880 resultados para Vehicle Routing Problem Multi-Trip Ricerca Operativa TSP VRP


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Research has identified a number of putative risk factors that places adolescents at incrementally higher risk for involvement in alcohol and other drug (AOD) use and sexual risk behaviors (SRBs). Such factors include personality characteristics such as sensation-seeking, cognitive factors such as positive expectancies and inhibition conflict as well as peer norm processes. The current study was guided by a conceptual perspective that support the notion that an integrative framework that includes multi-level factors has significant explanatory value for understanding processes associated with the co-occurrence of AOD use and sexual risk behavior outcomes. This study evaluated simultaneously the mediating role of AOD-sex related expectancies and inhibition conflict on antecedents of AOD use and SRBs including sexual sensation-seeking and peer norms for condom use.^ The sample was drawn from the Enhancing My Personal Options While Evaluating Risk (EMPOWER: Jonathan Tubman, PI), data set (N = 396; aged 12-18 years). Measures used in the study included Sexual Sensation-Seeking Scale, Inhibition Conflict for Condom Use, Risky Sex Scale. All relevant measures had well-documented psychometric properties. A global assessment of alcohol, drug use and sexual risk behaviors was used.^ Results demonstrated that AOD-sex related expectancies mediated the influence of sexual sensation-seeking on the co-occurrence of alcohol and other drug use and sexual risk behaviors. The evaluation of the integrative model also revealed that sexual sensation-seeking was positively associated with peer norms for condom use. Also, peer norms predicted inhibition conflict among this sample of multi-problem youth. ^ This dissertation research identified mechanisms of risk and protection associated with the co-occurrence of AOD use and SRBs among a multi-problem sample of adolescents receiving treatment for alcohol or drug use and related problems. This study is informative for adolescent-serving programs that address those individual and contextual characteristics that enhance treatment efficacy and effectiveness among adolescents receiving substance use and related problems services.^

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The dissertation reports on two studies. The purpose of Study I was to develop and evaluate a measure of cognitive competence (the Critical Problem Solving Skills Scale – Qualitative Extension) using Relational Data Analysis (RDA) with a multi-ethnic, adolescent sample. My study builds on previous work that has been conducted to provide evidence for the reliability and validity of the RDA framework in evaluating youth development programs (Kurtines et al., 2008). Inter-coder percent agreement among the TOC and TCC coders for each of the category levels was moderate to high, with a range of .76 to .94. The Fleiss' kappa across all category levels was from substantial agreement to almost perfect agreement, with a range of .72 to .91. The correlation between the TOC and the TCC demonstrated medium to high correlation, with a range of r(40)=.68, p<.001 to r(40)=.79, p<.001. Study II reports an investigation of a positive youth development program using an Outcome Mediation Cascade (OMC) evaluation model, an integrated model for evaluating the empirical intersection between intervention and developmental processes. The Changing Lives Program (CLP) is a community supported positive youth development intervention implemented in a practice setting as a selective/indicated program for multi-ethnic, multi-problem at risk youth in urban alternative high schools in the Miami Dade County Public Schools (M-DCPS). The 259 participants for this study were drawn from the CLP's archival data file. The study used a structural equation modeling approach to construct and evaluate the hypothesized model. Findings indicated that the hypothesized model fit the data (χ2 (7) = 5.651, p = .83; RMSEA = .00; CFI = 1.00; WRMR = .319). My study built on previous research using the OMC evaluation model (Eichas, 2010), and the findings are consistent with the hypothesis that in addition to having effects on targeted positive outcomes, PYD interventions are likely to have progressive cascading effects on untargeted problem outcomes that operate through effects on positive outcomes.

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There is a growing body of literature that provides evidence for the efficacy of positive youth development programs in general and preliminary empirical support for the efficacy of the Changing Lives Program (CLP) in particular. This dissertation sought to extend previous efforts to develop and preliminarily examine the Transformative Goal Attainment Scale (TGAS) as a measure of participant empowerment in the promotion of positive development. Consistent with recent advances in the use of qualitative research methods, this dissertation sought to further investigate the utility of Relational Data Analysis (RDA) for providing categorizations of qualitative open-ended response data. In particular, a qualitative index of Transformative Goals, TG, was developed to complement the previously developed quantitative index of Transformative Goal Attainment (TGA), and RDA procedures for calculating reliability and content validity were refined. Second, as a Stage I pilot/feasibility study this study preliminarily examined the potentially mediating role of empowerment, as indexed by the TGAS, in the promotion of positive development. ^ Fifty-seven participants took part in this study, forty CLP intervention participants and seventeen control condition participants. All 57 participants were administered the study's measures just prior to and just following the fall 2003 semester. This study thus used a short-term longitudinal quasi-experimental research design with a comparison control group. ^ RDA procedures were refined and applied to the categorization of open-ended response data regarding participants' transformative goals (TG) and future possible selves (PSQ-QE). These analyses revealed relatively strong, indirect evidence for the construct validity of the categories as well as their theoretically meaningful structural organization, thereby providing sufficient support for the utility of RDA procedures in the categorization of qualitative open-ended response data. ^ In addition, transformative goals (TG) and future possible selves (PSQ-QE), and the quantitative index of perceived goal attainment (TGA) were evaluated as potential mediators of positive development by testing their relationships to other indices of positive intervention outcome within a four-step method involving both analysis of variance (ANOVA and RMANOVAs) and regression analysis. Though more limited in scope than the efforts at the development and refinement of the measures of these mediators, the results were also promising. ^

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This study investigated group processes as potential mediators or moderators of positive development outcome and negative reduction intervention response by evaluating the utility of a group measure modified from a widely known measure of group impact found in the group therapy research literature. Four group processes were of primary interest, (1) Group Impact; (2) Facilitator Impact; (3) Skills Impact; and (4) Exploration Impact as assessed by the Session Evaluation Form (SEF). Outcome measures included the Personally Expressive Activities Questionnaire (PEAQ), Erikson Psycho-Social Index (EPSI) and the Zill Behavior Items, Behavior Problem Index (ZBI (BPI)). The sample consisted of 121 multi-ethnic participants drawn from four alternative high schools from the Miami-Dade County Public School system. Utilizing a Latent Growth Curve Modeling approach with Structural Equation Modeling (SEM) statistics, preliminary analyses were conducted to evaluate the psychometric properties of the SEF and its role in the mediation or moderation of intervention outcome. Preliminary results revealed evidence of a single higher order factor representing a "General" global reaction, which was hypothesized to be a "Positive Group Climate" construct to the program as opposed to the four distinct group processes that were initially hypothesized to affect outcomes. The results of the evaluation of the mediation or moderation role of intervention outcome of the single "General" global latent factor ("Positive Group Climate" construct) did not significantly predict treatment response on any of the outcome variables. Nevertheless, the evidence of an underlying "General" global latent factor ("Positive Group Climate" construct) has important future directions for research on positive youth development programs as well as in group therapy research.

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This study was conducted to determine the effects of the Changing Lives Program intervention on troubled adolescents' feelings of personal expressiveness, believed to be one domain of positive identity development. Forty-three intervention and twenty nonintervention comparison control participants were given a battery of pre-, post-, and follow-up assessments including the Personally Expressive Questionnaire (Waterman, 1995), which was used to derive participants' feelings of personal expressiveness scores. Using Repeated Measures Analysis of Multivariate Analysis (RMANOVA), a significant four-way interaction of Time X Condition X Gender X Ethnicity was found relative to the Control, Roy's Ɵ = .166, F(2,47) = 3.899, p < .027 indicating that intervention participants' feelings of personal expressiveness did increase significantly relative to the control group. Furthermore, the results suggest differential outcomes based on ethnicity, suggesting the need for future study with respect to specificity of effects and mechanisms of identity formation in differing ethnic subgroups.

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Research has identified a number of putative risk factors that places adolescents at incrementally higher risk for involvement in alcohol and other drug (AOD) use and sexual risk behaviors (SRBs). Such factors include personality characteristics such as sensation-seeking, cognitive factors such as positive expectancies and inhibition conflict as well as peer norm processes. The current study was guided by a conceptual perspective that support the notion that an integrative framework that includes multi-level factors has significant explanatory value for understanding processes associated with the co-occurrence of AOD use and sexual risk behavior outcomes. This study evaluated simultaneously the mediating role of AOD-sex related expectancies and inhibition conflict on antecedents of AOD use and SRBs including sexual sensation-seeking and peer norms for condom use. The sample was drawn from the Enhancing My Personal Options While Evaluating Risk (EMPOWER: Jonathan Tubman, PI), data set (N = 396; aged 12-18 years). Measures used in the study included Sexual Sensation-Seeking Scale, Inhibition Conflict for Condom Use, Risky Sex Scale. All relevant measures had well-documented psychometric properties. A global assessment of alcohol, drug use and sexual risk behaviors was used. Results demonstrated that AOD-sex related expectancies mediated the influence of sexual sensation-seeking on the co-occurrence of alcohol and other drug use and sexual risk behaviors. The evaluation of the integrative model also revealed that sexual sensation-seeking was positively associated with peer norms for condom use. Also, peer norms predicted inhibition conflict among this sample of multi-problem youth. This dissertation research identified mechanisms of risk and protection associated with the co-occurrence of AOD use and SRBs among a multi-problem sample of adolescents receiving treatment for alcohol or drug use and related problems. This study is informative for adolescent-serving programs that address those individual and contextual characteristics that enhance treatment efficacy and effectiveness among adolescents receiving substance use and related problems services.

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The Traveling Salesman with Multiple Ridesharing (TSP-MR) is a type of the Capacitated Traveling Salesman, which presents the possibility of sharing seats with passengers taking advantage of the paths the salesman travels through his cycle. The salesman shares the cost of a path with the boarded passengers. This model can portray a real situation in which, for example, drivers are willing to share parts of a trip with tourists that wish to move between two locations visited by the driver’s route, accepting to share the vehicle with other individuals visiting other locations within the cycle. This work proposes a mathematical formulation for the problem, and an exact and metaheuristics algorithms for its solution, comparing them.

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The Traveling Salesman with Multiple Ridesharing (TSP-MR) is a type of the Capacitated Traveling Salesman, which presents the possibility of sharing seats with passengers taking advantage of the paths the salesman travels through his cycle. The salesman shares the cost of a path with the boarded passengers. This model can portray a real situation in which, for example, drivers are willing to share parts of a trip with tourists that wish to move between two locations visited by the driver’s route, accepting to share the vehicle with other individuals visiting other locations within the cycle. This work proposes a mathematical formulation for the problem, and an exact and metaheuristics algorithms for its solution, comparing them.

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Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

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Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

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Los problemas de corte y empaquetado son una familia de problemas de optimización combinatoria que han sido ampliamente estudiados en numerosas áreas de la industria y la investigación, debido a su relevancia en una enorme variedad de aplicaciones reales. Son problemas que surgen en muchas industrias de producción donde se debe realizar la subdivisión de un material o espacio disponible en partes más pequeñas. Existe una gran variedad de métodos para resolver este tipo de problemas de optimización. A la hora de proponer un método de resolución para un problema de optimización, es recomendable tener en cuenta el enfoque y las necesidades que se tienen en relación al problema y su solución. Las aproximaciones exactas encuentran la solución óptima, pero sólo es viable aplicarlas a instancias del problema muy pequeñas. Las heurísticas manejan conocimiento específico del problema para obtener soluciones de alta calidad sin necesitar un excesivo esfuerzo computacional. Por otra parte, las metaheurísticas van un paso más allá, ya que son capaces de resolver una clase muy general de problemas computacionales. Finalmente, las hiperheurísticas tratan de automatizar, normalmente incorporando técnicas de aprendizaje, el proceso de selección, combinación, generación o adaptación de heurísticas más simples para resolver eficientemente problemas de optimización. Para obtener lo mejor de estos métodos se requiere conocer, además del tipo de optimización (mono o multi-objetivo) y el tamaño del problema, los medios computacionales de los que se dispone, puesto que el uso de máquinas e implementaciones paralelas puede reducir considerablemente los tiempos para obtener una solución. En las aplicaciones reales de los problemas de corte y empaquetado en la industria, la diferencia entre usar una solución obtenida rápidamente y usar propuestas más sofisticadas para encontrar la solución óptima puede determinar la supervivencia de la empresa. Sin embargo, el desarrollo de propuestas más sofisticadas y efectivas normalmente involucra un gran esfuerzo computacional, que en las aplicaciones reales puede provocar una reducción de la velocidad del proceso de producción. Por lo tanto, el diseño de propuestas efectivas y, al mismo tiempo, eficientes es fundamental. Por esta razón, el principal objetivo de este trabajo consiste en el diseño e implementación de métodos efectivos y eficientes para resolver distintos problemas de corte y empaquetado. Además, si estos métodos se definen como esquemas lo más generales posible, se podrán aplicar a diferentes problemas de corte y empaquetado sin realizar demasiados cambios para adaptarlos a cada uno. Así, teniendo en cuenta el amplio rango de metodologías de resolución de problemas de optimización y las técnicas disponibles para incrementar su eficiencia, se han diseñado e implementado diversos métodos para resolver varios problemas de corte y empaquetado, tratando de mejorar las propuestas existentes en la literatura. Los problemas que se han abordado han sido: el Two-Dimensional Cutting Stock Problem, el Two-Dimensional Strip Packing Problem, y el Container Loading Problem. Para cada uno de estos problemas se ha realizado una amplia y minuciosa revisión bibliográfica, y se ha obtenido la solución de las distintas variantes escogidas aplicando diferentes métodos de resolución: métodos exactos mono-objetivo y paralelizaciones de los mismos, y métodos aproximados multi-objetivo y paralelizaciones de los mismos. Los métodos exactos mono-objetivo aplicados se han basado en técnicas de búsqueda en árbol. Por otra parte, como métodos aproximados multi-objetivo se han seleccionado unas metaheurísticas multi-objetivo, los MOEAs. Además, para la representación de los individuos utilizados por estos métodos se han empleado codificaciones directas mediante una notación postfija, y codificaciones que usan heurísticas de colocación e hiperheurísticas. Algunas de estas metodologías se han mejorado utilizando esquemas paralelos haciendo uso de las herramientas de programación OpenMP y MPI.

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Technologies for Big Data and Data Science are receiving increasing research interest nowadays. This paper introduces the prototyping architecture of a tool aimed to solve Big Data Optimization problems. Our tool combines the jMetal framework for multi-objective optimization with Apache Spark, a technology that is gaining momentum. In particular, we make use of the streaming facilities of Spark to feed an optimization problem with data from different sources. We demonstrate the use of our tool by solving a dynamic bi-objective instance of the Traveling Salesman Problem (TSP) based on near real-time traffic data from New York City, which is updated several times per minute. Our experiment shows that both jMetal and Spark can be integrated providing a software platform to deal with dynamic multi-optimization problems.

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The dissertation reports on two studies. The purpose of Study I was to develop and evaluate a measure of cognitive competence (the Critical Problem Solving Skills Scale – Qualitative Extension) using Relational Data Analysis (RDA) with a multi-ethnic, adolescent sample. My study builds on previous work that has been conducted to provide evidence for the reliability and validity of the RDA framework in evaluating youth development programs (Kurtines et al., 2008). Inter-coder percent agreement among the TOC and TCC coders for each of the category levels was moderate to high, with a range of .76 to .94. The Fleiss’ kappa across all category levels was from substantial agreement to almost perfect agreement, with a range of .72 to .91. The correlation between the TOC and the TCC demonstrated medium to high correlation, with a range of r(40)=.68, p Study II reports an investigation of a positive youth development program using an Outcome Mediation Cascade (OMC) evaluation model, an integrated model for evaluating the empirical intersection between intervention and developmental processes. The Changing Lives Program (CLP) is a community supported positive youth development intervention implemented in a practice setting as a selective/indicated program for multi-ethnic, multi-problem at risk youth in urban alternative high schools in the Miami Dade County Public Schools (M-DCPS). The 259 participants for this study were drawn from the CLP’s archival data file. The study used a structural equation modeling approach to construct and evaluate the hypothesized model. Findings indicated that the hypothesized model fit the data (χ2 (7) = 5.651, p = .83; RMSEA = .00; CFI = 1.00; WRMR = .319). My study built on previous research using the OMC evaluation model (Eichas, 2010), and the findings are consistent with the hypothesis that in addition to having effects on targeted positive outcomes, PYD interventions are likely to have progressive cascading effects on untargeted problem outcomes that operate through effects on positive outcomes.

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The electrocatalytic reduction of CO2 (CO2RR) is a captivating strategy for the conversion of CO2 into fuels, to realize a carbon neutral circular economy. In the recent years, research has focused on the development of new materials and technology capable of capturing and converting CO2 into useful products. The main problem of CO2RR is given by its poor selectivity, which can lead to the formation of numerous reaction products, to the detriment of efficiencies. For this reason, the design of new electrocatalysts that selectively and efficiently reduce CO2 is a fundamental step for the future exploitation of this technology. Here we present a new class of electrocatalysts, designed with a modular approach, namely, deriving from the combination of different building blocks in a single nanostructure. With this approach it is possible to obtain materials with an innovative design and new functionalities, where the interconnections between the various components are essential to obtain a highly selective and efficient reduction of CO2, thus opening up new possibilities in the design of optimized electrocatalytic materials. By combining the unique physic-chemical properties of carbon nanostructures (CNS) with nanocrystalline metal oxides (MO), we were able to modulate the selectivity of CO2RR, with the production of formic acid and syngas at low overpotentials. The CNS have not only the task of stabilizing the MO nanoparticles, but the creation of an optimal interface between two nanostructures is able to improve the catalytic activity of the active phase of the material. While the presence of oxygen atoms in the MO creates defects that accelerate the reaction kinetics and stabilize certain reaction intermediates, selecting the reaction pathway. Finally, a part was dedicated to the study of the experimental parameters influencing the CO2RR, with the aim of improving the experimental setup in order to obtain commercial catalytic performances.

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Machine (and deep) learning technologies are more and more present in several fields. It is undeniable that many aspects of our society are empowered by such technologies: web searches, content filtering on social networks, recommendations on e-commerce websites, mobile applications, etc., in addition to academic research. Moreover, mobile devices and internet sites, e.g., social networks, support the collection and sharing of information in real time. The pervasive deployment of the aforementioned technological instruments, both hardware and software, has led to the production of huge amounts of data. Such data has become more and more unmanageable, posing challenges to conventional computing platforms, and paving the way to the development and widespread use of the machine and deep learning. Nevertheless, machine learning is not only a technology. Given a task, machine learning is a way of proceeding (a way of thinking), and as such can be approached from different perspectives (points of view). This, in particular, will be the focus of this research. The entire work concentrates on machine learning, starting from different sources of data, e.g., signals and images, applied to different domains, e.g., Sport Science and Social History, and analyzed from different perspectives: from a non-data scientist point of view through tools and platforms; setting a problem stage from scratch; implementing an effective application for classification tasks; improving user interface experience through Data Visualization and eXtended Reality. In essence, not only in a quantitative task, not only in a scientific environment, and not only from a data-scientist perspective, machine (and deep) learning can do the difference.