Contribution of re-regulation reservoirs considering pumping capability to environmentally friendly hydropower operation

Environmental constraints imposed on hydropoweroperation are usually given in the form of minimum environmental flows and maximum and minimum rates of change of flows, or ramp rates. One solution proposed to mitigate the environmental impact caused by the flows discharged by a hydropower plant while reducing the economic impact of the above-mentioned constraints consists in building a re-regulationreservoir, or afterbay, downstream of the power plant. Adding pumpingcapability between the re-regulationreservoir and the main one could contribute both to reducing the size of the re-regulationreservoir, with the consequent environmental improvement, and to improving the economic feasibility of the project, always fulfilling the environmental constraints imposed to hydropoweroperation. The objective of this paper is studying the contribution of a re-regulationreservoir to fulfilling the environmental constraints while reducing the economic impact of said constraints. For that purpose, a revenue-driven optimization model based on mixed integer linear programming is used. Additionally, the advantages of adding pumpingcapability are analysed. In order to illustrate the applicability of the methodology, a case study based on a real hydropower plant is presented

Red Eléctrica de España uses integer programming for annual salary revisions

In this paper, we present a mixed-integer linear programming model for determining salary-revision matrices for an organization based on that organization?s general strategies. The solution obtained from this model consists of salary increases for each employee; these increases consider the employee?s professional performance, salary level relative to peers within the organization, and professional group. In addition to budget constraints, we modeled other elements typical of compensation systems, such as equity and justice. Red Eléctrica de España (REE), the transmission agent and operator of the Spanish electricity system, used the model to revise its 2010 and 2011 salary policies, and achieved results that were aligned with the company strategy. REE incorporated the model into the salary management module within its information system, and plans to continue to use the model in revisions of the module.

Modelo de gestión de un embalse en tiempo real durante avenidas basado en redes bayesianas entrenadas con el método de optimización PLEM

En la actualidad, la gestión de embalses para el control de avenidas se realiza, comúnmente, utilizando modelos de simulación. Esto se debe, principalmente, a su facilidad de uso en tiempo real por parte del operador de la presa. Se han desarrollado modelos de optimización de la gestión del embalse que, aunque mejoran los resultados de los modelos de simulación, su aplicación en tiempo real se hace muy difícil o simplemente inviable, pues está limitada al conocimiento de la avenida futura que entra al embalse antes de tomar la decisión de vertido. Por esta razón, se ha planteado el objetivo de desarrollar un modelo de gestión de embalses en avenidas que incorpore las ventajas de un modelo de optimización y que sea de fácil uso en tiempo real por parte del gestor de la presa. Para ello, se construyó un modelo de red Bayesiana que representa los procesos de la cuenca vertiente y del embalse y, que aprende de casos generados sintéticamente mediante un modelo hidrológico agregado y un modelo de optimización de la gestión del embalse. En una primera etapa, se generó un gran número de episodios sintéticos de avenida utilizando el método de Monte Carlo, para obtener las lluvias, y un modelo agregado compuesto de transformación lluvia- escorrentía, para obtener los hidrogramas de avenida. Posteriormente, se utilizaron las series obtenidas como señales de entrada al modelo de gestión de embalses PLEM, que optimiza una función objetivo de costes mediante programación lineal entera mixta, generando igual número de eventos óptimos de caudal vertido y de evolución de niveles en el embalse. Los episodios simulados fueron usados para entrenar y evaluar dos modelos de red Bayesiana, uno que pronostica el caudal de entrada al embalse, y otro que predice el caudal vertido, ambos en un horizonte de tiempo que va desde una a cinco horas, en intervalos de una hora. En el caso de la red Bayesiana hidrológica, el caudal de entrada que se elige es el promedio de la distribución de probabilidad de pronóstico. En el caso de la red Bayesiana hidráulica, debido al comportamiento marcadamente no lineal de este proceso y a que la red Bayesiana devuelve un rango de posibles valores de caudal vertido, se ha desarrollado una metodología para seleccionar un único valor, que facilite el trabajo del operador de la presa. Esta metodología consiste en probar diversas estrategias propuestas, que incluyen zonificaciones y alternativas de selección de un único valor de caudal vertido en cada zonificación, a un conjunto suficiente de episodios sintéticos. Los resultados de cada estrategia se compararon con el método MEV, seleccionándose las estrategias que mejoran los resultados del MEV, en cuanto al caudal máximo vertido y el nivel máximo alcanzado por el embalse, cualquiera de las cuales puede usarse por el operador de la presa en tiempo real para el embalse de estudio (Talave). La metodología propuesta podría aplicarse a cualquier embalse aislado y, de esta manera, obtener, para ese embalse particular, diversas estrategias que mejoran los resultados del MEV. Finalmente, a modo de ejemplo, se ha aplicado la metodología a una avenida sintética, obteniendo el caudal vertido y el nivel del embalse en cada intervalo de tiempo, y se ha aplicado el modelo MIGEL para obtener en cada instante la configuración de apertura de los órganos de desagüe que evacuarán el caudal. Currently, the dam operator for the management of dams uses simulation models during flood events, mainly due to its ease of use in real time. Some models have been developed to optimize the management of the reservoir to improve the results of simulation models. However, real-time application becomes very difficult or simply unworkable, because the decision to discharge depends on the unknown future avenue entering the reservoir. For this reason, the main goal is to develop a model of reservoir management at avenues that incorporates the advantages of an optimization model. At the same time, it should be easy to use in real-time by the dam manager. For this purpose, a Bayesian network model has been developed to represent the processes of the watershed and reservoir. This model learns from cases generated synthetically by a hydrological model and an optimization model for managing the reservoir. In a first stage, a large number of synthetic flood events was generated using the Monte Carlo method, for rain, and rain-added processing model composed of runoff for the flood hydrographs. Subsequently, the series obtained were used as input signals to the reservoir management model PLEM that optimizes a target cost function using mixed integer linear programming. As a result, many optimal discharge rate events and water levels in the reservoir levels were generated. The simulated events were used to train and test two models of Bayesian network. The first one predicts the flow into the reservoir, and the second predicts the discharge flow. They work in a time horizon ranging from one to five hours, in intervals of an hour. In the case of hydrological Bayesian network, the chosen inflow is the average of the probability distribution forecast. In the case of hydraulic Bayesian network the highly non-linear behavior of this process results on a range of possible values of discharge flow. A methodology to select a single value has been developed to facilitate the dam operator work. This methodology tests various strategies proposed. They include zoning and alternative selection of a single value in each discharge rate zoning from a sufficient set of synthetic episodes. The results of each strategy are compared with the MEV method. The strategies that improve the outcomes of MEV are selected and can be used by the dam operator in real time applied to the reservoir study case (Talave). The methodology could be applied to any single reservoir and, thus, obtain, for the particular reservoir, various strategies that improve results from MEV. Finally, the methodology has been applied to a synthetic flood, obtaining the discharge flow and the reservoir level in each time interval. The open configuration floodgates to evacuate the flow at each interval have been obtained applying the MIGEL model.

Herramientas de gestión de compromiso para trabajadores del conocimiento

El objetivo de la línea de investigación seguida en esta tesis consiste en identificar palancas de gestión de las personas en las organizaciones que permitan mejorar su rendimiento mediante la gestión del compromiso de los profesionales de las organizaciones inmersas en la denominada sociedad del conocimiento. Para identificar dichas palancas se analizan algunos de los factores que, según la literatura científica, tienen como consecuencia cambios en la productividad, como son el compromiso organizacional y las conductas cívicas dentro de la organización. También, por su actualidad y relevancia en las prácticas de gestión de recursos humanos, se han analizado el impacto que tienen en estos factores en las prácticas empresariales que permiten conciliar vida profesional y personal el efecto del género en las distintas variables analizadas. Por todo lo anterior, en la investigación se analizan algunos de los factores de carácter psicosocial que promueven el compromiso en una organización, y se profundiza en dos conceptos: el análisis del compromiso de los profesionales con la organización para la que trabajan, y los comportamientos de ciudadanía organizativa que se exhiben en la organización por sus miembros. Para ello, se realiza un encuadramiento teórico de los siguientes conceptos: el compromiso como eje del trabajo; la ciudadanía organizativa como modelo cultural de la organización que promueve el compromiso; el rol de los líderes; los efectos de las políticas de conciliación; las diferencias de percepciones derivadas del género y un sistema de revisión de retributiva eficiente y coherente con el marco conceptual planteado. La metodología seleccionada para este trabajo ha sido el análisis en profundidad del caso de una empresa española, Red Eléctrica de España a través de tres pilares básicos: el primero consiste en el análisis exhaustivo de los datos obtenidos en las dos encuestas de clima social que dicha empresa realizó en el período 2006-2009; el segundo se centra en el desarrollo de un modelo matemático para el cálculo eficiente de recompensas salariales a través de un modelo de optimización; y el tercero es la consecuencia del conocimiento profundo que el autor tiene de la propia empresa, su cultura y funcionamiento, fruto de su experiencia profesional como directivo en el área de desarrollo de recursos humanos, función que desempeñó en la organización durante nueve años. En el análisis de este caso se ha investigado la influencia del género en el compromiso y la ciudadanía organizativa de los empleados de dicha organización, para identificar las diferencias de percepción que puedan ser explicadas por el género en una empresa muy masculina como es aquella. También, se ha incluido en este estudio de caso el análisis del efecto que presentan las medidas de conciliación en el compromiso de los empleados, por la relevancia que tiene este asunto en el panorama laboral español actual. Este análisis permite conocer hasta qué punto son o no motivadoras estas medidas en la organización analizada y, como consecuencia de ello, el tipo de gestión más oportuna de las mismas para conseguir no sólo los fines sociales que pretenden, garantizar que los empleados puedan compatibilizar sus exigencias laborales con una vida personal adecuada, sino también mejorar el clima, productividad y compromiso de éstos con la empresa. Para completar este análisis del caso, se han identificado de forma analítica los factores que mejor explican el clima de la organización y se ha concluido el papel central de la dirección que se concreta en la actuación de cada jefe, como motor del clima social en el equipo que dirige. Dado que la tesis pivota sobre el papel relevante que tiene la generación de una cultura de ciudadanía organizativa, se ha complementado el análisis con el desarrollo una herramienta de cálculo que facilita la determinación de los incrementos de la retribución fija de acuerdo con los principios de transparencia, equidad y justicia acordes con el modelo de empresa que promueve la virtud cívica de las personas empleadas en ella. Para ello se ha desarrollado un nuevo método de cálculo del incremento de retribución fija mediante un modelo analítico innovador y compacto de programación lineal entera mixta. Este modelo permite a las organizaciones realizar diseños de política retributiva de forma sencilla y rápida, a la vez que facilita la transparencia de las mismas en el proceso de gestión de la compensación. No se ha abordado el asunto de la determinación de la retribución variable, por ser un asunto relativamente menos complejo y profusamente tratado en la práctica directiva de las empresas. La primera de las conclusiones de la investigación realizada se refiere a los aspectos de la cultura organizativa que pueden identificarse como motores del compromiso. Se concluye que en el caso de estudio hay una fuerte relación mutua entre los rasgos que definen el compromiso emocional y los rasgos que determinan un comportamiento caracterizado como de ciudadanía organizativa. Se ha encontrado una correlación significativa y alta entre indicadores de compromiso y factores que recogen comportamientos de ciudadanía organizativa, correlación muy notable tanto para los factores de compromiso racional como para los de compromiso emocional. También se ha evidenciado que la correlación entre compromiso emocional y rasgos de comportamientos de ciudadanía organizacional es mayor que la que aparece entre compromiso racional y rasgos de comportamientos de ciudadanía organizacional. Desde el punto de vista de la práctica de gestión de recursos humanos, estas relaciones indican la conveniencia de promover una cultura organizacional basada en los principios de la ciudadanía organizativa para alcanzar altos niveles de compromiso emocional de los profesionales y mejorar la eficiencia organizativa. La segunda de las conclusiones se refiere al efecto de las políticas de conciliación en las organizaciones. Sobre este asunto se concluye que en el caso de estudio no puede considerarse que las medidas de conciliación tengan una fuerte relación con el compromiso emocional, y menos que puedan considerarse directamente una herramienta de generación de compromiso emocional. Sin embargo, sí que se detecta una cierta relación entre las percepciones de conciliación y de compromiso con la organización, y sobre todo, con el compromiso racional con la organización, que puede tener que ver con que para los empleados de la organización analizada, las medidas de conciliación son consideradas como una parte más de las condiciones laborales que ofrece la organización a los trabajadores. La tercera conclusión se refiere a la relación entre el género de los trabajadores y su nivel de compromiso y de ciudadanía organizativa. En el caso de estudio no se identifica una relación entre el género y el nivel de compromiso de los profesionales ni tampoco con la percepción de ciudadanía organizativa, variando la situación del período 2006 al período 2009. La cuarta conclusión se refiere al impacto que la actuación de los líderes (jefes) tiene en el clima social. En el caso de estudio, la actuación de los directivos y el nivel de compromiso que genera en los profesionales explica por sí sola más de un tercio de la varianza del clima organizativo, entendido como tal el que refleja el conjunto global de preguntas que constituyen la encuesta de clima del caso de estudio. Del análisis realizado se concluye que en el caso de estudio la percepción que los empleados tienen de sus jefes tiene un efecto relevante sobre el resto de percepciones de compromiso, ciudadanía organizativa y otros factores que conforman el clima social de la organización. La quinta y última conclusión supone la aportación de un modelo novedoso de cálculo de la recompensa económica coherente con un modelo de gestión empresarial mediante una cultura de ciudadanía organizativa. La solución que obtiene este modelo es el incremento salarial individual de cada profesional, que tiene en cuenta su rendimiento, posicionamiento salarial y encuadramiento profesional. Además de las restricciones presupuestarias, se consideran los principios de transparencia, equidad y justicia coherentes con el modelo conceptual planteado. La principal contribución de este trabajo es la formulación matemática de los criterios cualitativos que se emplean habitualmente en el proceso de revisión salarial. El método planteado supone una innovación que permite automatizar la metodología tradicional de gestión de incrementos salariales basados en matrices de incremento, así como evitar la aplicación de limitaciones en las valoraciones de desempeño derivadas de las restricciones presupuestarias que toda organización tiene. De esta manera se puede disponer de un mecanismo de revisión salarial que tiene en cuenta el desempeño de los profesionales, pero que permite la gestión “desacoplada” de la evaluación de rendimiento y la actualización de la retribución fija. ABSTRACT The aim of the research pursued in this thesis is to identify some human resources management levers in organizations to improve their performance through individual’s commitment management, focusing in organizations immersed in the so-called knowledge society. In order to find out these levers, the author analysed some of the psychosocial factors that promote engagement to the organizations and, according to the scientific literature, have effects in their productivity. These factors analysed are organisational commitment and citizenship behaviours. Additionally, the investigation also focuses on work-life balance policies and gender considerations, because of their relevance and topicality for the human resources’ policies. In the light of this, the investigation focuses on some of the psychosocial factors that promote organisational commitment, and delves into two concepts: the analysis of the commitment of professionals to the organization for which they work, and the organizational citizenship behaviours exhibited in the organization by its members. For this, a theoretical framework is performed for the following items: the professional’s commitment which is the pillar of this work; the organisational citizenship as a cultural model to promote that commitment; the role of the leaders; the effects of the work-life balance policies; the different perceptions of the professionals because of their gender; and an efficient salary review system, which is coherent with the conceptual framework set. The methodology selected for this work was the analysis in depth of the case of a Spanish company, Red Eléctrica de España, through three basic subjects: the first consists of a thorough analysis of the data obtained in the two work climate surveys made by this company in 2006 and 2009; the second focuses on the development of a mathematical model for calculating efficient salary reviews through an optimization model; and the third is the result of the author’s deep understanding of the company, its culture and its performance because of his professional experience as a manager in the area of human resource development, which was his role in the organization for nine years. The author investigated in the analysis of this case about the influence of gender on the employees’ organizational commitment and citizenship behaviours, in order to find out perception differences that can be explained by the highly masculine organisational culture such Red Eléctrica de España had during the studied period. Additionally, because of the importance of the work-life balance promotion in the Spanish labour scene, the case study analysis includes their effect in the employees’ commitment. This analysis allows to know motivating are these measures in the studied organization and, as a result, the most appropriate type of management thereof for social purposes, not only intended to ensure that employees can balance their work and personal demands, but also improving the work climate, the productivity and the organisational commitment. The investigation identifies the factors which best explain the work climate of the organization and concludes the central role of the leadership, embodied in the performance of every manager, to boost the work climate in their teams. Since this thesis pivots on the important role the generation of a culture of organizational citizenship has, the investigation has been complemented with the development of a analytic tool that facilitates the calculation of the salary review increments according to the principles of transparency, equity and justice in line with a work culture that promotes organisational citizenship behaviours. For this, this works develops a new method for calculating fixed salary increases through an innovative and compact mixed integer linear programming model. This model enables organizations to design compensation policies easily and quickly, and facilitates the transparency of the compensation management system. The method for determining variable remuneration has not been addressed because it is relatively less complex issue and widely discussed. The first conclusion of the conducted investigation concerns aspects of organizational culture that could be identified as commitment drivers. In the case study exists a strong and mutual relationship between the characteristics defining the emotional commitment and the organisational citizenship behaviours. The investigation has found out a meaningful and high correlation between indicators of commitment and the factors collecting organizational citizenship behaviour. This correlation with organisational citizenship is remarkable for both, rational and emotional, commitment. The correlation between organizational citizenship behaviours and emotional commitment and is greater than the one with rational commitment. From the practitioner point of view, these relationships show the importance of promoting an organizational culture based on the principles of organizational citizenship to achieve high levels of emotional engagement of professionals and improve organizational efficiency. The second conclusion relates to the effect of work-life balance policies in organizations. On this matter, the investigation concludes that for the case study, work-life balance measures do not have a strong relationship with the emotional commitment, and unless they can be usually considered as a tool to improve employees’ emotional commitment. However, a certain relationship between perceptions of work-life facilities and organisational commitment exists, especially with the rational commitment to the organization. This relationship appears because for employees of the analysed organization, work-life balance measures could be considered as a part of working conditions offered to them by the organization. The third conclusion concerns the relationship between the gender of workers and their level of commitment and organizational citizenship. In this case study, there is not any relationship between gender and the professional’s commitment level nor the perception of organizational citizenship; and the situation varies during the period studied. The fourth conclusion refers to the impact that the actions of the leaders have on the work climate. In the case study, the performance of management and the level of commitment generated, explains more than a third of the variance of work climate - understood as such reflecting the overall set of questions that constitute the work climate survey -. The analysis concludes that in the case study perception that employees have of their leaders has a significant effect on the rest of perceptions of commitment, organizational citizenship and other factors making the work climate of the organization. The fifth and last conclusion represents the contribution of a new model for calculating the salary increment, coherent with a corporate citizenship management culture. The solution obtained from this model consists of salary increases for each employee; these increases consider the employee’s professional performance, salary level relative to peers within the organization, and professional group. In addition to budget constraints, we modelled other elements typical of compensation systems, such as equity and justice. The major contribution of this work is the mathematical formulation of the criteria that are typically the basis for salary management. The compact formulation and the ease of obtaining the optimal solution facilitate its use in large companies that maintain very high levels of homogeneity across employees. Designing different strategies for specific groups within a company is also possible. A major benefit of this method is that it allows a company to independently manage its salary and assessment policies. Because obtaining salary-revision matrices without using the mathematical model we present in this paper is typically done iteratively by tuning previously defined matrices, managers commonly tune values for assessing employee performance to ensure that salary increases and performance assessments are consistent; however, this distorts the evaluation process and decreases employee motivation. In this MILP model, employee performance is only one parameter of several input parameters used in designing a salary policy that is independent of the results of performance-assessment values.

Planejamento de sistemas de distribuição de energia elétrica considerando questões de confiabilidade e risco

O problema de Planejamento da Expansão de Sistemas de Distribuição (PESD) visa determinar diretrizes para a expansão da rede considerando a crescente demanda dos consumidores. Nesse contexto, as empresas distribuidoras de energia elétrica têm o papel de propor ações no sistema de distribuição com o intuito de adequar o fornecimento da energia aos padrões exigidos pelos órgãos reguladores. Tradicionalmente considera-se apenas a minimização do custo global de investimento de planos de expansão, negligenciando-se questões de confiabilidade e robustez do sistema. Como consequência, os planos de expansão obtidos levam o sistema de distribuição a configurações que são vulneráveis a elevados cortes de carga na ocorrência de contingências na rede. Este trabalho busca a elaboração de uma metodologia para inserir questões de confiabilidade e risco ao problema PESD tradicional, com o intuito de escolher planos de expansão que maximizem a robustez da rede e, consequentemente, atenuar os danos causados pelas contingências no sistema. Formulou-se um modelo multiobjetivo do problema PESD em que se minimizam dois objetivos: o custo global (que incorpora custo de investimento, custo de manutenção, custo de operação e custo de produção de energia) e o risco de implantação de planos de expansão. Para ambos os objetivos, são formulados modelos lineares inteiros mistos que são resolvidos utilizando o solver CPLEX através do software GAMS. Para administrar a busca por soluções ótimas, optou-se por programar em linguagem C++ dois Algoritmos Evolutivos: Non-dominated Sorting Genetic Algorithm-2 (NSGA2) e Strength Pareto Evolutionary Algorithm-2 (SPEA2). Esses algoritmos mostraram-se eficazes nessa busca, o que foi constatado através de simulações do planejamento da expansão de dois sistemas testes adaptados da literatura. O conjunto de soluções encontradas nas simulações contém planos de expansão com diferentes níveis de custo global e de risco de implantação, destacando a diversidade das soluções propostas. Algumas dessas topologias são ilustradas para se evidenciar suas diferenças.

Rigorous Design of Complex Distillation Columns Using Process Simulators and the Particle Swarm Optimization Algorithm

We present a derivative-free optimization algorithm coupled with a chemical process simulator for the optimal design of individual and complex distillation processes using a rigorous tray-by-tray model. The proposed approach serves as an alternative tool to the various models based on nonlinear programming (NLP) or mixed-integer nonlinear programming (MINLP) . This is accomplished by combining the advantages of using a commercial process simulator (Aspen Hysys), including especially suited numerical methods developed for the convergence of distillation columns, with the benefits of the particle swarm optimization (PSO) metaheuristic algorithm, which does not require gradient information and has the ability to escape from local optima. Our method inherits the superstructure developed in Yeomans, H.; Grossmann, I. E.Optimal design of complex distillation columns using rigorous tray-by-tray disjunctive programming models. Ind. Eng. Chem. Res.2000, 39 (11), 4326–4335, in which the nonexisting trays are considered as simple bypasses of liquid and vapor flows. The implemented tool provides the optimal configuration of distillation column systems, which includes continuous and discrete variables, through the minimization of the total annual cost (TAC). The robustness and flexibility of the method is proven through the successful design and synthesis of three distillation systems of increasing complexity.

Handling of Uncertainty in Life Cycle Inventory by Correlated Multivariate Lognormal Distributions: Application to the Design of Supply Chain Networks

Poster presented in the 24th European Symposium on Computer Aided Process Engineering (ESCAPE 24), Budapest, Hungary, June 15-18, 2014.

MINLP Optimization Algorithm for the Synthesis of Heat and Work Exchange Networks

This paper introduces a new optimization model for the simultaneous synthesis of heat and work exchange networks. The work integration is performed in the work exchange network (WEN), while the heat integration is carried out in the heat exchanger network (HEN). In the WEN synthesis, streams at high-pressure (HP) and low-pressure (LP) are subjected to pressure manipulation stages, via turbines and compressors running on common shafts and stand-alone equipment. The model allows the use of several units of single-shaft-turbine-compressor (SSTC), as well as helper motors and generators to respond to any shortage and/or excess of energy, respectively, in the SSTC axes. The heat integration of the streams occurs in the HEN between each WEN stage. Thus, as the inlet and outlet streams temperatures in the HEN are dependent of the WEN design, they must be considered as optimization variables. The proposed multi-stage superstructure is formulated in mixed-integer nonlinear programming (MINLP), in order to minimize the total annualized cost composed by capital and operational expenses. A case study is conducted to verify the accuracy of the proposed approach. The results indicate that the heat integration between the WEN stages is essential to enhance the work integration, and to reduce the total cost of process due the need of a smaller amount of hot and cold utilities.

Handling of Uncertainty in Life Cycle Inventory by Correlated Multivariate Lognormal Distributions: Application to the Design of Supply Chain Networks

In this work, we analyze the effect of incorporating life cycle inventory (LCI) uncertainty on the multi-objective optimization of chemical supply chains (SC) considering simultaneously their economic and environmental performance. To this end, we present a stochastic multi-scenario mixed-integer linear programming (MILP) coupled with a two-step transformation scenario generation algorithm with the unique feature of providing scenarios where the LCI random variables are correlated and each one of them has the desired lognormal marginal distribution. The environmental performance is quantified following life cycle assessment (LCA) principles, which are represented in the model formulation through standard algebraic equations. The capabilities of our approach are illustrated through a case study of a petrochemical supply chain. We show that the stochastic solution improves the economic performance of the SC in comparison with the deterministic one at any level of the environmental impact, and moreover the correlation among environmental burdens provides more realistic scenarios for the decision making process.

An integer-valued data envelopment analysis model with bounded outputs

Integer-valued data envelopment analysis (DEA) with alternative returns to scale technology has been introduced and developed recently by Kuosmanen and Kazemi Matin. The proportionality assumption of their introduced "natural augmentability" axiom in constant and nondecreasing returns to scale technologies makes it possible to achieve feasible decision-making units (DMUs) of arbitrary large size. In many real world applications it is not possible to achieve such production plans since some of the input and output variables are bounded above. In this paper, we extend the axiomatic foundation of integer-valuedDEAmodels for including bounded output variables. Some model variants are achieved by introducing a new axiom of "boundedness" over the selected output variables. A mixed integer linear programming (MILP) formulation is also introduced for computing efficiency scores in the associated production set. © 2011 The Authors. International Transactions in Operational Research © 2011 International Federation of Operational Research Societies.

Optimization models for selecting bus stops for accessibility improvements for people with disabilities

Bus stops are key links in the journeys of transit patrons with disabilities. Inaccessible bus stops prevent people with disabilities from using fixed-route bus services, thus limiting their mobility. The Americans with Disabilities Act (ADA) of 1990 prescribes the minimum requirements for bus stop accessibility by riders with disabilities. Due to limited budgets, transit agencies can only select a limited number of bus stop locations for ADA improvements annually. These locations should preferably be selected such that they maximize the overall benefits to patrons with disabilities. In addition, transit agencies may also choose to implement the universal design paradigm, which involves higher design standards than current ADA requirements and can provide amenities that are useful for all riders, like shelters and lighting. Many factors can affect the decision to improve a bus stop, including rider-based aspects like the number of riders with disabilities, total ridership, customer complaints, accidents, deployment costs, as well as locational aspects like the location of employment centers, schools, shopping areas, and so on. These interlacing factors make it difficult to identify optimum improvement locations without the aid of an optimization model. This dissertation proposes two integer programming models to help identify a priority list of bus stops for accessibility improvements. The first is a binary integer programming model designed to identify bus stops that need improvements to meet the minimum ADA requirements. The second involves a multi-objective nonlinear mixed integer programming model that attempts to achieve an optimal compromise among the two accessibility design standards. Geographic Information System (GIS) techniques were used extensively to both prepare the model input and examine the model output. An analytic hierarchy process (AHP) was applied to combine all of the factors affecting the benefits to patrons with disabilities. An extensive sensitivity analysis was performed to assess the reasonableness of the model outputs in response to changes in model constraints. Based on a case study using data from Broward County Transit (BCT) in Florida, the models were found to produce a list of bus stops that upon close examination were determined to be highly logical. Compared to traditional approaches using staff experience, requests from elected officials, customer complaints, etc., these optimization models offer a more objective and efficient platform on which to make bus stop improvement suggestions.

Branch and price solution approach for order acceptance and capacity planning in make -to -order operations

The increasing emphasis on mass customization, shortened product lifecycles, synchronized supply chains, when coupled with advances in information system, is driving most firms towards make-to-order (MTO) operations. Increasing global competition, lower profit margins, and higher customer expectations force the MTO firms to plan its capacity by managing the effective demand. The goal of this research was to maximize the operational profits of a make-to-order operation by selectively accepting incoming customer orders and simultaneously allocating capacity for them at the sales stage. ^ For integrating the two decisions, a Mixed-Integer Linear Program (MILP) was formulated which can aid an operations manager in an MTO environment to select a set of potential customer orders such that all the selected orders are fulfilled by their deadline. The proposed model combines order acceptance/rejection decision with detailed scheduling. Experiments with the formulation indicate that for larger problem sizes, the computational time required to determine an optimal solution is prohibitive. This formulation inherits a block diagonal structure, and can be decomposed into one or more sub-problems (i.e. one sub-problem for each customer order) and a master problem by applying Dantzig-Wolfe’s decomposition principles. To efficiently solve the original MILP, an exact Branch-and-Price algorithm was successfully developed. Various approximation algorithms were developed to further improve the runtime. Experiments conducted unequivocally show the efficiency of these algorithms compared to a commercial optimization solver.^ The existing literature addresses the static order acceptance problem for a single machine environment having regular capacity with an objective to maximize profits and a penalty for tardiness. This dissertation has solved the order acceptance and capacity planning problem for a job shop environment with multiple resources. Both regular and overtime resources is considered. ^ The Branch-and-Price algorithms developed in this dissertation are faster and can be incorporated in a decision support system which can be used on a daily basis to help make intelligent decisions in a MTO operation.^

Branch and Price Solution Approach for Order Acceptance and Capacity Planning in Make-to-Order Operations

The increasing emphasis on mass customization, shortened product lifecycles, synchronized supply chains, when coupled with advances in information system, is driving most firms towards make-to-order (MTO) operations. Increasing global competition, lower profit margins, and higher customer expectations force the MTO firms to plan its capacity by managing the effective demand. The goal of this research was to maximize the operational profits of a make-to-order operation by selectively accepting incoming customer orders and simultaneously allocating capacity for them at the sales stage. For integrating the two decisions, a Mixed-Integer Linear Program (MILP) was formulated which can aid an operations manager in an MTO environment to select a set of potential customer orders such that all the selected orders are fulfilled by their deadline. The proposed model combines order acceptance/rejection decision with detailed scheduling. Experiments with the formulation indicate that for larger problem sizes, the computational time required to determine an optimal solution is prohibitive. This formulation inherits a block diagonal structure, and can be decomposed into one or more sub-problems (i.e. one sub-problem for each customer order) and a master problem by applying Dantzig-Wolfe’s decomposition principles. To efficiently solve the original MILP, an exact Branch-and-Price algorithm was successfully developed. Various approximation algorithms were developed to further improve the runtime. Experiments conducted unequivocally show the efficiency of these algorithms compared to a commercial optimization solver. The existing literature addresses the static order acceptance problem for a single machine environment having regular capacity with an objective to maximize profits and a penalty for tardiness. This dissertation has solved the order acceptance and capacity planning problem for a job shop environment with multiple resources. Both regular and overtime resources is considered. The Branch-and-Price algorithms developed in this dissertation are faster and can be incorporated in a decision support system which can be used on a daily basis to help make intelligent decisions in a MTO operation.

Cooperative routing for collision minimization in wireless sensor networks

Cooperative communication has gained much interest due to its ability to exploit the broadcasting nature of the wireless medium to mitigate multipath fading. There has been considerable amount of research on how cooperative transmission can improve the performance of the network by focusing on the physical layer issues. During the past few years, the researchers have started to take into consideration cooperative transmission in routing and there has been a growing interest in designing and evaluating cooperative routing protocols. Most of the existing cooperative routing algorithms are designed to reduce the energy consumption; however, packet collision minimization using cooperative routing has not been addressed yet. This dissertation presents an optimization framework to minimize collision probability using cooperative routing in wireless sensor networks. More specifically, we develop a mathematical model and formulate the problem as a large-scale Mixed Integer Non-Linear Programming problem. We also propose a solution based on the branch and bound algorithm augmented with reducing the search space (branch and bound space reduction). The proposed strategy builds up the optimal routes from each source to the sink node by providing the best set of hops in each route, the best set of relays, and the optimal power allocation for the cooperative transmission links. To reduce the computational complexity, we propose two near optimal cooperative routing algorithms. In the first near optimal algorithm, we solve the problem by decoupling the optimal power allocation scheme from optimal route selection. Therefore, the problem is formulated by an Integer Non-Linear Programming, which is solved using a branch and bound space reduced method. In the second near optimal algorithm, the cooperative routing problem is solved by decoupling the transmission power and the relay node se- lection from the route selection. After solving the routing problems, the power allocation is applied in the selected route. Simulation results show the algorithms can significantly reduce the collision probability compared with existing cooperative routing schemes.

Optimal Capital Requirements in Financial Networks with Fire Sales

I explore and analyze a problem of finding the socially optimal capital requirements for financial institutions considering two distinct channels of contagion: direct exposures among the institutions, as represented by a network and fire sales externalities, which reflect the negative price impact of massive liquidation of assets.These two channels amplify shocks from individual financial institutions to the financial system as a whole and thus increase the risk of joint defaults amongst the interconnected financial institutions; this is often referred to as systemic risk. In the model, there is a trade-off between reducing systemic risk and raising the capital requirements of the financial institutions. The policymaker considers this trade-off and determines the optimal capital requirements for individual financial institutions. I provide a method for finding and analyzing the optimal capital requirements that can be applied to arbitrary network structures and arbitrary distributions of investment returns.

In particular, I first consider a network model consisting only of direct exposures and show that the optimal capital requirements can be found by solving a stochastic linear programming problem. I then extend the analysis to financial networks with default costs and show the optimal capital requirements can be found by solving a stochastic mixed integer programming problem. The computational complexity of this problem poses a challenge, and I develop an iterative algorithm that can be efficiently executed. I show that the iterative algorithm leads to solutions that are nearly optimal by comparing it with lower bounds based on a dual approach. I also show that the iterative algorithm converges to the optimal solution.

Finally, I incorporate fire sales externalities into the model. In particular, I am able to extend the analysis of systemic risk and the optimal capital requirements with a single illiquid asset to a model with multiple illiquid assets. The model with multiple illiquid assets incorporates liquidation rules used by the banks. I provide an optimization formulation whose solution provides the equilibrium payments for a given liquidation rule.

I further show that the socially optimal capital problem using the ``socially optimal liquidation" and prioritized liquidation rules can be formulated as a convex and convex mixed integer problem, respectively. Finally, I illustrate the results of the methodology on numerical examples and

discuss some implications for capital regulation policy and stress testing.