Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Every beginning of semester higher education institutions face the same dilemma: to assignment courses to classrooms keeping up certain restrictions. This problem is known as Classroom Assignment Problem or Rooms Allocation Problem and consists of allocating courses, with schedules established, at classrooms considering the room capacity and the needs of teachers and students. This process usually is solved manually by the institutions, which can take several days to complete, besides it is hard work and often does not guarantee the efficient allocation of spaces. This reality is also faced by the Technology Center of the Federal University of Santa Maria that due to increasing demand and expansion of the institution needs to adapt to efficiently allocate the available spaces. Currently, the center has 14 undergraduate courses divided into three buildings that have 47 rooms, effectively used, with capacities ranging between 25 and 50 students. Thereby, the aim of this study is to propose a new configuration for the allocation of classrooms in the Technology Center at the Federal University of Santa Maria in order to make the most efficient use of space. Therefore, the study has the support of the precepts of operational research so that a mathematical model was developed to represent the problem. Were used as reference the courses offered in the first and second half of 2014 and from these databases built were coded in ZIMPL and implemented with CPLEX. Because of the problem size, it was decided to split the databases on weekdays and shifts (morning and afternoon) totaling 20 instances. Overall, the results meets the proposed objectives to optimize the spaces and also demonstrated some nonconformities as between the number of vacancies offered by the disciplines and capabilities of rooms. In addition, it was found that there is some imbalance in the supply of disciplines as the days and timeslots, which consequently leads to difficulties for classrooms assignment. Furthermore, it is suggested that further studies are conducted, especially with the use of metaheuristics in order to test the quality of these solutions. / Todo início de semestre letivo as instituições de ensino superior enfrentam o mesmo dilema: o de alocar disciplinas às salas de aula respeitando determinadas restrições. Esse problema é conhecido como Classroom Assignment Problem ou Problema de Alocação de Salas (PAS) e consiste na alocação de disciplinas, com horários já estabelecidos, a salas de aulas considerando-se a capacidade da sala e as necessidades dos docentes e discentes. Esse processo, geralmente, é resolvido pelas instituições de ensino manualmente o que além de levar vários dias para ser concluído muitas vezes não garante a alocação eficiente dos espaços. Tal situação também é a enfrentada pelo Centro de Tecnologia da Universidade Federal de Santa Maria (UFSM) que devido à crescente demanda e expansão da Instituição precisa se adaptar para alocar eficientemente os espaços disponíveis. Atualmente, o Centro conta com 14 cursos de graduação alocados em três prédios que dispõem de 47 salas, efetivamente utilizadas, com capacidades que variam entre 25 e 50 alunos. Sendo assim, este estudo se propôs a desenvolver uma nova configuração para a alocação de salas de aula do Centro de Tecnologia da UFSM a fim de tornar mais eficiente o uso dos espaços. Para tanto o trabalho teve como aporte metodológico os preceitos da pesquisa operacional de modo que foi desenvolvido um modelo matemático para representar o problema. Foram utilizados como referência os dados das disciplinas ofertadas no primeiro e segundo semestre de 2014. De modo geral, os resultados encontrados foram ao encontro dos objetivos propostos de otimizar os espaços e também demostraram algumas inconformidades como entre o número de vagas ofertadas pelas disciplinas e as capacidades das salas. Ademais, sugere-se que novos estudos sejam realizados, em especial com o uso de metaheurísticas, a fim de testar a qualidade das soluções apresentadas.

The main goal of this diploma thesis, called Temporary agency work, is via detailed analysis to provide comprehensive overview of the Institute of agency temporary work in the Czech Republic, to assess the application of the legislation in practice and then compare it with selected EU countries. The main focus of this thesis is on the analysis of current legislation and its history. The diploma thesis is divided into four chapters, further it contains the introduction, the conclusion, the list of abbreviation, the list of pictures/graphs/figures, attachments and the list of literature. The first chapter deals with the legal development of this form of employment assignment not only in the Czech Republic, but also in the EU and international law. The second chapter defines the relationships between parties and describes in detail the process of temporary assignment. The last two chapters are the most important part of this thesis. The third chapter contains description of the application of temporary agency work in selected EU countries - the UK, Germany, France and Sweden. The fourth chapter deals with the practical use of temporary agency work at Vodafone Czech Republic.

The pressure from high population density leads to the creation of high-rise structures within urban areas. Consequently, the design of facilities which confront the challenges of emergency evacuation from high-rise buildings become a complex concern. This paper proposes an embedded program which combines a deterministic (GMAFLAD) and stochastic model (M/G/C/C State Dependent Queueing model) into one program, GMAF_MGCC, to solve an evacuation problem. An evacuation problem belongs to Quadratic Assignment Problem (QAP) class which will be formulated as a Quadratic Set Packing model (QSP) including the random flow out of the building and the random pairwise traffic flow among activities. The procedure starts with solving the QSP model to find all potential optimal layouts for the problem. Then, the stochastic model calculates an evacuation time of each solution which is the primary decision variable to figure the best design for the building. Here we also discuss relevant topics to the new program including the computational accuracy and the correlation between a successful rate of solving and problems’ scale. This thesis examines the relationship of independent variables including arrival rate, population and a number of stories with the dependent variable, evacuation time. Finally, the study also analyzes the probability distribution of an evacuation time for a wide range of problem scale.

I denna uppsats studeras användandet av traditionella och icke-traditionella expatriatuppdrag. Uppsatsens frågeställning är: I vilken utsträckning kan syften med traditionella expatriater uppfyllas av icke-traditionella uppdrag? Detta undersöks genom en kvalitativ studie på ett multinationellt företag som länge arbetat med expatriater. Resultatet visar tydliga exempel på hur externa faktorer samt organisatoriska- och individuella drivkrafter påverkar expatriatuppdrag när det kommer till dess syfte och/eller uppdragstyp. Resultatet visar också att flera av de syften som forskare presenterat för traditionella expatriater identifierats inom vissa icke-traditionella expatriatuppdrag. Utöver detta påträffas syftet att minska risken för konflikter som kan uppstå till följd av kulturella skillnader. Detta visade sig endast kunna uppfyllas av traditionella expatriatuppdrag, vilket motiverar att icke-traditionella uppdrag i liten utsträckning kan uppfylla traditionella uppdrag. Däremot visar studien en pågående trend mot ett minskande av traditionella expatriatuppdrag och en större acceptans gentemot alternativa uppdrag. / This paper aims to examine the employment of traditional long-term and non-standardized expatriate assignments. The question posed is: To what extent can the aims of traditional long-term assignments be reached with non-standardized assignments? To do this, the authors have performed a case study of a multinational company with a long history of employing expatriates. The theoretical framework for the study was devised by focusing on factors considered to affect the purposes and design of expatriate assignments. The results clearly demonstrate, through the examples presented, how external factors, together with organizational and individual motivations, influence the design of expatriate assignments, in terms both of the purpose and the type of assignment chosen. Similar goals with expatriates have been identified within some non-standardized expatriate assignments. Further to discussing these goals, the paper also discusses the aim of reducing the risk of conflict arising through cultural differences. As this only turned out to be relevant in the case of traditional long-term assignments, one may assert that non- standardized assignments can fulfil the goals of traditional long-term assignments to a limited extent only. Furthermore, the study demonstrates an ongoing trend towards a reduction in the use of traditional long-term assignments, and a growing tendency to accept alternative non- standardized assignments.

Föreliggande studie fokuserar på lärares uppdrag i det svenska utbildningsväsendet. Ofta beskrivs detta uppdrag som dubbelt; det innehåller både uppdraget att förmedla och förankra kunskaper och att förmedla och förankra värden. Studiens kunskapsobjekt är lärares förhållningssätt till fostransdelen av lärares uppdrag. Genom en diskursanalys av 118 lärarstudenters reflektioner kring sitt uppdrag undersöks deras förhållningssätt till lärarprofessionen med särskilt avseende på fostransuppdraget. Studiens teoretiska utgångspunkt utgår från att betrakta frågor kring lärares förhållningssätt till fostransuppdraget som en didaktisk fråga, varför studien vilar på teorier inom didaktikens forskningsfält. Resultatet visar att lärarstudenternas förhållningssätt uttrycks genom tre olika diskurser: den tudelade konkurrerande diskursen, den tudelade samverkande diskursen och slutligen den sammanhållna integrerande diskursen.

Plusieurs problématiques de gestion d’opérations peuvent être formalisées avec un problème d’optimisation discret. Ces modèles d’optimisation sont traditionnellement développés sous l’hypothèse que les données d’entrée sont déterministes, non impactées par des changements inattendus ou des incertitudes. Au cours des dernières années, le besoin en modèles performants, incluant des outils efficaces et permettant de réagir de manière optimale aux imprévus (perturbations), n’a cessé de croitre. En phase d’exécution d’un système, plusieurs événements imprévus (incertitudes) peuvent le perturber et le faire dévier de son parcours original voire rendre son exécution impossible. Il est vrai que ces incertitudes peuvent être considérées de manière proactive par le biais d’une optimisation stochastique ou des modèles d'optimisation robustes. Mais même avec des solutions robustes, des événements inattendus peuvent encore se produire nécessitant de revoir le plan robuste en cours d’exécution. Dans cette thèse, l’objectif est de prendre en compte ces incertitudes de manière réactive dans les modèles. Ainsi, une nouvelle méthodologie générique est proposée pour les problèmes d'optimisation de réparation / récupération. En considérant les solutions réparées / récupérées fournies par cette méthodologie appliquée à un plan initial en cours de mise en oeuvre, un décideur peut vouloir minimiser les coûts d'exploitation, mais aussi limiter les changements par rapport au plan initial. Le problème de réparation / récupération est formulé comme un problème d'optimisation multiobjectif, qui minimise des fonctions spécifiques relatives à divers critères de réparation (pilotés par les choix du décideur). / A wide variety of operations management problems can be formulated and solved as discrete optimization problems. Traditionally, these models have been mostly developed and used under the assumption that the input data are known in advance, not subject to unexpected changes, nor impacted by uncertainty. In recent years, the need for improved models providing efficient tools for quickly and optimally reacting to the occurrence of unexpected events (disruptions) has become a more and more important issue. In the execution phase, various unanticipated events will disrupt the system and make the plan deviate from its intended course and even make it infeasible.Uncertainty can be taken into account in a proactive way with stochastic optimization or robust optimization models. However, even with robust solutions, unexpected events can still occur requiring to reconsider the robust plan under execution. In this thesis, we are interested to cope with uncertainty in a reactive way. We propose a new generic methodology for repair/recovery optimization problems. When considering repair/recovery solutions for the initial plan under implementation, the decision-maker may want to minimize operating costs, but also limit the changes with respect to the initial plan. We formulate the repair/recovery problem as a multiobjective optimization problem minimizing specified functions for various repair criteria.

No description available.

The imminent threat of global catastrophe due to climate change gets more real by each passing year. The Aviation trade association, IATA, claims that Aviation accounts for approximately 2% of the Greenhouse Gases (GHG) caused by human activities, and 3.5% of the total Radiative Forcing. With continuous increase in Aviation industry and subsequent drop in fossil fuel prices, these numbers are only expected to up with time. In Addition, these numbers do not include the effects of altitude of emission and many environmentalists believe that the number for some pollutants could be at least 2-3 times larger than IATA estimates. This rising concern engages the Aviation industry to investigate possible methods to alleviate their environmental impact.  The first part of this thesis provides a framework to support Airlines in monitoring their current environmental footprint during the process of scheduling. This objective is realised by developing a robust system for estimating the fuel consumed (ergo quantity of major Greenhouse Gases emitted) by a particular fleet type operating a certain leg, which is then employed in a Fleet Assignment (FA) Operation to reduce emissions and increase the Contribution. An emissions estimation model for Turbojet Aeroplane fleets is created for Industrial Optimizers AB’sMP2 software. The emissions estimation model uses historic fuel consumption data provided by ICAO for a given fleet type to estimate the quantity (in kg) of environmental pollutants during the Landing and Takeoff operation (below 3000 ft) and the Cruise, Climb and Descent operation (above 3000 ft).  The second part of this thesis concerns with assigning monetary weights to the pollutant estimates to calculate an emission cost. This emission cost is then added to MP2’s Fleet Assignment’s objective function as an additional Operational cost to perform a Contribution maximization optimization subjected to the legality constraints. The effects of these monetary weights levied on the results of Fleet Assignment are studied, and utilizing curve-fitting and mathematical optimization, monetary weights are estimated for the desired reduction in GHG emissions.  Finally, a recursive algorithm based on Newton-Raphson method is designed and tested for calculating pollutant weights for untested schedules. / Det omedelbara hotet om en global katastrof pga klimatförändringar blir mer och mer tydligt för varje år som går. IATA, den internationella flyghandelsorganisationen, hävdar att flyget står för runt 2% av växthusgaserna (GHG) som kommer från människans aktiviteter, och 3.5% av den totala avstrålningen. Med den kontinuerliga tillväxten av flygindustrin och prisminskningar av fossila bränslen så förväntas dessa andelar att öka. Dessutom så inkluderar inte dessa siffror effekten av att utsläppen sker på hög höjd, och många miljöaktivister tror att siffrorna för vissa utsläpp kan vara åtminstone 2-3 gånger högre än IATAs uppskattningar. Denna växande oro motiverar flygindustrin till att undersöka metoder för att begränsa dess miljöpåverkan.  Den första delen av denna rapport ger ett ramverk för att hjälpa flygbolag med att bevaka deras aktuella miljöavtryck under schemaläggningsprocessen. Detta mål realiseras genom att utveckla ett robust system för att uppskatta bränsleförbrukningen (och därmed kvantiteten av växthusgasutsläpp) av en specifik flygplanstyp på en given etapp, som sedan kan användas för att allokera flygplanstyper för att minska utsläppen och bidra till att förbättra miljön. En modell för att uppskatta utsläpp för flottor av turbojetflygplan har skapats för Industrial Optimizers AB programvara MP2. Modellen för att uppskatta utsläppen baseras på historiska data om bränsleförbrukning som tillhandahållits av ICAO för en given flygplanstyp som använts för att uppskatta kvantiteten (i kg) av föroreningar vid start (under 3000 fot) och vid sträckflygning, stigning och inflygning (över 3000 fot). Den andra delen av denna rapport handlar om att bestämma monetära vikter till föroreningsskattningarna för att beräkna utsläppskostnader som ska användas i MP2 s målfunktion för allokering av flygplanstyper. Detta ger en ytterligare driftskostnad att beakta i optimeringen för att få med miljöaspekterna och tillåtna lösningar. Effekten som dessa monetära vikter har på resultaten från optimeringen studeras, och genom att använda kurvanpassning och matematisk optimering, de monetära vikterna anpassas för att få den önskade minskningen i växthusgasutsläpp. Slutligen så har en rekursiv algoritm, baserad på Newon-Raphsons metod, designats och testats för att beräkna utsläppsvikter för scheman som inte använts för att beräkna vikterna

<p>This dissertation examines the interplay between school district assignment and reassignment policies and the elementary public school parents select for their children. The sample in all chapters includes the third and fourth grade students in a subset of growing North Carolina school districts from 2003/04 to 2010/11. The data are derived from historical, longitudinal secondary data sources containing student, school, and district records. All chapters employ quantitative longitudinal data analysis methods. Chapter 1 identifies the groups of students who do not comply with their school assignments. Chapter 2 identifies the groups of students who are reassigned to different schools, and to schools of varying quality, when school districts enact reassignment plans. Chapter 3 identifies the groups of students who do not comply with school reassignments. Together, the chapters demonstrate the interplay between residential decisions, school choices, and the resulting educational opportunities of observably different students. Consistent with existing bodies of literature, the findings demonstrate unexplored processes through which advantaged families maintain the most desirable educational opportunities for their children. Policy implications of these findings are also discussed.</p> / Dissertation

This dissertation addresses resource allocation problems that occur in both public and private health care settings with the objective of characterizing the tradeoffs that occur when simultaneously incorporating multiple objectives and developing methods to address these tradeoffs. We examine three resource allocation problems (i) strategic allocation of financial resources and limited staffing capacity for the mobile delivery of health care within African countries, (ii) real-time allocation of hospital beds to internal patient requests, and (iii) development of patient redirection policies in response to limited bed availability in units within a system of hospitals. For each problem we define models, each with a different methodology, and utilize the models to develop allocation strategies that account for multiple competing objectives and examine the performance of the strategies with computational studies. In Chapter 2, we model African health care delivery systems utilizing a mixed-integer program (MIP) which accounts for financial and personnel constraints as well as infrastructure quality. We characterize tradeoffs in effectiveness, efficiency, and equity resulting from four allocation strategies with computational experiments representing the variety of spatial patterns that occur throughout the continent. The main contributions include (i) the development of a model that incorporates spatial and infrastructure characteristics and allows for a study of equity in the delivery of care, rather than access to care, and (ii) the characterization of tradeoffs in the three objectives under a variety of settings. In Chapter 3, we model the real-time assignment of bed requests to available beds as a queueing system and a Markov decision process (MDP). Through the development of bed assignment algorithms and simulation experiments, we illustrate the value of implementing strategic bed assignment practices which balance the bed management objectives of timeliness and appropriateness of assignments. The main contributions of this section include (i) the development of new bed assignment algorithms which use stochastic optimization techniques and outperform algorithms which mimic processes currently used in practice and (ii) the definition of a model and methods for the control of a large complex system that includes flexible units, multiple patient types, and type-dependent routing. In Chapter 4, we model the impact of a patient redirection policy in a hospital unit as a Markov chain. Assuming preferences for patient redirection are aligned with costs, we examine the impact of incremental changes to redirection policies on the probability of the unit being completely occupied, the long-run average utilization, and the long-run average cost of redirection. The main contributions of this chapter include (i) the introduction of a model of patient redirection with multiple patient thresholds and patient preference constraints and (ii) the definition of necessary conditions for an optimal patient redirection policy that minimizes the average cost of redirection.