The simulation of seafloor-steel catenary interaction and prediction of riser fatigue life required an accurate characterization of seafloor stiffness as well as realistic description of riser load-deflection (P-y) response. This thesis presents two load-deflection (P-y) models (non-degradating and degradating models) to simulate seafloor-riser interaction. These two models considered the seafloor-riser system in terms of an elastic steel pipe supported on non-linear soil springs with vertical motions. These two models were formulated in terms of a backbone curve describing self-embedment of the riser, bounding curves describing P-y behavior under extremely large deflections, and a series of rules for describing P-y behavior within the bounding loop. The non-degradating P-y model was capable of simulating the riser behavior under very complex loading conditions, including unloading (uplift) and re-loading (downwards) cycles under conditions of partial and full separation of soils and riser. In the non-degradating model, there was a series of model parameters which included three riser properties, two trench geometry parameters and one trench roughness parameter, two backbone curve model parameters, and four bounding loop model parameters. To capture the seafloor stiffness degradation effect due to cyclic loading, a degradating P-y model was also developed. The degradating model proposes three degradation control parameters, which consider the effects of the number of cycles and cyclic unloading-reloading paths. Accumulated deflections serve as a measure of energy dissipation. The degradating model was also made up of three components. The first one was the backbone curve, same as the non-degradating model. The bounding loops define the P-y behavior of extreme loading deflections. The elastic rebound curve and partial separation stage were in the same formation as the non-degradating model. However, for the re-contact and re-loading curve, degradation effects were taken into the calculation. These two models were verified through comparisons with laboratory basin tests. Computer codes were also developed to implement these models for seafloor-riser interaction response.

The simulation of seafloor-steel catenary interaction and prediction of riser fatigue life required an accurate characterization of seafloor stiffness as well as realistic description of riser load-deflection (P-y) response. This thesis presents two load-deflection (P-y) models (non-degradating and degradating models) to simulate seafloor-riser interaction. These two models considered the seafloor-riser system in terms of an elastic steel pipe supported on non-linear soil springs with vertical motions. These two models were formulated in terms of a backbone curve describing self-embedment of the riser, bounding curves describing P-y behavior under extremely large deflections, and a series of rules for describing P-y behavior within the bounding loop. The non-degradating P-y model was capable of simulating the riser behavior under very complex loading conditions, including unloading (uplift) and re-loading (downwards) cycles under conditions of partial and full separation of soils and riser. In the non-degradating model, there was a series of model parameters which included three riser properties, two trench geometry parameters and one trench roughness parameter, two backbone curve model parameters, and four bounding loop model parameters. To capture the seafloor stiffness degradation effect due to cyclic loading, a degradating P-y model was also developed. The degradating model proposes three degradation control parameters, which consider the effects of the number of cycles and cyclic unloading-reloading paths. Accumulated deflections serve as a measure of energy dissipation. The degradating model was also made up of three components. The first one was the backbone curve, same as the non-degradating model. The bounding loops define the P-y behavior of extreme loading deflections. The elastic rebound curve and partial separation stage were in the same formation as the non-degradating model. However, for the re-contact and re-loading curve, degradation effects were taken into the calculation. These two models were verified through comparisons with laboratory basin tests. Computer codes were also developed to implement these models for seafloor-riser interaction response.

Most recorded data are rounded to the nearest decimal place due to the precision of the recording mechanism. This rounding entails errors in estimation and measurement. In this paper, we compare the performances of three types of estimators based on rounded data from time series models, namely A-K corrected estimator, approximate MLE and the SOS estimator. In order to perform the comparison, the A-K corrected estimators for the MA(1) model are derived theoretically. To improve the efficiency of the estimation, two types of variance-reduction estimators are further proposed, which are based on linear combinations of aforementioned three estimators. Simulation results show the proposed variance reduction estimators significantly improve the estimation efficiency.

Realistic predictions of service life of steel catenary risers (SCR) require an accurate characterization of seafloor stiffness in the zone where the riser contacts the seafloor, the so- called touchdown area (TDA). This paper describes the key features of a seafloor-riser interaction model based on the previous experimental model tests. The seafloor is represented in terms of non-linear load-deflection (P-y) relationships, which are also able to account for soil stiffness degradation due to vertical cyclic loading. The P-y approach has some limitations, but simulations show good agreement with experimental data. Hence, stiffness degradation and rate effects during penetration and uplift motion (suction force increase) of the riser are well captured through comparison with previous experimental tests carried out at the Centre for Offshore Foundation Systems (COFS) and Norwegian Geotechnical Institute (NGI). The analytical framework considers the riser-seafloor interaction problem in terms of a pipe resting on a bed of springs, and requires the iterative solution of a fourth-order ordinary differential equation. A series of simulations is used to illustrate the capabilities of the model. Due to the non-linear soil springs with stiffness degradation it is possible to simulate the trench formation process and estimate deflections and moments along the riser length. The seabed model is used to perform parametric studies to assess the effects of stiffness, soil strength, amplitude of pipe displacements, and riser tension on pipe deflections and bending stresses. The input parameters include the material properties (usually pipe and soil), model parameters, and loading conditions such as the amplitude of imposed dis- placements, tension, and moment. Primary outputs from this model include the deflected shape of the riser pipe and bending moments along riser length. The code also provides the location of maximum trench depth and the position where the maximum bending moment occurs and any point where user is interested in.

Several studies have been carryout on finding optimal locations to minimize CO2 emissions from the last mile distribution perspective. In conjunction with that, there has been no study conducted in Sweden that provides a decision support system to compute the transport consequences of the modifications in the retailer’s store network. This thesis did used the following steps: requirement analysis, system design, implementation and testing to build a prototype decision support system that is to help retailers find optimal locations for a new retail store. This thesis provided a subsequent answer as to which data are needed along with the rightful user interface for said decision support system. Subsequently, this thesis does present a decision support system prototype from which some recommendations were provided as to what skills set and tools are needed for the management and maintenance of said decision support system. The primary data used during this thesis is the Dalarna municipalities, six selected retailer’s stores networks and the Dalarna Road network geo-data (Longitude and latitude). This thesis does conclude that it is possible to integrate an optimization model within the Django framework using a geo data to build a decision support system.

The p-median problem is often used to locate p service centers by minimizing their distances to a geographically distributed demand (n). The optimal locations are sensitive to geographical context such as road network and demand points especially when they are asymmetrically distributed in the plane. Most studies focus on evaluating performances of the p-median model when p and n vary. To our knowledge this is not a very well-studied problem when the road network is alternated especially when it is applied in a real world context. The aim in this study is to analyze how the optimal location solutions vary, using the p-median model, when the density in the road network is alternated. The investigation is conducted by the means of a case study in a region in Sweden with an asymmetrically distributed population (15,000 weighted demand points), Dalecarlia. To locate 5 to 50 service centers we use the national transport administrations official road network (NVDB). The road network consists of 1.5 million nodes. To find the optimal location we start with 500 candidate nodes in the network and increase the number of candidate nodes in steps up to 67,000. To find the optimal solution we use a simulated annealing algorithm with adaptive tuning of the temperature. The results show that there is a limited improvement in the optimal solutions when nodes in the road network increase and p is low. When p is high the improvements are larger. The results also show that choice of the best network depends on p. The larger p the larger density of the network is needed.

Indiana University-Purdue University Indianapolis (IUPUI) / While optimization techniques have been studied since 300 B.C. when Euclid first considered the minimal distance between a point and a line, it wasn’t until 1966 that location optimization was first applied to a problem in healthcare. Location optimization techniques are capable of increasing efficiency and equity in the placement of many types of services, including those within the healthcare industry, thus enhancing quality of life. Medical imaging is a healthcare service which helps to determine medical diagnoses in acute and preventive care settings. It provides physicians with information guiding treatment and returning a patient back to optimal health. In this study, a retrospective analysis of the locations of current medical imaging centers in central Indiana is performed, and alternate placement as determined using optimization techniques is considered and compared. This study focuses on reducing the drive time experienced by the population within the study area to their nearest imaging facility. Location optimization models such as the P-Median model, the Maximum Covering model, and Clustering and Partitioning are often used in the field of operations research to solve location problems, but are lesser known within the discipline of Geographic Information Science. This study was intended to demonstrate the capabilities of these powerful algorithms and to increase understanding of how they may be applied to problems within healthcare. While the P-Median model is effective at reducing the overall drive time for a given network set, individuals within the network may experience lengthy drive times. The results further indicate that while the Maximum Covering model is more equitable than the P-Median model, it produces large sets of assigned individuals overwhelming the capacity of one imaging center. Finally, the Clustering and Partitioning method is effective at limiting the number of individuals assigned to a given imaging center, but it does not provide information regarding average drive time for those individuals. In the end, it is determined that a capacitated Maximal Covering model would be the preferred method for solving this particular location problem.

企業評價對於投資決策有重大的影響，不論是發行上市、或是機構投資人選擇投資標的、乃至於併購或是清算，企業評價都是一切的基礎。再加上近來各界對於節能產業的重視，發光二極體封裝產業正如日中天的高度成長，如何能夠正確地衡量此產業的企業價值，實是機構投資人或是一般大眾關心的課題。此外，實務界長久以來詬病證管會所採用的承銷價格公式，乃是結合不同評價模式的方式來評斷發行股票公司之正確股票價值，但實證結果往往發現此公式會造成股價被低估的現象。 本研究以台灣地區共六家發光二極體封裝產業上市櫃公司為例，以其民國八十七年至九十四年的財務數據和資料，以五年為一階段，利用七種不同的評價模式：三階段成長現金流量折現法、三階段成長本益比法、三階段成長股價淨值比法、三階段股價銷售額比法、市場比較本益比法、市場比較股價淨值比法以及市場比較股價銷售額比法，預期九十二年初至九十五年初之理論實際股價，並與實際的市價作一比較，利用THEIL所提出的THEIL’S U值來比較不同評價模型與實際市價差距的績效，以選出最適合發光二極體封裝產業之企業評價模式。 本研究更進一步探討長久以來被實務界所詬病的綜合評價模式（結合不同的評價模式），試著經過第一階段實證結果的篩選，利用簡單權重結合本產業最佳和次佳的企業評價模式，以得到一個評價績效更勝於最佳評價模式的綜合評價法。 實證結果顯示，發光二極體最佳評價模型乃為市場比較股價銷售額比法(THEIL’S U=0.3515)，而三階段成長現金流量折現法，則適用於產業較穩定的情況下。突破性的發現則為，利用THEIL’S U值來比較評價績效而選出的最佳和次佳模型，在分別給予簡單權重（ex：50％：50％、60％：40％等）的情況下所得到的綜合評價法，其THEIL’S U值（<0.3515）比當初單一最佳評價法--市場比較股價銷售額比法(0.3515)還要來得低，顯示綜合評價法的有效性的確存在，並值得各界參考。此外，亦發現給予最佳評價法較大權重時，更可以進一步提昇綜合評價法之績效。此結果反駁了實務界長久以來對於綜合評價法的不信任，也給予證管會一個修正承銷價格公式的方向。跨類型的評價法結合並不是不可行，但是需要第一階段各個評價法的評價績效驗證，讓較佳的評價模式彼此結合以產生資訊互補的效果。

GPS technology has been embedded into portable, low-cost electronic devices nowadays to track the movements of mobile objects. This implication has greatly impacted the transportation field by creating a novel and rich source of traffic data on the road network. Although the promise offered by GPS devices to overcome problems like underreporting, respondent fatigue, inaccuracies and other human errors in data collection is significant; the technology is still relatively new that it raises many issues for potential users. These issues tend to revolve around the following areas: reliability, data processing and the related application. This thesis aims to study the GPS tracking form the methodological, technical and practical aspects. It first evaluates the reliability of GPS based traffic data based on data from an experiment containing three different traffic modes (car, bike and bus) traveling along the road network. It then outline the general procedure for processing GPS tracking data and discuss related issues that are uncovered by using real-world GPS tracking data of 316 cars. Thirdly, it investigates the influence of road network density in finding optimal location for enhancing travel efficiency and decreasing travel cost. The results show that the geographical positioning is reliable. Velocity is slightly underestimated, whereas altitude measurements are unreliable.Post processing techniques with auxiliary information is found necessary and important when solving the inaccuracy of GPS data. The densities of the road network influence the finding of optimal locations. The influence will stabilize at a certain level and do not deteriorate when the node density is higher.

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