<p>Uppsatsen syftar till att ge en bild av hur den ryska Östersjömarinen har förändrats sen Kalla krigets slut. För att skapa en överskådlig och konkret bild för läsaren har tre parametrar belysts dessa är uppgifter, resurser och materiel. En avgränsning i tid har gjorts då jag avser rikta in min analys på tre årtal, 1992, 2000 och 2007 dock har en mindre historisk invisning gjorts. Uppsatsens frågeställningar är: Hur har Östersjömarinens uppgifter, resurser och uppgifter förändrats sen Kalla krigets slut?</p><p>    Östersjömarinen var som störst i slutet på Kalla kriget. Under 1990-talet då Ryssland befann sig i en ekonomisk kris drabbades hela den ryska krigsmakten och inte minst Östersjömarinen av neddragningar och minskat manöverutrymme. Antalet fartyg minskade och tillfälle till övningar försvann. Efter millennieskiftet stabiliserades Rysslands ekonomi och Östersjömarinens styrka växte, samarbetet med väst utökades och Ryssland deltar t.ex. i övningar med Nato. Under 2000-talet har Ryssland stärkts ytterligare och Östersjömarinen spelar allt en större roll i Rysslands vilja att försvara sina ekonomiska intressen. De militära utgifterna har ökat och nyproduktion av fartyg både till ryska flottan och för export har börjat byggas under 2000-talet.</p> / <p>Russia has since the fall of the Soviet Union faced some severe economic issues. During the 1990s the economy was rebuilt from a planned economy towards a more liberalized economy, and therefore a crisis was at hand. This unbalanced economy turned after the millennium, since a new president with a strong will strengthened Russia’s economy. This development after the Cold War also affected the Russian armed forces. The purpose of this essay is to describe the change in the Russian Baltic Fleet since the end of the Cold War. The study intends to answer the following questions: How have the economic recourses, the material situation and finally how the tasks changed in the Russian Baltic Fleet since the Cold War ended? To answer these questions I have analyzed a wealth of published materials covering this subject. The essay is built on three parameters: tasks, resources and material. With these three dimensions in mind I have built a total picture of the alterations that have been made in the Russian Baltic Fleet over the passed years.  The study has been carried out with the help of a comparative descriptive method.</p><p>    The result of this essay shows that the purpose and tasks for the Baltic Fleet have changed since the end of the Cold War. During the 1980s the goals in the Baltic were more aggressive and apparent. The strategic goals changed after the Cold War and the Baltic Fleet became more defensive. The tasks today concentrate upon Russia’s maritime interests, international cooperation and intervention.</p><p>    The Russian Fleet suffered from severe economic reductions during the 1990s. Since the new millennium the Russian economy has been strengthened and so have the Baltic Fleet. The result of how the material situation has changed since the Cold war ended is substantial. During the 1990s the number of ships became fewer and fewer.  Since 1998 the reduction of ships has stabilized and has since then been the same. The ships that serve in the Baltic Fleet are very old and few new ships have been added to the fleet.</p>

Uppsatsen syftar till att ge en bild av hur den ryska Östersjömarinen har förändrats sen Kalla krigets slut. För att skapa en överskådlig och konkret bild för läsaren har tre parametrar belysts dessa är uppgifter, resurser och materiel. En avgränsning i tid har gjorts då jag avser rikta in min analys på tre årtal, 1992, 2000 och 2007 dock har en mindre historisk invisning gjorts. Uppsatsens frågeställningar är: Hur har Östersjömarinens uppgifter, resurser och uppgifter förändrats sen Kalla krigets slut?     Östersjömarinen var som störst i slutet på Kalla kriget. Under 1990-talet då Ryssland befann sig i en ekonomisk kris drabbades hela den ryska krigsmakten och inte minst Östersjömarinen av neddragningar och minskat manöverutrymme. Antalet fartyg minskade och tillfälle till övningar försvann. Efter millennieskiftet stabiliserades Rysslands ekonomi och Östersjömarinens styrka växte, samarbetet med väst utökades och Ryssland deltar t.ex. i övningar med Nato. Under 2000-talet har Ryssland stärkts ytterligare och Östersjömarinen spelar allt en större roll i Rysslands vilja att försvara sina ekonomiska intressen. De militära utgifterna har ökat och nyproduktion av fartyg både till ryska flottan och för export har börjat byggas under 2000-talet. / Russia has since the fall of the Soviet Union faced some severe economic issues. During the 1990s the economy was rebuilt from a planned economy towards a more liberalized economy, and therefore a crisis was at hand. This unbalanced economy turned after the millennium, since a new president with a strong will strengthened Russia’s economy. This development after the Cold War also affected the Russian armed forces. The purpose of this essay is to describe the change in the Russian Baltic Fleet since the end of the Cold War. The study intends to answer the following questions: How have the economic recourses, the material situation and finally how the tasks changed in the Russian Baltic Fleet since the Cold War ended? To answer these questions I have analyzed a wealth of published materials covering this subject. The essay is built on three parameters: tasks, resources and material. With these three dimensions in mind I have built a total picture of the alterations that have been made in the Russian Baltic Fleet over the passed years.  The study has been carried out with the help of a comparative descriptive method.     The result of this essay shows that the purpose and tasks for the Baltic Fleet have changed since the end of the Cold War. During the 1980s the goals in the Baltic were more aggressive and apparent. The strategic goals changed after the Cold War and the Baltic Fleet became more defensive. The tasks today concentrate upon Russia’s maritime interests, international cooperation and intervention.     The Russian Fleet suffered from severe economic reductions during the 1990s. Since the new millennium the Russian economy has been strengthened and so have the Baltic Fleet. The result of how the material situation has changed since the Cold war ended is substantial. During the 1990s the number of ships became fewer and fewer.  Since 1998 the reduction of ships has stabilized and has since then been the same. The ships that serve in the Baltic Fleet are very old and few new ships have been added to the fleet.

In this study, we consider the Air Cargo Scheduling Problem based on a real life application. The aim is to move cargo and passengers that have different priorities and delivery time window, from a number of origin airports to destination airports by means of a transportation system. The system has predefined carrier routes and a heterogeneous fleet of aircraft. The problem is formulated as a heterogeneous vehicle, multi commodity, pick-up, and delivery network flow problem with a large set of system specific constraints. The proposed model determines set of movement requirements assigned on each route leg and number and type of aircraft assigned for each route in a reasonable amount of time. The model is tested with the real and generated data and the results are compared with the current methodology under different scenarios. The model produced better results in a short amount of time compared to the current methodology.

A multi-period optimal energy planning program for Ontario has been developed in mixed-integer non-linear programming using General Algebraic Modeling System, GAMS. The program applies both time-dependent and time-independent constraints. These include, but not limited to, construction time, fluctuation of fuel prices, and CO2 emission reduction target. It also offer flexibility of fuel balancing and fuel switching of the existing boilers and option purchasing of Carbon credit if the reduction target is not achievable. The objective function incorporates all these constraints as well as minimizes over all the cost of electricity and meets the projected electricity demand over the 30 years horizon. A number of Ontario study cases are performed utilizing this 30 years model. These cases include a number of CO2 emission reduction target from 6% to 75% below that of 1990 levels by 2014, doubling of natural gas over the forecasted price in 2020, an arbitrary year. A study case in appliance with the Environmental Protection Act where no new or existing coal-fired power stations are available after 2014, as well as study cases where no new nuclear power stations are available. The overall cost of the electricity for different CO2 emission reduction targets increases linearly with slope of ~ 5. The fuel switching, fuel balancing for coal stations, and retrofitting of the carbon capture and storage are the main strategy in order to keep the cost of electricity relative low and satisfy the CO2 emission constraints. Nuclear power is an essential supply technology to the fleet especially when CO2 emission is concerned. An additional 248 Mt of CO2 emission is observed over the reference case when no new nuclear supply is offered. Eliminating all coal technologies by 2014 in accordance to the Environmental Protection Act may also reduce the CO2 emission with less additional expenditure normally associated with the emission reduction processes. This however also reduces the energy port folio diversity, forcing the system to depend on a smaller group of supply technologies and decreasing the reliability of the system overall. These results help us better understand the factors affecting the fleet’s structure. It may also help plan the energy direction of Ontario and perhaps serve as an example for other provinces, territories, states, and even countries.

A multi-period optimal energy planning program for Ontario has been developed in mixed-integer non-linear programming using General Algebraic Modeling System, GAMS. The program applies both time-dependent and time-independent constraints. These include, but not limited to, construction time, fluctuation of fuel prices, and CO2 emission reduction target. It also offer flexibility of fuel balancing and fuel switching of the existing boilers and option purchasing of Carbon credit if the reduction target is not achievable. The objective function incorporates all these constraints as well as minimizes over all the cost of electricity and meets the projected electricity demand over the 30 years horizon. A number of Ontario study cases are performed utilizing this 30 years model. These cases include a number of CO2 emission reduction target from 6% to 75% below that of 1990 levels by 2014, doubling of natural gas over the forecasted price in 2020, an arbitrary year. A study case in appliance with the Environmental Protection Act where no new or existing coal-fired power stations are available after 2014, as well as study cases where no new nuclear power stations are available. The overall cost of the electricity for different CO2 emission reduction targets increases linearly with slope of ~ 5. The fuel switching, fuel balancing for coal stations, and retrofitting of the carbon capture and storage are the main strategy in order to keep the cost of electricity relative low and satisfy the CO2 emission constraints. Nuclear power is an essential supply technology to the fleet especially when CO2 emission is concerned. An additional 248 Mt of CO2 emission is observed over the reference case when no new nuclear supply is offered. Eliminating all coal technologies by 2014 in accordance to the Environmental Protection Act may also reduce the CO2 emission with less additional expenditure normally associated with the emission reduction processes. This however also reduces the energy port folio diversity, forcing the system to depend on a smaller group of supply technologies and decreasing the reliability of the system overall. These results help us better understand the factors affecting the fleet’s structure. It may also help plan the energy direction of Ontario and perhaps serve as an example for other provinces, territories, states, and even countries.

Robust Airline Fleet Assignment Barry C. Smith 140 Pages Directed by Dr. Ellis L. Johnson Fleet assignment models are used by many airlines to assign aircraft to flights in a schedule to maximize profit. Major airlines report that the use of fleet assignment models increases annual profits by more than $100 million. The results of fleet assignment models affect subsequent planning, marketing and operational processes within the airline. Anticipating these processes and developing solutions favorable to them can further increase the benefits of fleet assignment models. We propose to produce fleet assignment solutions that increase planning flexibility and reduce cost by imposing station purity, limiting the number of fleet types allowed to serve each airport in the schedule. We demonstrate that imposing station purity on the fleet assignment model can limit aircraft dispersion in the network and make solutions more robust relative to crew planning, maintenance planning and operations. Because station purity can significantly degrade computational efficiency, we develop a solution approach, Station Decomposition, which takes advantage of airline network structure. Station Decomposition uses a column generation approach to solving the fleet assignment problem; we further improve the performance of Station Decomposition by developing a primal-dual method that increases the solution quality and model efficiency. Station Decomposition solutions can be highly fractional; we develop a fix and price heuristic to efficiently find integer solutions to the fleet assignment problem. Airline profitability can be increased if fleet assignment models anticipate the effects of marketing processes such as revenue management. We develop an approach, ODFAM, which incorporates airline revenue management effects into the fleet assignment model. We develop an approach to incorporate station purity and ODFAM using a combination of column and cut generation. This approach can increase airline profit up to $27 million per year.

Efficient integrated/robust planning and recovery models were studied. The research focus was to integrate fleet assignment and crew scheduling, and, in addition, to provide solutions robust to real time operations. The contributions include: (1) To understand how schedule development and fleet assignment stages influence crew scheduling performance, schedule analysis methods were proposed to evaluate the crew friendliness of a schedule for a given fleet. (2) To meet the computational challenges of crew scheduling in integrated planning, a duty flow model was proposed which can efficiently find suboptimal legal pairing solutions. (3) A new robust crew scheduling method based on spoke purity was proposed. Computational results indicated that with little or no extra cost, a more robust crew pairing solutions can be expected. (4) By imposing station purity, an integrated and robust planning model which integrates fleet assignment and crew connections was proposed. The impact of crew base purities and fleet purities on FAM profit, crew scheduling, and computational efficiency were investigated. (5) Airline integrated recovery method was studied. A recovery scope for integrated recovery was proposed to limit the ripple effect caused by disruptions. Based on the defined recovery scope, a new integrated recovery model and Bender¡¯s decomposition solution approach was studied.

Intelligent Transport Systems (ITS) are becoming a part of our daily lives in various forms of application. Their success depends highly on the accuracy of the digital data they use. In networks where characteristics change by time, time-based network analysis algorithms provide results that are more accurate. However, these analyses require time-based travel speed data to provide accurate results. Conventionally, traffic data are usually obtained using the data provided from loop-detectors. These detectors usually exist on main arteries, freeways and highways / they rarely exist on back roads, secondary roads and streets due to their deployment costs. Today, telematics systems offer fleet operators to track their fleet remotely from a central system. Those systems provide data about the behaviors of vehicles with time information. Therefore, a tracking system can be used as an alternative to detector-based systems on estimating travel speeds on networks. This study aims to provide methods to estimate network characteristics using the data collected directly from fleets consisting of global positioning system (GPS) receiver equipped vehicles. GIS technology is used to process the collected GPS data spatially to match digital road maps. After matching, time-dependent characteristics of roads on which tracked vehicles traveled are estimated. This estimation provides data to perform a time-dependent network analysis. The methods proposed in this study are tested on traffic network of Middle East Technical University campus. The results showed that the proposed methods are capable of measuring time-dependent link-travel times on the network. Peak hours through the network are clearly detected.

In this study we discuss the Vehicle Routing Problem with multiple use of vehicles (VRPM). In this variant of the routing problem the vehicles may replenish at any time at the depot. We present a detailed review of existing literature and propose two mathematical models to solve the VRPM. For these two models and their several variants we provide computational results based on the test problems taken from the literature. We also discuss a case study in which we are simultaneously dealing with side constraints such as time windows, working hour limits, backhaul customers and a heterogeneous vehicle fleet.

Commercial aviation has become an integral part of modern society and enables unprecedented global connectivity by increasing rapid business, cultural, and personal connectivity. In the decades following World War II, passenger travel through commercial aviation quickly grew at a rate of roughly 8% per year globally. The FAA's most recent Terminal Area Forecast predicts growth to continue at a rate of 2.5% domestically, and the market outlooks produced by Airbus and Boeing generally predict growth to continue at a rate of 5% per year globally over the next several decades, which translates into a need for up to 30,000 new aircraft produced by 2025. With such large numbers of new aircraft potentially entering service, any negative consequences of commercial aviation must undergo examination and mitigation by governing bodies so that growth may still be achieved. Options to simultaneously grow while reducing environmental impact include evolution of the commercial fleet through changes in operations, aircraft mix, and technology adoption. Methods to rapidly evaluate fleet environmental metrics are needed to enable decision makers to quickly compare the impact of different scenarios and weigh the impact of multiple policy options. As the fleet evolves, interdependencies may emerge in the form of tradeoffs between improvements in different environmental metrics as new technologies are brought into service. In order to include the impacts of these interdependencies on fleet evolution, physics-based modeling is required at the appropriate level of fidelity. Evaluation of environmental metrics in a physics-based manner can be done at the individual aircraft level, but will then not capture aggregate fleet metrics. Contrastingly, evaluation of environmental metrics at the fleet level is already being done for aircraft in the commercial fleet, but current tools and approaches require enhancement because they currently capture technology implementation through post-processing, which does not capture physical interdependencies that may arise at the aircraft-level. The goal of the work that has been conducted here was the development of a methodology to develop surrogate fleet approaches that leverage the capability of physics-based aircraft models and the development of connectivity to fleet-level analysis tools to enable rapid evaluation of fuel burn and emissions metrics. Instead of requiring development of an individual physics-based model for each vehicle in the fleet, the surrogate fleet approaches seek to reduce the number of such models needed while still accurately capturing performance of the fleet. By reducing the number of models, both development time and execution time to generate fleet-level results may also be reduced. The initial steps leading to surrogate fleet formulation were a characterization of the commercial fleet into groups based on capability followed by the selection of a reference vehicle model and a reference set of operations for each group. Next, three potential surrogate fleet approaches were formulated. These approaches include the parametric correction factor approach, in which the results of a reference vehicle model are corrected to match the aggregate results of each group; the average replacement approach, in which a new vehicle model is developed to generate aggregate results of each group, and the best-in-class replacement approach, in which results for a reference vehicle are simply substituted for the entire group. Once candidate surrogate fleet approaches were developed, they were each applied to and evaluated over the set of reference operations. Then each approach was evaluated for their ability to model variations in operations. Finally, the ability of each surrogate fleet approach to capture implementation of different technology suites along with corresponding interdependencies between fuel burn and emissions was evaluated using the concept of a virtual fleet to simulate the technology response of multiple aircraft families. The results of experimentation led to a down selection to the best approach to use to rapidly characterize the performance of the commercial fleet for accurately in the context of acceptability of current fleet evaluation methods. The parametric correction factor and average replacement approaches were shown to be successful in capturing reference fleet results as well as fleet performance with variations in operations. The best-in-class replacement approach was shown to be unacceptable as a model for the larger fleet in each of the scenarios tested. Finally, the average replacement approach was the only one that was successful in capturing the impact of technologies on a larger fleet. These results are meaningful because they show that it is possible to calculate the fuel burn and emissions of a larger fleet with a reduced number of physics-based models within acceptable bounds of accuracy. At the same time, the physics-based modeling also provides the ability to evaluate the impact of technologies on fleet-level fuel burn and emissions metrics. The value of such a capability is that multiple future fleet scenarios involving changes in both aircraft operations and technology levels may now be rapidly evaluated to inform and equip policy makers of the implications of impacts of changes on fleet-level metrics.