El presente trabajo de tesis tiene como objetivo presentar una solución de optimización al proceso “Gestión de flota” de una empresa dedicada al transporte de carga por carretera de mercancías en general. Para la arquitectura empresarial se utilizó el framework Zachman, que permitió realizar el análisis del negocio, su entorno, estructura y procesos, bajo la perspectiva del negocio como caja negra que necesita descifrarse. Lo cual permitió que se comprenda el propósito y los objetivos para la cual fue creado el negocio. Adicionalmente, se utilizó TOGAF y ADM, del resultado del análisis se observa que el macroproceso de “Gestión de Flota”, es uno de los procesos operativos de vital importancia para el negocio, pues es donde se administra los recursos operativos del negocio, también, es donde se evidenciará la problemática que será motivo de estudio, análisis y planteamiento de solución. Por otro lado, se usó la Guía PMBOK, para poder gestionar el desarrollo del proyecto, determinando el alcance de la investigación, así como, el análisis del negocio, la definición de la arquitectura empresarial, el análisis de la problemática, la ingeniería de los procesos, la propuesta solución, arquitectura de solución utilizando tendencias tecnológicas como GPS, SMS Gateway, Machine Learning y BI, por último, se diseñará el prototipado de la solución y arquitectura propuesta. Asimismo, se utilizará la gestión de riesgos para poder mitigar cualquier incidencia. / The objective of this thesis work is to present an optimization solution to the "Fleet Management" process of a company dedicated to the road freight transport of goods in general. For the business architecture, the Zachman framework was used, which allowed the analysis of the business, its environment, structure and processes, from the perspective of the business as a black box that needs to be deciphered. Which allowed the purpose and objectives for which the business was created to be understood. Additionally, we use TOGAF and ADM, from the result of the analysis it is observed that the macro-process of "Fleet Management" is one of the operational processes of vital importance for the business, since it is where the operational resources of the business are managed, it is also where the problem that will be the subject of study, analysis and solution proposal will be evidenced. On the other hand, the PMBOK Guide was used to manage the development of the project, determining the scope of the research, as well as the business analysis, the definition of the business architecture, the analysis of the problem, the engineering of the processes, the proposed solution, solution architecture using technological trends such as GPS, SMS Gateway, Machine Learning and BI, finally, the prototyping of the proposed solution and architecture will be designed. Likewise, risk management will be used to mitigate any incident. / Tesis

The diploma thesis proposes new innovation strategy for The Brno Public Transport Authority (DPMB) tram vehicles. The thesis reviews different approaches to transport innovation strategy. Analyse current strategy in Transport Authority and finally is proposed original innovation strategy of DPMB tram vehicles. The proposal aims to serve as strategical document for the management and stakeholders in tramway fleet renewal.

Transportation is one of the most vital services in modern society. It makes most of the other functions of society possible. Real transportation systems are so large and complex that in order to build the science of transportation systems it will be necessary to work in many areas, such as: Modeling, Optimization and Simulation. We are interested in solutions for the so-called fleet-sizing-and-allocation problem (FSAP). Fleet sizing and allocation problems are one of the most interesting and hard to solve logistic problems. A fleet sizing and allocation problem consists of two interdependent parts. The fleet sizing problem is to determine a number of transportation units that optimally balances service requirements against the cost of purchasing and maintaining the transportation units. The allocation problem is dealing with the repositioning of transportation units to serve future transportation demand. To make the fleet sizing and allocation problem a little bit more tractable we concentrate on logistic systems with a special hub-and-spoke structure. We start with a very simple fleet sizing of one-to-one case. This case will cause us to focus attention on several key issues in fleet sizing. Afterwards, the generalization of the one-to-one system is the one-to-many system. As a simple example can serve the continuous time situation where a single origin delivers items to many destinations. For the case that items are produced in a deterministic production cycle and transportation times are stochastic. We also studied a hub-and-spoke problem with continuous time and stochastic demand. To solve this problem, based on Marginal Analysis, we applied queueing theory methods. The investigation of the fleet-sizing-and-allocation problem for hub-and-spoke systems is started for a single-period, deterministic-demand model. In that the model hub has to decide how to use a given number of TU’s to satisfy a known (deterministic) demand in the spokes. We consider two cases: 1. Renting of additional TU’s from outside the system is not possible, 2. Renting of additional TU’s from outside the system is possible. For each case, based on Marginal Analysis, we developed a simple algorithm, which gives us the cost-minimal allocation. Since the multi-period, deterministic demand problem is NP-hard we suggest to use Genetic Algorithms. Some building elements for these are described. For the most general situation we also suggest to use simulation optimization. To realize the simulation optimization approach we could use the software tool “Calculation Assessment Optimization System” (CAOS). The idea of CAOS is to provide a software system, which separates the optimization process from the optimization problem. To solve an optimization problem the user of CAOS has to build up a model of the system to which the problem is related. Furthermore he has to define the decision parameters and their domain. Finally, we used CAOS for two classes of hub-and-spoke system: 1. A single hub with four spokes, 2. A single hub with fifty spokes. We applied four optimizers – a Genetic Algorithm, Tabu Search, Hybrid Parallel and Hybrid Serial with two distributions (Normal Distribution and Exponential Distribution) for a customer interarrival times and their demand.

This report studies the possibility of integrating Transport Management Services (TMS) in a low-cost platform called Communicator 200 (C200). The platform is developed by Scania and is a black box that manages vehicle data, positioning, and wireless communication. The C200’s main purpose is to connect a hauler’s vehicles to their office system via wireless links and Internet. The thesis describes the design and implements a prototype of a service called Messaging that is used to send text messages between truck and office. The prototype is evaluated and tested with different web browsers in various hand-held terminals with different screen sizes. The main conclusion is that it is technically possible to integrate TMS in the C200 without altering the platform architecture too much. / Denna rapport undersöker möjligheten att integrera transportledningstjänster i en billig platform kallad Communicator 200 (C200). Platformen är utvecklad av Scania och är en svart låda som hanterar fordonsdata, positionering och trådlös kommunikation. C200 huvudsyfte är att sammankoppla ett åkeris fordon med deras kontorssystem via trådlösa förbindelser och Internet. Rapporten beskriver designen och implementerar en prototyp av en tjänst kallad Messaging som används för att skicka textmeddelanden mellan lastbil och kontor. Prototypen utvärderas och testas mot webbläsare i olika handhållna terminaler med olika skärmstorlekar. Huvudslutsatsen är att det är möjligt att integrera transportledningstjänster i C200 utan att ändra plattformens arkitektur alltför mycket.

El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado. / Mining activities around the world are undergoing constant change and modernization owing to technological and scientific advancements. Consequently, there are frequent proposals to streamline and enhance processes in mining operations. This study deals with ore transportation in mechanized mining units and aims to optimize fleet management using the Lean Six Sigma methodology to obtain a model in this specific process. The proposed method was implemented using a Lean Six Sigma instrument known as DMAIC (Define, Measure, Analyze, Improve, and Control). The case study was applied to an underground mine located in the Huancavelica region, Peru. The simulation showed that 24% of the time in the ore transport cycle is un-productive time and the improvement potential time represents 53% of the transportation process time.

Nomenclature for the Upper Triassic and Lower Jurassic strata along the south flank of the Uinta Mountains has been somewhat confusing because of the position of the study area between southern Wyoming, where one set of names is used, and central/southern Utah where a different set of formation names is used. The Nugget Sandstone or Glen Canyon Sandstone of the eastern Uinta Mountains overlies the Upper Triassic Popo Agie or Chinle Formation. The nature of the contact between these two formations is unclear both in stratigraphic location and conformability. The Chinle Formation consists, in ascending order, of the Gartra Member, the purple unit, the ocher unit, and the upper red unit. The overlying Nugget Sandstone consists of two members, the lower Bell Springs Member and the overlying unnamed cross-bedded member, typically believed to be Navajo Sandstone equivalent. These two units of the Nugget Sandstone are thought to represent the Glen Canyon Group of the Colorado Plateau, although no obvious Wingate or Kayenta Formation equivalents have been recognized. The Bell Springs Member contains abundant fine-grained, ripple-laminated sandstones, red and green mudstones, occasional mudcracks and salt casts, evidence of burrowing and exposure, and some medium- to coarse-grained sandstones with small-scale (30-40 cm high) cross-beds. This member was deposited in a marine tidal flat environment, quite different from the mainly eolian environment of the rest of the Nugget Sandstone. The Bell Springs Member appears to be entirely Upper Triassic, based upon dinosaur tracks, while the upper windblown unit's age is unknown, but probably straddles the Triassic-Jurassic boundary. During mapping in the Donkey Flat, Steinaker Reservoir, Dry Fork, and Lake Mountain quadrangles, the Bell Springs Member of the Nugget Sandstone was mapped as a separate unit.

The United States is the world's largest oil consumer demanding about twenty five percent of the total world oil production. Whenever there are difficulties to supply the increasing quantities of oil demanded by the market, the price of oil escalates leading to what is known as oil price spikes or oil price shocks. The last oil price shock which was the longest sustained oil price run up in history, began its course in year 2004, and ended in 2008. This last oil price shock initiated recognizable changes in transportation dynamics: transit operators realized that commuters switched to transit as a way to save gasoline costs, consumers began to search the market for more efficient vehicles leading car manufactures to close 'gas guzzlers' plants, and the government enacted a new law entitled the Energy Independence Act of 2007, which called for the progressive improvement of the fuel efficiency indicator of the light vehicle fleet up to 35 miles per gallon in year 2020. The past trend of gasoline consumption will probably change; so in the context of the problem a gasoline consumption model was developed in this thesis to ascertain how some of the changes will impact future gasoline demand. Gasoline demand was expressed in oil equivalent million barrels per day, in a two steps Ordinary Least Square (OLS) explanatory variable model. In the first step, vehicle miles traveled expressed in trillion vehicle miles was regressed on the independent variables: vehicles expressed in million vehicles, and price of oil expressed in dollars per barrel. In the second step, the fuel consumption in million barrels per day was regressed on vehicle miles traveled, and on the fuel efficiency indicator expressed in miles per gallon. The explanatory model was run in EVIEWS that allows checking for normality, heteroskedasticty, and serial correlation. Serial correlation was addressed by inclusion of autoregressive or moving average error correction terms. Multicollinearity was solved by first differencing. The 36 year sample series set (1970-2006) was divided into a 30 years sub-period for calibration and a 6 year "hold-out" sub-period for validation. The Root Mean Square Error or RMSE criterion was adopted to select the "best model" among other possible choices, although other criteria were also recorded. Three scenarios for the size of the light vehicle fleet in a forecasting period up to 2020 were created. These scenarios were equivalent to growth rates of 2.1, 1.28, and about 1 per cent per year. The last or more optimistic vehicle growth scenario, from the gasoline consumption perspective, appeared consistent with the theory of vehicle saturation. One scenario for the average miles per gallon indicator was created for each one of the size of fleet indicators by distributing the fleet every year assuming a 7 percent replacement rate. Three scenarios for the price of oil were also created: the first one used the average price of oil in the sample since 1970, the second was obtained by extending the price trend by exponential smoothing, and the third one used a longtime forecast supplied by the Energy Information Administration. The three scenarios created for the price of oil covered a range between a low of about 42 dollars per barrel to highs in the low 100's. The 1970-2006 gasoline consumption trend was extended to year 2020 by ARIMA Box-Jenkins time series analysis, leading to a gasoline consumption value of about 10 millions barrels per day in year 2020. This trend line was taken as the reference or baseline of gasoline consumption. The savings that resulted by application of the explanatory variable OLS model were measured against such a baseline of gasoline consumption. Even on the most pessimistic scenario the savings obtained by the progressive improvement of the fuel efficiency indicator seem enough to offset the increase in consumption that otherwise would have occurred by extension of the trend, leaving consumption at the 2006 levels or about 9 million barrels per day. The most optimistic scenario led to savings up to about 2 million barrels per day below the 2006 level or about 3 millions barrels per day below the baseline in 2020. The "expected" or average consumption in 2020 is about 8 million barrels per day, 2 million barrels below the baseline or 1 million below the 2006 consumption level. More savings are possible if technologies such as plug-in hybrids that have been already implemented in other countries take over soon, are efficiently promoted, or are given incentives or subsidies such as tax credits. The savings in gasoline consumption may in the future contribute to stabilize the price of oil as worldwide demand is tamed by oil saving policy changes implemented in the United States.

<p>QC 20130524</p>

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The problem of fleet design and fleet modelling; for decades problems regarding determining fleet sizes and optimized routing problems have formed the groundwork into the fleet design and fleet optimization for a wide range of business sectors. In most of these problems only single entities or fixed design resources are optimized for a certain route and delivery objective based on minimizing operational costs. In the naval industry, there has been a growing need for numerical methods that are able to predict what kind of fleets, in terms of size and capabilities, would be suited to achieve certain operational needs. Further than that, for shipbuilders and designers, what kind of design requirements the individual vessel platforms in such a fleet must contain constitutes the bridge in translating operational needs to ship design and system integration requirements. Especially in an era where technology advances more quickly than it takes to design a naval vessel, creating tools that are able to predict something about future fleet resilience could become an effective asset for future naval fleet development. For this, studies that contribute to developing methods that can evaluate the combined effect of individual vessel platforms from a fleet perspective are still fairly limited. The overall goal of this study was to determine how the development and application of fleet modelling tools can contribute to designing naval fleets that are more robust against future threats and missions. The objective was to extend and build on a fleet modelling method based on Systems Engineering, that is able to generate fleet compositions and produce basic individual platform design requirements for early-stage design phases of naval fleets through scripted naval scenario's. The aim was to construct a functional numerical simulation model through Mixed Integer Linear programming and extend the abilities of the method to be able to include 'future' technologies, with UXV's receiving the main focus. The overall potential and results that the numerical model produces are interesting, through an optimization process it is able to build a fleet from a wide range of platform choices and deliver basic platform design requirements. Actual combat performance of the fleets that are generated, is debatable and needs to be further investigated and tested/verified through different means. The conclusion from the study is that to design future resilient fleets, more research and development is needed in the area of naval fleet modelling and simulation since the functionality of tools available can not overcome the amount of uncertainty that the future brings. Besides that, the method under review does make it able to generate interesting fleet combinations that could spark new ideas on how we could regard the future potential of uprising technology and their combined capabilities with naval vessel platforms. / Problemet med flottdesign och flottmodellering; i årtionden har problem med att bestämma flottans storlek och optimerade routingproblem bildat grunden för flottans design och flottans optimering för ett brett spektrum av affärssektorer. I de flesta av dessa problem är mätvärden för enkel design eller fasta fartyg optimerade för en viss rutt och antal hamnar baserat på minimering av driftskostnader. Inom marinindustrin har det funnits ett växande behov av numeriska metoder som kan förutsäga vilken typ av flotta, när det gäller storlek och kapacitet, som skulle vara lämplig för att möta vissa operativa behov. För varvsbyggare och konstruktörer fungerar dessutom att tillskriva designkrav till enskilda fartygsplattformar i en sådan flotta som bron som översätter operativa behov till krav på fartygsdesign och systemintegration. Särskilt i en tid där tekniken går snabbare än vad som krävs för att utforma ett marinfartyg kan skapandet av verktyg som kan förutsäga motståndskraften hos en framtida flotta vara en effektiv tillgång för framtida marinutveckling. För detta är studier som bidrar till att utveckla metoder som kan utvärdera den kombinerade effekten av enskilda fartygsplattformar ur ett flottperspektiv fortfarande ganska begränsade. Det övergripande målet för denna studie var att avgöra hur utvecklingen och tillämpningen av verktyg för modellering av flottor kan bidra till att utforma marinflottor som är mer robusta mot framtida hot och uppdrag. Målet var att utöka och bygga på en flottmodelleringsmetod baserad på Systems Engineering, som kan generera flottanheter och producera grundläggande individuella plattformskrav för designfasen i de tidiga stadierna av marina flottar genom scenarier för manusskrivning. Syftet var att konstruera en funktionell numerisk simuleringsmodell genom Mixed Integer Linear Programmering och utöka metodens förmåga för att kunna inkludera 'framtida' teknologier, med UXV: er som huvudfokus. Den övergripande potentialen och resultaten som den numeriska modellen ger är intressanta, genom en optimeringsprocess kan den bygga en flotta från ett brett spektrum av plattformsval och leverera grundläggande krav på plattformsdesign. Den faktiska stridsprestandan för de genererade flottorna kan inte bedömas och måste undersökas vidare och testas / verifieras med olika metoder. Studien drar slutsatsen att utformning av framtida motståndskraftiga flottor kräver mer forskning och utveckling inom marinmodellering och simulering, eftersom funktionaliteten hos nuvarande tillgängliga verktyg inte kan övervinna osäkerheten i framtiden. Förutom det gör metoden under granskning det möjligt att generera intressanta flottkombinationer som kan utlösa nya idéer om hur vi kan betrakta den framtida potentialen för upprorsteknologi och deras kombinerade kapacitet med sjöfartygsplattformar.