This thesis is done to solve two issues for Sayid Paper Mill Ltd Pakistan. Section one deals with a practical problem arise in SPM that is cutting a given set of raw paper rolls of known length and width, and a set of product paper rolls of known length (equal to the length of raw paper rolls) and width, practical cutting constraints on a single cutting machine, according to demand orders for all customers. To solve this problem requires to determine an optimal cutting schedule to maximize the overall cutting process profitability while satisfying all demands and cutting constraints. The aim of this part of thesis is to develop a mathematical model which solves this problem.Second section deals with a problem of delivering final product from warehouse to different destinations by finding shortest paths. It is an operational routing problem to decide the daily routes for sending trucks to different destination to deliver their final product. This industrial problem is difficult and includes aspect such as delivery to a single destination and multiple destinations with limited resources. The aim of this part of thesis is to develop a process which helps finding shortest path.

The asymmetric distance-constrained vehicle routing problem (ADVRP) looks at finding vehicle tours to connect all customers with a depot, such that the total distance is minimised; each customer is visited once by one vehicle; every tour starts and ends at a depot; and the travelled distance by each vehicle is less than or equal to the given maximum value. We present three basic results in this thesis. In the first one, we present a general flow-based formulation to ADVRP. It is suitable for symmetric and asymmetric instances. It has been compared with the adapted Bus School Routing formulation and appears to solve the ADVRP faster. Comparisons are performed on random test instances with up to 200 customers. We reach a conclusion that our general formulation outperforms the adapted one. Moreover, it finds the optimal solution for small test instances quickly. For large instances, there is a high probability that an optimal solution can be found or at least improve upon the value of the best feasible solution found so far, compared to the other formulation which stops because of the time condition. This formulation is more general than Kara formulation since it does not require the distance matrix to satisfy the triangle inequality. The second result improves and modifies an old branch-and-bound method suggested by Laporte et al. in 1987. It is based on reformulating a distance-constrained vehicle routing problem into a travelling salesman problem and uses the assignment problem as a lower bounding procedure. In addition, its algorithm uses the best-first strategy and new branching rules. Since this method was fast but memory consuming, it would stop before optimality is proven. Therefore, we introduce randomness in choosing the node of the search tree in case we have more than one choice (usually we choose the smallest objective function). If an optimal solution is not found, then restart is required due to memory issues, so we restart our procedure. In that way, we get a multistart branch and bound method. Computational experiments show that we are able to exactly solve large test instances with up to 1000 customers. As far as we know, those instances are much larger than instances considered for other VRP models and exact solution approaches from recent literature. So, despite its simplicity, this proposed algorithm is capable of solving the largest instances ever solved in literature. Moreover, this approach is general and may be used in solving other types of vehicle routing problems. In the third result, we use VNS as a heuristic to find the best feasible solution for groups of instances. We wanted to determine how far the difference is between the best feasible solution obtained by VNS and the value of optimal solution in order to use the output of VNS as an initial feasible solution (upper bound procedure) to improve our multistart method. Unfortunately, based on the search strategy (best first search), using a heuristic to find an initial feasible solution is not useful. The reason for this is because the branch and bound is able to find the first feasible solution quickly. In other words, in our method using a good initial feasible solution as an upper bound will not increase the speed of the search. However, this would be different for the depth first search. However, we found a big gap between VNS feasible solution and an optimal solution, so VNS can not be used alone unless for large test instances when other exact methods are not able to find any feasible solution because of memory or stopping conditions.

Includes bibliographical references (pages 165-169). / Classical Statistical Process Control Charts are essential in Statistical Control exercises and thus constantly obtained attention for quality improvements. However, the establishment of control charts requires large-sample data (say, no less than I 000 data points). On the other hand, we notice that the small-sample based Grey System Theory Approach is well-established and applied in many areas: social, economic, industrial, military and scientific research fields. In this research, the short time trend curve in terms of GM( I, I) model will be merged into Shewhart and CU SUM two-sided version control charts and establish Grey Predictive Shewhart Control chart and Grey Predictive CUSUM control chart. On the other hand the GM(2, I) model is briefly checked its of how accurate it could be as compared to GM( I, 1) model in control charts. Industrial process data collected from TBF Packaging Machine Company in Taiwan was analyzed in terms of these new developments as an illustrative example for grey quality control charts.

Staff scheduling is one of the most important challenges that every healthcare organization faces. Long wait times due to the lack of care providers, high salary costs, rigorous work regulations, decreasing workforce availability, and other similar difficulties make it necessary for healthcare decision-makers to pay special attention to this crucial part of their management activities. Staff scheduling decisions can be very difficult. At inpatient clinics, there is not always a good estimate of the demand for services and patients can be discharged at any given time, consequently affecting staff requirements. Moreover, there are many other unpredictable factors affecting the decision process. For example, various seasonal patterns or possible staff leaves due to sickness, vacations, etc. This research describes a solution approach for staff scheduling problems at inpatient clinics where demand for services and patient discharges are considered to be stochastic. The approach is comprehensive enough to be generalizable to a wide range of different inpatient settings with different staff requirements, patient types, and workplace regulations. We first classify patients into a number of patient groups with known care-provider requirements and then develop a predictive model that captures patients’ flow and arrivals for each patient category in the inpatient clinic. This model provides a prediction of the number of patients of each type on each specific day of the planning horizon. Our predictive modelling methodology is based on a Discrete Time Markov model with the number of patients of different types as the state of the system. The predictive model generates a potentially large set of possible scenarios for the system utilization over the planning horizon. We use Monte Carlo Simulation to generate samples of these scenarios and a well known Stochastic Optimization algorithm, called the Sample Average Approximation (SAA) to find a robust solution for the problem across all possible scenarios. The algorithm is linked with a Mixed-Integer Programming (MIP) model which seeks to find the optimal staff schedule over the planning horizon while ensuring maximum demand coverage and cost efficiency are achieved. To check the validity of the proposed approach, we simulated a number of scenarios for different inpatient clinics and evaluated the model’s performance for each of them.

Twenty-four independent logging businesses in the Southeastern United States were analyzed in a general systems approach to document the components of logging costs for mechanized operations, assess the sensitivity of these components to external stimuli, and to identify and describe the business management techniques adopted by contractors to insure survival and profitability. The contractors' cost records for 1988 and 1989 were analyzed to meet the study's first two objectives and interviews with each participant facilitated identification of survival and profitability strategies. The general interviews and on-site observations of the harvesting systems provided background information for evaluating the costs and identifying business management techniques. The contractors' records were summarized into six cost components: 1) consumable supplies, 2) labor, 3) equipment,4) insurance. 5) contract hauling, and 6) administrative overhead. Contractors were stratified by trucking strategy, ranging from those who hauled all of their own wood to contractors relying exclusively on contract truckers. Consumable supplies, labor, and equipment accounted for approximately 75% of total costs for the average contractor in 1988 and 1989. The concept of excess logging capacity was evaluated. Analyses indicate that excess capacity exists in many areas of the Southeastern U.S., and excess capacity influences cost structures and survival strategies. Discussion with most contractors and evaluation of direct costs of excess capacity indicated that contractors are unable to achieve marginal efficiencies due to the large number of suppliers in some areas. Four major business survival strategies were identified during the study. Equity dissolution and diversification were the prevalent strategies, suggesting that the late 1980s and early 1990s favor harvesting systems that are downwardly elastic in terms of production. / Master of Science

Dieser Beitrag basiert auf einer Planungshierarchie zur Produktionsplanung und -steuerung, die üblicherweise in der industriellen Praxis verwendet wird. In der Produktionsprogrammplanung werden meist deterministische Planungsparameter unterstellt. Tatsächlich sind insbesondere die Bedarfe zum Planungszeitpunkt nicht bekannt und somit unsicher. Zur Berücksichtigung dieser Unsicherheit wird in der aktuellen Forschung insbesondere die szenariobasierte robuste Optimierung verwendet. In diesem Forschungsvorhaben wird untersucht, wie eine robuste Produktionsprogrammplanung in einer solchen Planungshierarchie eingesetzt werden kann.

Dieser Beitrag basiert auf einer Planungshierarchie zur Produktionsplanung und -steuerung, die üblicherweise in der industriellen Praxis verwendet wird. In der Produktionsprogrammplanung werden meist deterministische Planungsparameter unterstellt. Tatsächlich sind insbesondere die Bedarfe zum Planungszeitpunkt nicht bekannt und somit unsicher. Zur Berücksichtigung dieser Unsicherheit wird in der aktuellen Forschung insbesondere die szenariobasierte robuste Optimierung verwendet. In diesem Forschungsvorhaben wird untersucht, wie eine robuste Produktionsprogrammplanung in einer solchen Planungshierarchie eingesetzt werden kann.

This study investigates the revenue performance of choice-based revenue management (RM) systems in various business environments. Previous research conducted using simulated data suggests that incremental revenue gains of up to 15% are to be expected when choice-based RM techniques are employed. In addition, despite the novelty of these techniques, the implementation of choice-based RM systems is considered to be feasible at large global corporations. The revenue potential and the ease of execution associated with the choice-based methods are examined in the context of a large hotel chain. Customer-centric data which includes transaction and time of booking availability information is collected for five hotel properties located in the continental US. The customer preference for hotel products and their attributes is determined using discrete choice and other ad hoc models of demand. Optimization techniques that account for the customer purchasing behavior are employed to compute the capacity control policies the hotel operator should follow to maximize its revenues. Results indicate that collecting customer-centric data from today s RM systems is a time-consuming task. In the environment in which the study hotels operate, the choice-based RM systems report incremental revenue gains that are dependent on how the purchasing behavior models are formulated. In capacity constrained regimes that are the focus of RM, revenue gains of up to 2% are typically noted. In controlled environments in which the customer purchasing behavior can be better asserted, the incremental revenue gains range between 1% and 14%. These findings suggest that the execution of the choice-based RM, while feasible, needs to be preceded by the implementation of efficient and, most likely, expensive data collection procedures. The incremental revenue gains, consistent with those reported in the literature, indicate that RM users can substantially benefit from the use of the choice-based RM.

Παρουσιάζονται υπολογιστικά μοντέλα τα οποία κατά το παρελθόν έχουν αναλυθεί από διάφορους μελετητές και τα οποία σχετίζονται άμεσα με θέματα δρομολόγησης αεροσκαφών, προγραμματισμού συντηρήσεων αεροσκαφών, καθώς και με τον ημερήσιο και τον μακροχρόνιο προγραμματισμό εργασιών σε στόλο αεροσκαφών αεροπορικών εταιρειών. Στο τέλος της εργασίας γίνεται μια επιλογή ενός εκ των παρουσιασθέντων υπολογιστικών μοντέλων λαμβάνοντας υπόψη τα θετικά και τα αρνητικά σημεία καθ’ ενός από αυτά. Και βέβαια πάντα με σημείο αναφοράς το εξεταζόμενο θέμα, της δρομολόγησης και του προγραμματισμού συντηρήσεων των αεροσκαφών μιας αεροπορικής εταιρείας. Και στο τελευταίο κεφάλαιο, έχοντας επιλέξει και αιτιολογήσει την επιλογή του καταλληλότερου, για την περίπτωσή μας, υπολογιστικού μοντέλου προχωρούμε στην εφαρμογή του με την χρήση του γνωστού υπολογιστικού πακέτου Premium Solver. / Presented computational models that previously have been analyzed by scholars and directly related to issues of aircraft routing, scheduling, aircraft maintenance, and daily and long term planning work on fleet of aircraft carriers. At the end of the work it is selected one of the presented computational models taking into account the positive and negative points of it. And at the last chapter,there are presented the reasons why we did that selection of the model and finally we proceed in the implementation of it using Premium Solver Platform and MS Excel.

Made available in DSpace on 2016-06-02T19:53:32Z (GMT). No. of bitstreams: 1 OLIVEIRA_Maritha_2014.pdf: 2487873 bytes, checksum: 7439c2c5d512e86e156f928f8d62ca37 (MD5) Previous issue date: 2014-04-04 / Financiadora de Estudos e Projetos / The purpose of this work is to study the configuration of the reverse logistical chain post consumption of the computer equipments from the project called "Computadores para a Inclusão" from the Federal Government (MINISTÉRIO DAS COMUNICAÇÕES, 2012). The motivations for the development of this study are the logistical challenges inherent to the disposal of solid human residues, which involve the compromising of society, government and private companies. Particularly, in the case of the electronic equipments, besides the legal aspects foreseen in the Política Nacional de Resíduos Sólidos (PNRS) the opportunities of value recovery for the products are relevant and may increase it´s life cycle. The computer equipments, for example, may be recovered at the Centro de Recondicionamento de Computadores (CRC) which are located where the computers are reconditioned and then made available for needy communities to use. The CRCs belong to the Computers for Inclusion project. One of the difficulties in planning this project is configuring the logistics network, which consists of: (i)defining the computers discharge points; (ii) locating the reconditioning centers, considering the existing places and the possibility of expanding; (iii) in determining the amount of computers present in Telecentros respecting the maximum and minimum number of computers; and (iv) defining the material flow amongst the discharge points, CRCs, Telecentros and the final destination points. In this context, the approach of this study is to propose a mathematical model to help the configuration of the logistical network of the Computadores para a Inclusão" project, contributing to the gathering and appropriate destination of the computer equipments post consumption in all national territory. / O objetivo deste trabalho é o estudo da configuração da rede de logística reversa pós-consumo de equipamentos de informática do projeto intitulado "Computadores para a Inclusão" do Governo Federal (MINISTÉRIO DAS COMUNICAÇÕES, 2012). A motivação para desenvolvimento do trabalho são os desafios logísticos inerentes ao descarte de resíduos sólidos urbanos, que envolvem o comprometimento entre sociedade, governo e empresas privadas. Particularmente, no caso de equipamentos eletroeletrônicos, além dos aspectos legais previstos no Plano Nacional de Resíduos Sólidos (PNRS), as oportunidades de recuperação de valor para os produtos são relevantes e podem aumentar sua vida útil. Os equipamentos de informática, por exemplo, podem ser recuperados nos Centros de Recondicionamento de Computadores (CRCs), que são locais onde os equipamentos são recondicionados e disponibilizados para utilização por comunidades carentes. Os CRCs fazem parte do projeto "Computadores para a Inclusão". Uma das dificuldades para o planejamento neste projeto é a configuração da rede logística, que consiste: (i) na localização dos centros de recondicionamento (CRCs), considerando os locais existentes e possibilidades de expansão; (ii) na determinação da quantidade de computadores presentes nos Telecentros respeitando a quantidade máxima e mínima de computadores; e, (iii) na definição dos fluxos de material entre pontos de descarte, CRCs, Telecentros e pontos de destinação final. Neste contexto, a abordagem deste trabalho é a proposição de modelos matemáticos para auxiliar a configuração da rede logística do projeto "Computadores para a Inclusão" contribuindo para coleta e destinação apropriada de equipamentos de informática pós-consumo em todo território nacional.