggio ottenuto nella sottoscala Drive della scala Behavioral Activation System.
Complessivamente, questa ricerca offre risultati interessanti per quanto riguarda le basi comportamentali e neurali del bottleneck attenzionale. Inoltre, aggiunge nuovi critici elementi di prova nel campo dell'apprendimento attenzionale mediato dalla ricompensa, dimostrando che le mappe di priorità spaziali possono andare incontro a durevoli cambiamenti plastici.<br>Through this series of experiments, we unveiled major determinants in multiple target selection and defined which critical features allow a target to win competition for attentional resources. We then revealed the electrophysiological correlates (ERPs) of the attentional bottleneck. Moreover, we induced durable reward-based changes in the attentional priority of specific spatial locations, resulting in an imbalanced probability to identify a target in one or the other of two critical spatial locations in a pair, and revealed an interesting influence of individual traits affecting performance during the training session.
In the first experiment, a series of critical elements were found to influence competition for attentional resources and allow a target to enter the attentional bottleneck. Firstly, an influence of target position within the stimulus array was revealed, with the best performance for the most lateralized positions, resulting in a visual anisotropy. We then observed an effect of targets’ relative position, namely a significant advantage when the targets were displayed across hemifields. Eventually, we demonstrated that the relative competitive strength of two target locations in a pair can be predicted on the basis of performance measured in the single target condition for the given locations.
In the second experiment, we measured the Event-Related Potentials (ERPs) in order to directly unveil neural correlates of the attentional bottleneck. Interestingly, a number of critical factors appeared to affect the occurrence and amplitude of the N2pc component. Specifically, the N2pc was not modulated by the number of presented targets, but only by the number of consciously identified targets, as well as by their relative spatial position. Furthermore, we demonstrated that the better performance at the behavioral level (corresponding to correctly reporting both targets vs. one in the double target condition) could be explained by an earlier attentional engagement in the given trial. Finally, we revealed a suggestive modulation of the amplitude of the N2pc waveform depending on the number of identified targets.
We then investigated the influence of a reward-based learning protocol on the attentional priority of locations in space. Specifically, through the use of a reward-based training protocol, we were able to produce enduring changes in priority maps that are responsible for directing spatial attention and for arbitrating target selection. In particular, spatial locations associated with an overall more positive outcome during training were prioritized with respect to spatial locations associated with an overall less positive outcome. Importantly, the observed changes in performance were measured after a four-day delay from the training phase, likely reflecting durable plastic changes in spatial priority maps.
Finally, we investigated whether the entity of the acquired reward-based attentional bias could depend on specific individual attributes and personality traits. An interesting influence of individual traits appeared to affect performance during training. Specifically, differences in performance (in terms of accuracy and of reaction times) between reporting a target displayed at an 80Hh position vs. a target displayed at a 20Lh position appeared to be predicted by a series of factors concerning participant profile. In particular, we identified two main individual traits having an influence on performance, namely gender and individual scores at the Drive subscale of the Behavioral Activation System scale.
Altogether, this research contributes interesting results with respect to the behavioral and neural basis of the attentional bottleneck that characterizes spatial directed attention. Moreover, it adds critical new evidence in the field of reward-mediated attentional learning, demonstrating that spatial priority maps can encounter durable plastic changes.
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Khan, Asim. "An Integrated Optimization Tool in Applications of Mining using A Discrete Rate Stochastic Model." 2011. http://hdl.handle.net/10222/14378.
Full textAbstract:
The simulation as a stand alone optimization tool of a complex system such as a vertical integrated mining operation, significantly over simplifies the actual picture of the system processes involved resulting in an unaccountable effort and resources being spent on optimizing Non Value Added (NA) processes.
This study purposed to develop a discrete stochastic simulation-optimization model to accurately capture the dynamics of the system and to provide a structured way to optimize the Value Added (VA) processes.
The mine operation model to be simulated for this study is designed as a hybrid level throughput model to identify the VA processes in a mining operation. This study also allows a better understanding of the impact of variation on the likelihood of achieving any given overall result.
The proposed discrete stochastic simulation- optimization model provides the ability for a process manager to gain realistic understanding of what a process can do if some factors constraining the process were to be optimized i.e. to conduct what-if analysis. Another benefit of this approached technique is to be able to estimate dependable and reasonable returns on a large optimization related expenditure.
The inputs into the model are the capability of the processes which are entered using various variables depending on how much information is available; simple inputs for least amount of information to detailed inputs for well known process to combinational inputs for somewhere in between. The process bottlenecks are identified and measured using the outputs of the model which include production output, severity of constraints, capacity constraints and cumulative bottleneck plots. Once a base case has been identified and documented then the inputs can be modified to represent the business initiatives and the outputs can be compared to the base case to evaluate the true value of the initiative.
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Zhan, Zhuang-Zh, and 詹莊智. "Application of Moving Bottlenecks Theory for Slow-Vehicle Impact on Freeway Traffic Characteristics." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/fqxau2.
Full textAbstract:
碩士<br>中原大學<br>土木工程研究所<br>107<br>Freeway is the major roadway for providing mobility. To be effective as a corridor, it is important to use lane capacity efficiently. When there are aberrant driving behavior and heterogeneity in traffic flow, the efficiency of road performance tends to drop abruptly. Although aberrant driving behavior is not regularly seen all the time in traffic flow, their influence to the efficiency of traffic flow can’t be ignored: travel time will increase while each time aberrant driving behavior appear. In previous research, several researchers had studied moving bottlenecks of slow vehicles in the traffic flow for a while. Most of the works were based on simulation models according to traffic theories. In contrast to the theoretical development, the empirical studies had fallen far behind due to the difficulties of data collecting.
This study aimed to explore the impact by slow vehicles based on the moving bottlenecks theory. The characteristics of slow vehicles were observed, identified and categorized on the survey section of Sun Yat-Sen Freeway. The video images from CCTV were used to build the methodology in measuring and analyzing slow vehicles as well as the moving bottleneck phenomenon. Followed by examining the characteristics of freeway flow for adjacent lanes. The issue of “wasteful” capacity was discussed thereafter.
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Tai, Cheng-Chung, and 戴正忠. "Application of TOC and TRIZ Theory Approach to Solve the Probiem of Production Bottlenecks." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/68902079815381389227.
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碩士<br>國立高雄應用科技大學<br>工業工程與管理系碩士在職專班<br>104<br>In recent years, TOC theory of constraints by the use range of more and more for a wide. From the early manufacturing. Until the service sector now. For cost-effective enterprise has a great contribution.The TRIZ technology for innovation, mainly to solve engineering problems. In recent years, one after another to solve management problems rule. But after all, still rare. Because TRIZ innovation theory is by 39 parameters export 40 to solve engineering problems based law.
In this study, after the TOC find bottlenecks. Cause analysis using the Figure due to a bottleneck analysis.After analyzing the causes of bottlenecks. The reason is divided into engineering problems and management issues. Engineering problems with 39 parameters TRIZ technology for innovation to solve the problem to find relevant laws. Coupled to elect suitable for solving engineering problems law in this study. However, management problems, resembling TRIZ principles.The cause of the problem as a management parameter. Then follow the relevant literature sorted out for solutions to problems. To solve the management problems.
In this study, a semiconductor packaging and testing plant in the Case.Application of the above method to solve the problem. The results show: To solve the bottleneck problem of the production system to enhance overall output. Enhance the overall output can be reduced manpower needs. For the better deployment of personnel deployment.
Keywords:Theory of Constraints, TRIZ technology for innovation, Improving production.
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Alves, Tiago Rafael de Jesus. "Teoria dos Constrangimentos – Identificação dos estrangulamentos aplicada na simulação por eventos discretos duma linha de produção." Master's thesis, 2018. http://hdl.handle.net/10316/86001.
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Dissertação de Mestrado em Engenharia e Gestão Industrial apresentada à Faculdade de Ciências e Tecnologia<br>O desempenho das linhas de produção de uma unidade fabril é determinante no sucesso alcançado pelas empresas. Para tal, qualquer processo de produção que vise o sucesso está diariamente sujeito a melhorias de forma a aumentar a eficiência e a diminuir os desperdícios, ferramentas de simulação como o software SIMUL8 têm visto a sua importância reforçada.O projecto desenvolvido consiste na análise e melhoria das operações realizadas na linha de produção de um dos tipos de rolha produzidos na Amorim Cork, a Twin Top. Com as dificuldades que a empresa apresenta em conseguir identificar os estrangulamentos nesta linha de produção, surge a necessidade de recorrer ao software de simulação, de forma a facilitar a visualização dos estrangulamentos do sistema. Assim sendo e recorrendo ao software SIMUL8, foi desenvolvido um modelo de simulação da linha de produção em questão. O modelo permite assim quantificar estrangulamentos previamente identificados.O objectivo deste trabalho passa por numa primeira etapa analisar algumas teorias recentes ligadas à primeira etapa da Teoria dos Constrangimentos – Identificação do estrangulamento, escolhendo a mais indicada, para depois fazer a sua aplicação no modelo de simulação criado para analisar a linha de produção Twin Top da Amorim Cork, identificando correctamente os bottlenecks do sistema.Os resultados obtidos, revelaram-se importantes ferramentas de análise e apoio à decisão para os processos de gestão de um sistema de produção, cada vez mais importante no dias actuais.<br>The performance of the production lines of a manufacturing unit is decisive in the success achieved by the companies. To this end, any production process aimed at success is daily subject to improvements in order to increase efficiency and decrease waste. Simulation tools such as SIMUL8 software have seen their importance reinforced.The project developed consists of the analysis and improvement of the operations carried out in the production line of one of the types of cork produced in Amorim Cork, the Twin Top. With the difficulties that the company presents in being able to identify the bottlenecks in this production line, it is necessary to use the simulation software, in order to facilitate the visualization of system bottlenecks. Thus, using a SIMUL8 software, a simulation model of the production line in question was developed. The model allows quantification of previously identified bottlenecks.The objective of this document is to analyze some recent theories related to the first stage of the Theory of Constraints - Identification of the bottleneck, choosing the most appropriate one, and then applying it to the simulation model created to analyze the production line, identifying the bottlenecks of the system.The obtained results proved to be important analysis tools and decision support for the management processes of a production system, increasingly each day the importance of this subject. After all, if we don't improve continuously our concorrents will reach us, and then leave us behind.