The implementation of the mandatory alternative payment model (APM) guarantees savings for Medicare regardless of participant hospitals ability for reducing spending that shifts the cost minimization burden from insurers onto the hospital administrators. Surgical interventions account for more than 30% and 40% of hospitals total cost and total revenue, respectively, with a cost structure consisting of nearly 56% direct cost, thus, large cost reduction is possible through efficient operation management. However, optimizing operating rooms (ORs) schedules is extraordinarily challenging due to the complexities involved in the process. We present new algorithms and managerial guidelines to address the problem of OR planning and scheduling with disturbances in demand and case times, and inconsistencies among the performance measures. We also present an extension of these algorithms that addresses production scheduling for sustainability. We demonstrate the effectiveness and efficiency of these algorithms via simulation and statistical analyses.

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Results found in this thesis draw attention to limitations in the conventional approach to modelling forest management strategy, where models have insufficient spatial resolution and ignore industry. Addressing these limitations, a Model One linear programming framework was developed in which models built can model strategically relevant spatial resolution, and include industry representation. In a case-study on Nova Scotia's Crown Central Forest, models from this framework were compared with Woodstock\texttrademark, a commercial modelling framework. When strategically relevant spatial resolution was modelled, these models found solutions in substantially less time than Woodstock. Of further interest, the framework's industry representation allows novel analysis to be performed. A comparison between a model that includes industry and a conventional model demonstrates that the conventional model schedules unprofitable stands for harvest. Then, models with industry representation are used to demonstrate industry based analysis, such as assessing the cost of a clearcut restriction policy and investigating the benefit of industrial expansion. Taken together, the results herein contained make an argument for modelling forest management strategy at strategically relevant spatial resolution, and including industry representation in modelling.

Made available in DSpace on 2014-06-11T19:26:18Z (GMT). No. of bitstreams: 0 Previous issue date: 2011-06-15Bitstream added on 2014-06-13T19:25:33Z : No. of bitstreams: 1 franco_bc_me_guara.pdf: 1492178 bytes, checksum: 2c201ad6660278573573b0b255349982 (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Esta pesquisa propõe o planejamento econômico de gráficos de controle ̅ para o monitoramento de uma característica de qualidade na qual as observações se ajustam a um modelo autorregressivo de primeira ordem com erro adicional. O modelo de custos de Duncan é usado para selecionar os parâmetros do gráfico, tamanho da amostra, intervalo de amostragem e os limites de controle. Utiliza-se o algoritmo genético na busca do custo mínimo de monitoramento. Para determinação do número médio de amostras até o sinal e o número de alarmes falsos são utilizadas Cadeias de Markov. Uma análise de sensibilidade mostrou que a autocorrelação provoca efeito adverso nos parâmetros do gráfico elevando seu custo de monitoramento e reduzindo sua eficiência / This research proposes an economic design of a ̅ control chart used to monitor a quality characteristic whose observations fit to a first-order autoregressive model with additional error. The Duncan's cost model is used to select the control chart parameters, namely the sample size, the sampling interval and the control limit coefficient, using genetic algorithm in order to search the minimum cost. The Markov chain is used to determine the average number of samples until the signal and the number of false alarms. A sensitivity analysis showed that the autocorrelation causes adverse effect on the parameters of the control chart increasing monitoring cost and reducing significantly their efficiency

Étant donnés un planning aérien et des prévisions de demande, le problème d'affectation de flotte aérienne consiste à déterminer la meilleure façon de répartir les types d'appareils sur les vols. Cette répartition a un impact majeur sur le profit d'une compagnie aérienne, puisqu'elle détermine les quantités de places disponibles sur les itinéraires du réseau aérien, ainsi que le coût de fonctionnement de celui-ci. Des décennies de recherche ont rendues les modélisations de ce problème de plus en plus réalistes. Cette thèse s'inscrit dans la continuité de ces recherches en considérant le problème d'affectation de flotte dans un contexte où les demandes des passagers sont incertaines. Nous proposons dans un premier temps une étude autour des deux modèles de la littérature les plus utilisés dans l'industrie, FAM et IFAM. Nous montrons que FAM peut être vu comme une Relaxation Lagrangienne de IFAM, avec des multiplicateurs Lagrangiens particuliers. Nous implémentons cette relaxation, et nous appliquons des résultats connus pour l'étendre en une génération de colonnes basée sur une décomposition de Dantzig-Wolfe de IFAM. Nous étudions ensuite les effets que l'imprécision des prévisions peut avoir sur la performance d'IFAM, et nous présentons au terme de cette étude une nouvelle approche pour modéliser le problème d'affectation de flotte. Notre modèle, Market Driven Fleet Assignment Model (MDFAM), intègre les demandes par itinéraires comme variables de décision, et contraint ces demandes plutôt que de les considérer comme une entrée fixe. Nous appelons les contraintes résultantes des contraintes de Marché. Nous illustrons la flexibilité de cette approche à travers divers exemples, et nous proposons une série d'expériences visant à déterminer quelles sont les contraintes de marché donnant les meilleurs résultats. Nous comparons les différents modèles, et nous montrons que MDFAM peut atteindre des niveaux de performance similaires à ceux offert par IFAM, tout en étant plus facile à utiliser et à implémenter. / Given an airline schedule and demand forecasts, the Fleet Assignment Problem consists in determining how to assign aircraft types to flight legs in the best possible way. This assignment has a major impact on the profit of an airline, since it determines the quantities of seats available over the itineraries of the flight network, along with the associated operating cost. Decades of research on this problem have improved the formulations to be more and more realistic. This thesis extends the ongoing work, considering the problem of doing Fleet Assignment taking demand volatility into account. We first propose a study involving the two models of the literature that are the most widely used by the industry, FAM and IFAM. We show that FAM can be seen as a Lagrangian Relaxation of IFAM, with particular Lagrangian multipliers. We implement this relaxation, and we apply known results to extend it in a column generation based on a Dantzig-Wolfe decomposition of IFAM. We then study the effects of forecasts inaccuracy over the performance of IFAM, and we present a novel approach for modeling the Fleet Assignment Problem. Our model, Market Driven Fleet Assignment Model (MDFAM), makes the itinerary demands part of the decision variables. We propose to constraint these variables rather than consider them as a fixed input of the problem, and we call the resulting constraints Market Constraints. We illustrate the flexibility of this approach through various examples, and we provide a series of experiments in order to determine which Market Constraints give the best results. We compare the different models, and we show that MDFAM can reach a performance which is similar to IFAM's, while being easier to use and to implement.

Esta tese estuda a implementação de heurísticas e da metaheurística scatter search (SS) em um problema de roteirização de veículos com frota heterogênea, janelas de tempo e entregas fracionadas (Heterogeneous Fleet Vehicle Routing Problem with Time Windows and Split Deliveries – HFVRPTWSD). O HFVRPTWSD é uma combinação do problema de roteirização com frota heterogênea (HFVRP), problema de roteirização de veículos com janelas de tempo (VRPTW) e problema de roteirização com entregas fracionadas (VRPSD). O problema é baseado em um único depósito, a demanda dos clientes pode ser maior que a capacidade dos veículos e, além das restrições de janelas de tempo, há também restrições de capacidade dos veículos e restrições quanto ao tipo de veículo. O VRPSD foi introduzido na literatura por Dror e Trudeau em 1989. No problema de roteirização de veículos com entregas fracionadas, cada cliente pode ser abastecido por mais de um veículo, enquanto no problema clássico de roteirização de veículos (VRP), cada cliente é atendido por um único veículo. Desta forma, para o VRPSD, além dos roteiros de entrega, deve-se determinar a quantidade entregue a cada cliente em cada veículo. Todos os problemas de roteirização com entregas fracionadas encontrados na literatura (VRPSD e suas extensões) têm como característica frota homogênea. O problema estudado neste trabalho difere, portanto, de todos os problemas de roteirização com entregas fracionadas da literatura, pois tem, como característica, frota heterogênea. O mesmo raciocínio vale para problemas de roteirização de veículos com frota heterogênea. Os modelos são aplicados em uma rede de varejo no Brasil que é abastecida a partir de um centro de distribuição. A rede compõe um total de 519 lojas distribuídas em 12 estados do país. As heurísticas e a metaheurística scatter search também são aplicadas em três conjuntos de problemas encontrados na literatura (SOLOMON, 1987; HO E HAUGLAND, 2004; LIU E SHEN, 1999), com o objetivo de avaliar o desempenho dos algoritmos para cada problema. O problema consiste em determinar, a cada dia, como alocar os caminhões às lojas, a quantidade de carga em cada caminhão a ser entregue em cada uma das lojas, qual o melhor roteiro e o tempo de início de atendimento do primeiro cliente da rota, de forma a minimizar o custo total de distribuição, garantindo que a demanda das lojas seja atendida e as demais restrições do problema sejam respeitadas. Para a resolução do VRPSD e suas extensões, a única metaheurística encontrada na literatura foi busca tabu. Para o problema de roteirização com frota heterogênea e suas extensões, foram implementadas apenas as metaheurísticas busca tabu e BATA (Back-Tracking Adaptative Threshold Accepting). As estratégias de solução propostas no presente trabalho consistem na implementação de heurísticas construtivas e da metaheurística scatter search. As soluções iniciais de SS são obtidas através da implementação de quatro heurísticas construtivas: heurística de economias, heurística de inserção seqüencial baseada nas idéias de Solomon (1987), heurística de inserção seqüencial baseada nas idéias de Ho e Haugland (2004) e adaptação da heurística de inserção seqüencial de Dullaert et al. (2002). Para o caso real, foi possível uma redução no custo total da frota comparado com a solução atual da empresa. Para algumas instâncias dos três conjuntos de problemas da literatura, os algoritmos apresentaram resultados similares ou superiores às melhores soluções encontradas. / This thesis studies the implementation of heuristics and scatter search (SS) metaheuristic in a Heterogeneous Fleet Vehicle Routing Problem with Time Windows and Split Deliveries (HFVRPTWSD). The HFVRPTWSD is a combination of Heterogeneous Fleet Vehicle Routing Problem (HFVRP), Vehicle Routing Problem with Time Windows (VRPTW) and Vehicle Routing Problem with Split Deliveries (VRPSD). The problem is based in a single depot, the demand of each client can be greater than the vehicle’s capacity and beyond the time windows constraints, and there are also constraints on the vehicle capacity and vehicles type. The VRPSD was introduced in the literature by Dror e Trudeau in 1989. In the split deliveries vehicle routing problem, each client can be supplied by more than one vehicle; while in a classic vehicle routing problem (VRP) each client is supplied by only one vehicle. Thus, for the VRPSD, besides the delivery routes, the amount to be delivered to each client in each vehicle must also be determined. All the split delivery vehicle routing problems researched in the literature (VRPSD and its extensions) have as a characteristic the homogeneous fleet. Therefore, the problem studied differs from the split deliveries vehicle routing problems of the literature because it has a heterogeneous fleet. The same reasoning can be applied in heterogeneous fleet vehicle routing problem. The models will be applied in a retail market in Brazil that is supplied by a distribution center. The market has 519 stores distributed in 12 Brazilian states. The heuristics and the scatter search metaheuristic will also be applied in three benchmark problems (SOLOMON, 1987; HO AND HAUGLAND, 2004; LIU AND SHEN, 1999), aiming to evaluate the design of the algorithms for each problem. The problem consists in determining, each day, how to allocate the trucks to the stores, the amount to be delivered in each truck to each client, which one is the best route and the initial time for attending the first client, with the aim of minimizing the total distribution cost, attending the clients’ demand and respecting all the problem’s constraints. For the VRPSD and its extensions, the only metaheuristic implemented in the literature was tabu search. For the heterogeneous fleet vehicle routing problem and its extensions, only the tabu search and BATA (Back-Tracking Adaptative Threshold Accepting) metaheuristics have been implemented. The strategies proposed here consist in the implementation of constructive heuristics and the scatter search metaheuristic. The initial solutions of SS are obtained with the implementation of four constructive heuristics: saving heuristics, sequential insertion heuristic based on the ideas of Solomon (1987), sequential insertion heuristic based on the ideas of Ho e Haugland (2004) and adaptation of the sequential insertion heuristic of Dullaert et al. (2002). For the real case, it was possible to reduce the total fleet cost, when comparing to the actual solution. At some instances of the three benchmark problems, the algorithms presented similar or better results when compared to the best solutions in the literature.

Este trabalho detalha o problema de programação de atividades de desenvolvimento de poços marítimos (PPADPM), cujo objetivo é definir o uso de sondas e navios, de forma a otimizar a produção de óleo dos poços marítimos. São apresentados cinco modelos baseados em programação linear-inteira mista (MILP) e um modelo gerado via programação por restrições (PR) para este problema. Concluiu-se que, dentre os modelos MILP, aquele baseado em variáveis que definem a ordem de execução das atividades apresenta os melhores resultados, tanto em termos de qualidade de soluções quanto em termos de tamanho do modelo. O aumento do tamanho da instância (em número de poços e/ou em número de recursos) traz como consequência um menor número de nós analisados dentro de um tempo limite de execução do modelo, ao mesmo tempo em que se observa que as estratégias de escolha de variáveis, de escolha de nós e de uso de solução inicial nos modelos MILP tornam-se ineficientes. Na comparação entre modelos MILP e o modelo baseado em PR, constatou-se que este último obteve as melhores soluções em mais de 90% dos casos analisados e, consistentemente, obteve mais soluções viáveis para cada instância. Entretanto, por não fornecer informações sobre a qualidade da solução, o modelo baseado em PR somente obtém a solução ótima ao analisar todo o espaço de busca do modelo; desta forma, este apenas chegou à solução ótima em instâncias com até quatro poços, enquanto alguns dos modelos MILP obtiveram a solução ótima para instâncias com até treze poços. / This work details the offshore wells activities on specialized resources scheduling problem, focusing on the optimization of the total oil production. A Constraint Programming (CP) model and five Mixed-Integer Linear Programming (MILP) models were studied. Among the linear models, those based on activities order variables are smaller, and led to the better solutions for almost all of the instances analyzed. As far as the size of the instances (number of wells and/or number of resources) increases, the number of branched nodes in a limited time decreases and, consequently, the influence of B&B nodes and variable selection strategies and of the initial guesses on the MILP model solution gets less efficient. Comparing best solutions for each instance, the CP model outperformed MILP models in 90% of the studied cases. In addition, the CP based model consistently found more solutions per instance than the MILP based models did. However, because the CP model does not give information on the quality of a solution (gap), it was only able to obtain optimal solutions for instances with up to four wells, while MILP based models found optimal solutions for instances up to thirteen wells.

In this thesis, and complex real world problem, a sequence dependent scheduling of different product orders on a number of lines is addressed. Changeover costs occur between product orders belonging to different product groups. The operational research cycle is employed exploring different optimization techniques as mathematical modelling and heuristic approaches. The identification, implementation and demonstration of the techniques are supported with numerical results from experiments. One combination of different solution techniques is put forward. Some suggestions are done for reducing cost and increasing productivity.

An expert elicitation is a method of eliciting subjective probability distributions over key parameters from experts. Traditionally an expert elicitation has taken the form of a face-to-face interview; however, interest in using online methods has been growing. This thesis compares two elicitation modes and examines the effectiveness of an interactive online survey compared to a face-to-face interview. Differences in central values, overconfidence, accuracy and satisficing were considered. The results of our analysis indicated that, in instances where the online and face-to-face elicitations were directly comparable, the differences between the modes was not significant. Consequently, a carefully designed online elicitation may be used successfully to obtain accurate forecasts.

Natural and man-made disasters are becoming more frequent in many countries throughout the world. Countries with inadequate infrastructure and poorly planned emergency logistics are subject to such events which may lead to the destruction of a community and/or may prevent e cient and successful recovery. Despite the progress that disaster planning, mitigation and new management systems have made, the need for disaster relief continues everlasting. Extensive research is on-going to improve the various phases in the disaster operations life cycle. However, the impact of disaster will not diminish and improved disaster relief planning and management should be addressed intensely. This dissertation addresses various possible mathematical models comprising stochastic and deterministic models, to provide generic means to address the damage and consequences associated with disaster events. The models are applied to countries such as Somalia and the Southern African Development Community (SADC), which have been prone to catastrophic events and poverty consequences. / Dissertation (MEng)--University of Pretoria, 2012. / Industrial and Systems Engineering / unrestricted