Multi-stage scheduling problems with precedence constraints

Abstract not available

Multi-level, Multi-stage and Stochastic Optimization Models for Energy Conservation in Buildings for Federal, State and Local Agencies

Energy Conservation Measure (ECM) project selection is made difficult given real-world constraints, limited resources to implement savings retrofits, various suppliers in the market and project financing alternatives. Many of these energy efficient retrofit projects should be viewed as a series of investments with annual returns for these traditionally risk-averse agencies. Given a list of ECMs available, federal, state and local agencies must determine how to implement projects at lowest costs. The most common methods of implementation planning are suboptimal relative to cost. Federal, state and local agencies can obtain greater returns on their energy conservation investment over traditional methods, regardless of the implementing organization. This dissertation outlines several approaches to improve the traditional energy conservations models. Any public buildings in regions with similar energy conservation goals in the United States or internationally can also benefit greatly from this research. Additionally, many private owners of buildings are under mandates to conserve energy e.g., Local Law 85 of the New York City Energy Conservation Code requires any building, public or private, to meet the most current energy code for any alteration or renovation. Thus, both public and private stakeholders can benefit from this research. The research in this dissertation advances and presents models that decision-makers can use to optimize the selection of ECM projects with respect to the total cost of implementation. A practical application of a two-level mathematical program with equilibrium constraints (MPEC) improves the current best practice for agencies concerned with making the most cost-effective selection leveraging energy services companies or utilities. The two-level model maximizes savings to the agency and profit to the energy services companies (Chapter 2). An additional model presented leverages a single congressional appropriation to implement ECM projects (Chapter 3). Returns from implemented ECM projects are used to fund additional ECM projects. In these cases, fluctuations in energy costs and uncertainty in the estimated savings severely influence ECM project selection and the amount of the appropriation requested. A risk aversion method proposed imposes a minimum on the number of “of projects completed in each stage. A comparative method using Conditional Value at Risk is analyzed. Time consistency was addressed in this chapter. This work demonstrates how a risk-based, stochastic, multi-stage model with binary decision variables at each stage provides a much more accurate estimate for planning than the agency’s traditional approach and deterministic models. Finally, in Chapter 4, a rolling-horizon model allows for subadditivity and superadditivity of the energy savings to simulate interactive effects between ECM projects. The approach makes use of inequalities (McCormick, 1976) to re-express constraints that involve the product of binary variables with an exact linearization (related to the convex hull of those constraints). This model additionally shows the benefits of learning between stages while remaining consistent with the single congressional appropriations framework.

Empregabilidade e procura do ensino superior: o caso da UA

O principal objectivo deste trabalho consistiu em avaliar as motivações preponderantes dos cursos de 1º ciclo dos alunos da Universidade de Aveiro. Em particular, tentamos perceber se o maior factor seria a taxa de empregabilidade do curso. Para o efeito foram analisados dados relativos a três fontes de informação fundamentais: os dados relativos aos concursos nacionais de acesso disponibilizados pela Direcção Geral do Ensino Superior; dados relativos aos perfil dos estudantes de 1º ciclo da UA no ano lectivo de 2011/12 e, finalmente, dados relativos ao perfil de empregabilidade dos diplomados da UA de 2009/10 a 2011/12. Dos resultados obtidos, concluiu-se que o factor empregabilidade não é o factor com maior peso na hora de um jovem escolher um curso superior da UA. Ainda assim, e apesar de termos verificado que motivos como a vocação e a realização pessoal, são de facto factores mais relevantes, não é claro que exista um factor de motivação claramente preponderante, o que aponta para que este processo de escolha seja multi-dimensional e não apenas um acto de mera racionalidade material.

Brain tumor and brain endothelial cells' response to ionizing radiation and phytochemical treatments

Le glioblastome multiforme (GBM) représente la tumeur cérébrale primaire la plus agressive et la plus vascularisée chez l’adulte. La survie médiane après le diagnostic est de moins d’un an en l’absence de traitement. Malheureusement, 90% des patients traités avec de la radiothérapie après la résection chirurgicale d’un GBM développent une récidive tumorale. Récemment, le traitement des GBM avec radiothérapie et témozolomide, un agent reconnu pour ses propriétés antiangiogéniques, a permis de prolonger la survie médiane à 14,6 mois. Des efforts sont déployés pour identifier des substances naturelles capables d’inhiber, de retarder ou de renverser le processus de carcinogenèse. Epigallocatechin-3-gallate (EGCG), un polyphénol retrouvé dans le thé vert, est reconnu pour ses propriétés anticancéreuses et antiangiogéniques. L’EGCG pourrait sensibiliser les cellules tumorales cérébrales et les cellules endothéliales dérivées des tumeurs aux traitements conventionnels. Le chapitre II décrit la première partie de ce projet de doctorat. Nous avons tenté de déterminer si l’EGCG pourrait sensibiliser la réponse des GBM à l’irradiation (IR) et si des marqueurs moléculaires spécifiques sont impliqués. Nous avons documenté que les cellules U-87 étaient relativement radiorésistantes et que Survivin, une protéine inhibitrice de l’apoptose, pourrait être impliquée dans la radiorésistance des GBM. Aussi, nous avons démontré que le pré-traitement des cellules U-87 avec de l’EGCG pourrait annuler l’effet cytoprotecteur d’une surexpression de Survivin et potentialiser l’effet cytoréducteur de l’IR. Au chapitre III, nous avons caractérisé l’impact de l’IR sur la survie de cellules endothéliales microvasculaires cérébrales humaines (HBMEC) et nous avons déterminé si l’EGCG pouvait optimiser cet effet. Bien que les traitements individuels avec l’EGCG et l’IR diminuaient la survie des HBMEC, le traitement combiné diminuait de façon synergique la survie cellulaire. Nous avons documenté que le traitement combiné augmentait la mort cellulaire, plus spécifiquement la nécrose. Au chapitre IV, nous avons investigué l’impact de l’IR sur les fonctions angiogéniques des HBMEC résistantes à l’IR, notamment la prolifération cellulaire, la migration cellulaire en présence de facteurs de croissance dérivés des tumeurs cérébrales, et la capacité de tubulogenèse. La voie de signalisation des Rho a aussi été étudiée en relation avec les propriétés angiogéniques des HBMEC radiorésistantes. Nos données suggèrent que l’IR altère significativement les propriétés angiogéniques des HBMEC. La réponse aux facteurs importants pour la croissance tumorale et l’angiogenèse ainsi que la tubulogenèse sont atténuées dans ces cellules. En conclusion, ce projet de doctorat confirme les propriétés cytoréductrices de l’IR sur les gliomes malins et propose un nouveau mécanisme pour expliquer la radiorésistance des GBM. Ce projet documente pour la première fois l’effet cytotoxique de l’IR sur les HBMEC. Aussi, ce projet reconnaît l’existence de HBMEC radiorésistantes et caractérise leurs fonctions angiogéniques altérées. La combinaison de molécules naturelles anticancéreuses et antiangiogéniques telles que l’EGCG avec de la radiothérapie pourrait améliorer l’effet de l’IR sur les cellules tumorales et sur les cellules endothéliales associées, possiblement en augmentant la mort cellulaire. Cette thèse supporte l’intégration de nutriments avec propriétés anticancéreuses et antiangiogéniques dans le traitement des gliomes malins pour sensibiliser les cellules tumorales et endothéliales aux traitements conventionnels.

Reinforcement Learning Approaches to Power System Scheduling

One major component of power system operation is generation scheduling. The objective of the work is to develop efficient control strategies to the power scheduling problems through Reinforcement Learning approaches. The three important active power scheduling problems are Unit Commitment, Economic Dispatch and Automatic Generation Control. Numerical solution methods proposed for solution of power scheduling are insufficient in handling large and complex systems. Soft Computing methods like Simulated Annealing, Evolutionary Programming etc., are efficient in handling complex cost functions, but find limitation in handling stochastic data existing in a practical system. Also the learning steps are to be repeated for each load demand which increases the computation time.Reinforcement Learning (RL) is a method of learning through interactions with environment. The main advantage of this approach is it does not require a precise mathematical formulation. It can learn either by interacting with the environment or interacting with a simulation model. Several optimization and control problems have been solved through Reinforcement Learning approach. The application of Reinforcement Learning in the field of Power system has been a few. The objective is to introduce and extend Reinforcement Learning approaches for the active power scheduling problems in an implementable manner. The main objectives can be enumerated as:(i) Evolve Reinforcement Learning based solutions to the Unit Commitment Problem.(ii) Find suitable solution strategies through Reinforcement Learning approach for Economic Dispatch. (iii) Extend the Reinforcement Learning solution to Automatic Generation Control with a different perspective. (iv) Check the suitability of the scheduling solutions to one of the existing power systems.First part of the thesis is concerned with the Reinforcement Learning approach to Unit Commitment problem. Unit Commitment Problem is formulated as a multi stage decision process. Q learning solution is developed to obtain the optimwn commitment schedule. Method of state aggregation is used to formulate an efficient solution considering the minimwn up time I down time constraints. The performance of the algorithms are evaluated for different systems and compared with other stochastic methods like Genetic Algorithm.Second stage of the work is concerned with solving Economic Dispatch problem. A simple and straight forward decision making strategy is first proposed in the Learning Automata algorithm. Then to solve the scheduling task of systems with large number of generating units, the problem is formulated as a multi stage decision making task. The solution obtained is extended in order to incorporate the transmission losses in the system. To make the Reinforcement Learning solution more efficient and to handle continuous state space, a fimction approximation strategy is proposed. The performance of the developed algorithms are tested for several standard test cases. Proposed method is compared with other recent methods like Partition Approach Algorithm, Simulated Annealing etc.As the final step of implementing the active power control loops in power system, Automatic Generation Control is also taken into consideration.Reinforcement Learning has already been applied to solve Automatic Generation Control loop. The RL solution is extended to take up the approach of common frequency for all the interconnected areas, more similar to practical systems. Performance of the RL controller is also compared with that of the conventional integral controller.In order to prove the suitability of the proposed methods to practical systems, second plant ofNeyveli Thennal Power Station (NTPS IT) is taken for case study. The perfonnance of the Reinforcement Learning solution is found to be better than the other existing methods, which provide the promising step towards RL based control schemes for practical power industry.Reinforcement Learning is applied to solve the scheduling problems in the power industry and found to give satisfactory perfonnance. Proposed solution provides a scope for getting more profit as the economic schedule is obtained instantaneously. Since Reinforcement Learning method can take the stochastic cost data obtained time to time from a plant, it gives an implementable method. As a further step, with suitable methods to interface with on line data, economic scheduling can be achieved instantaneously in a generation control center. Also power scheduling of systems with different sources such as hydro, thermal etc. can be looked into and Reinforcement Learning solutions can be achieved.

Finite-element discretization of 3D energy-transport equations for semiconductors

In this thesis a mathematical model was derived that describes the charge and energy transport in semiconductor devices like transistors. Moreover, numerical simulations of these physical processes are performed. In order to accomplish this, methods of theoretical physics, functional analysis, numerical mathematics and computer programming are applied. After an introduction to the status quo of semiconductor device simulation methods and a brief review of historical facts up to now, the attention is shifted to the construction of a model, which serves as the basis of the subsequent derivations in the thesis. Thereby the starting point is an important equation of the theory of dilute gases. From this equation the model equations are derived and specified by means of a series expansion method. This is done in a multi-stage derivation process, which is mainly taken from a scientific paper and which does not constitute the focus of this thesis. In the following phase we specify the mathematical setting and make precise the model assumptions. Thereby we make use of methods of functional analysis. Since the equations we deal with are coupled, we are concerned with a nonstandard problem. In contrary, the theory of scalar elliptic equations is established meanwhile. Subsequently, we are preoccupied with the numerical discretization of the equations. A special finite-element method is used for the discretization. This special approach has to be done in order to make the numerical results appropriate for practical application. By a series of transformations from the discrete model we derive a system of algebraic equations that are eligible for numerical evaluation. Using self-made computer programs we solve the equations to get approximate solutions. These programs are based on new and specialized iteration procedures that are developed and thoroughly tested within the frame of this research work. Due to their importance and their novel status, they are explained and demonstrated in detail. We compare these new iterations with a standard method that is complemented by a feature to fit in the current context. A further innovation is the computation of solutions in three-dimensional domains, which are still rare. Special attention is paid to applicability of the 3D simulation tools. The programs are designed to have justifiable working complexity. The simulation results of some models of contemporary semiconductor devices are shown and detailed comments on the results are given. Eventually, we make a prospect on future development and enhancements of the models and of the algorithms that we used.

A measurement instrument for process modeling research : development, test and procedural model

Process modeling is an emergent area of Information Systems research that is characterized through an abundance of conceptual work with little empirical research. To fill this gap, this paper reports on the development and validation of an instrument to measure user acceptance of process modeling grammars. We advance an extended model for a multi-stage measurement instrument development procedure, which incorporates feedback from both expert and user panels. We identify two main contributions: First, we provide a validated measurement instrument for the study of user acceptance of process modeling grammars, which can be used to assist in further empirical studies that investigate phenomena associated with the business process modeling domain. Second, in doing so, we describe in detail a procedural model for developing measurement instruments that ensures high levels of reliability and validity, which may assist fellow scholars in executing their empirical research.

Digital Storytelling within a Service-Learning Partnership: Technology as Product and Process for University Students and Culturally and Linguistically Diverse High School Youth

This chapter describes a university/high school partnership focused on digital storytelling. It also explains the multi-stage process used to establish this successful partnership and project. The authors discuss the central role that technology played in developing this university/high school partnership, a collaboration that extended the impact of a digital storytelling project to reach high school students, university students, educators, high school administrators, and the local community. Valuing a reflective process that can lead to the creation of a powerful final product, the authors describe the impact of digital storytelling on multiple stakeholders, including the 13 university students and 33 culturally and linguistically diverse high school youth who participated during the fall of 2009. In addition, the chapter includes reflections from university and high school student participants expressed during focus groups conducted throughout the project. While most participants had a positive experience with the project, complications with the technology component often caused frustrations and additional challenges. Goals for sharing this project are to critically evaluate digital storytelling, describe lessons learned, and recommend good practices for others working within a similar context or with parallel goals.

Desalination by a solar thermally driven distillation process

Desalination processes to remove dissolved salts from seawater or brackish water includes common industrial scale processes such as reverse osmosis, thermal processes (i.e. multi-stage flash, multiple-effect distillation) and mechanical vapour compression. These processes are very energy intensive. The Institute for Future Environments (IFE) has evaluated various alternative processes to accomplish desalination using renewable or sustainable energy sources. A new process - a solar, thermally driven distillation system . based on the principles of a solar still – has been examined. This work presents an initial evaluation of the process.

Lagöversättning som process och produkt : Revideringar och institutioner vid lagöversättning till svenska i Finland

The thesis studies the translation process for the laws of Finland as they are translated from Finnish into Swedish. The focus is on revision practices, norms and workplace procedures. The translation process studied covers three institutions and four revisions. In three separate studies the translation process is analyzed from the perspective of the translations, the institutions and the actors. The general theoretical framework is Descriptive Translation Studies. For the analysis of revisions made in versions of the Swedish translation of Finnish laws, a model is developed covering five grammatical categories (textual revisions, syntactic revisions, lexical revisions, morphological revisions and content revisions) and four norms (legal adequacy, correct translation, correct language and readability). A separate questionnaire-based study was carried out with translators and revisers at the three institutions. The results show that the number of revisions does not decrease during the translation process, and no division of labour can be seen at the different stages. This is somewhat surprising if the revision process is regarded as one of quality control. Instead, all revisers make revisions on every level of the text. Further, the revisions do not necessarily imply errors in the translations but are often the result of revisers following different norms for legal translation. The informal structure of the institutions and its impact on communication, visibility and workplace practices was studied from the perspective of organization theory. The results show weaknesses in the communicative situation, which affect the co-operation both between institutions and individuals. Individual attitudes towards norms and their relative authority also vary, in the sense that revisers largely prioritize legal adequacy whereas translators give linguistic norms a higher value. Further, multi-professional teamwork in the institutions studied shows a kind of teamwork based on individuals and institutions doing specific tasks with only little contact with others. This shows that the established definitions of teamwork, with people co-working in close contact with each other, cannot directly be applied to the workplace procedures in the translation process studied. Three new concepts are introduced: flerstegsrevidering (multi-stage revision), revideringskedja (revision chain) and normsyn (norm attitude). The study seeks to make a contribution to our knowledge of legal translation, translation processes, institutional translation, revision practices and translation norms for legal translation. Keywords: legal translation, translation of laws, institutional translation, revision, revision practices, norms, teamwork, organizational informal structure, translation process, translation sociology, multilingual.

Dental Service Utilization, Dental Health Production and Equity in Dental Care: the Finnish Experience

This thesis is grounded on four articles. Article I generally examines the factors affecting dental service utilization. Article II studies the factors associated with sector-specific utilization among young adults entitled to age-based subsidized dental care. Article III explores the determinants of dental ill-health as measured by the occurrence of caries and the relationship between dental ill-health and dental care use. Article IV measures and explains income-related inequality in utilization. Data employed were from the 1996 Finnish Health Care Survey (I, II, IV) and the 1997 follow-up study included in the longitudinal study of the Northern Finland 1966 Birth Cohort (III). Utilization is considered as a multi-stage decision-making process and measured as the number of visits to the dentist. Modified count data models and concentration and horizontal equity indices were applied. Dentist s recall appeared very efficient at stimulating individuals to seek care. Dental pain, recall, and the low number of missing teeth positively affected utilization. Public subvention for dental care did not seem to statistically increase utilization. Among young adults, a perception of insufficient public service availability and recall were positively associated with the choice of a private dentist, whereas income and dentist density were positively associated with the number of visits to private dentists. Among cohort females, factors increasing caries were body mass index and intake of alcohol, sugar, and soft drinks and those reducing caries were birth weight and adolescent school achievement. Among cohort males, caries was positively related to the metropolitan residence and negatively related to healthy diet and education. Smoking increased caries, whereas regular teeth brushing, regular dental attendance and dental care use decreased caries. We found equity in young adults utilization but pro-rich inequity in the total number of visits to all dentists and in the probability of visiting a dentist for the whole sample. We observed inequity in the total number of visits to the dentist and in the probability of visiting a dentist, being pro-poor for public care but pro-rich for private care. The findings suggest that to enhance equal access to and use of dental care across population and income groups, attention should focus on supply factors and incentives to encourage people to contact dentists more often. Lowering co-payments and service fees and improving public availability would likely increase service use in both sectors. To attain favorable oral health, appropriate policies aimed at improving dental health education and reducing the detrimental effects of common risk factors on dental health should be strengthened. Providing equal access with respect to need for all people ought to take account of the segmentation of the service system, with its two parallel delivery systems and different supplier incentives to patients and dentists.

Evaluating Stakeholder Engagement in North Carolina Sea Grant’s Strategic Planning Process

In order to develop a strategic plan that will guide their priorities and resource allocation for 2018-2021, North Carolina Sea Grant has implemented a multi-stage process designed to increase stakeholder engagement and to better assess and serve the coastal priorities of North Carolinians. This project explores strengths and potential areas for improvement within NC Sea Grant’s planning process with a specific focus on maximizing stakeholder engagement. By interviewing staff, observing focus groups, and creating a survey instrument for public distribution, we developed a set of recommendations highlighting the ways that NC Sea Grant can better facilitate inclusion of stakeholder, public, and staff input in its strategic planning process, such as holding some stakeholder events outside of typical business hours and discussing ways to incorporate diversity into the strategic plan.

Culture and food: a model of yoghurt consumption in the EU

The completion of the Single European Market was expected to create a large market that would enable firms to capture economies of scale that would in turn result in lower prices to European consumers. These benefits are only likely to be realised if consumers in the various countries of the EU wish to consume the same products and respond to similar marketing strategies (with respect to promotion, distribution etc). This study examines, through a model of yoghurt consumption, whether cultural differences continue to determine food-related behaviour in the EU. The model is derived from the marketing literature and views the consumption decision as the outcome of a multi-stage process in which yoghurt knowledge, attitudes to different yoghurt attributes (such as bio-bifidus, low-fat, organic) and overall attitude towards yoghurt as a product all feed into the frequency with which yoghurt is consumed at breakfast, as a snack and as a dessert. The model uses data collected from a consumer survey in I I European countries and is estimated using probit and ordinal probit methods. The results suggest that important cultural differences continue to determine food-related behaviour in the I I countries of the study. (c) 2004 Elsevier Ltd. All rights reserved.