179 research outputs found

    Preface

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    Uncertainties in Transportation Analysis

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    Time scheduling of transit systems with transfer considerations using genetic algorithms

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    Scheduling of a bus transit system must be formulated as an optimization problem, if the level of service to passengers is to be maximized within the available resources. In this paper, we present a formulation of a transit system scheduling problem with the objec-tive of minimizing the overall waiting time of transferring and nontransferring passengers while satisfying a number of resource- and service-related constraints. It is observed that the number of variables and constraints for even a simple transit system (a single bus station with three routes) is too large to tackle using classical mixed-integer optimization techniques. The paper shows that genetic algorithms (GAS) are ideal for these problems, mainly because they (i) naturally handle binary variables, thereby taking care of transfer decision variables, which constitute the majority of the decision variables in the transit scheduling problem; and (ii) allow procedure-based declarations, thereby allowing com-plex algorithmic approaches (involving if then-else conditions) to be handled easily. The paper also shows how easily the same GA procedure with minimal modifications can han-dle a number of other more pragmatic extensions to the simple transit scheduling problem: buses with limited capacity, buses that do not arrive exactly as per scheduled times, and a multiple-station transit system having common routes among bus stations. Simulation results show the success of GAS in all these problems and suggest the application of GAS in more complex scheduling problems. Genetic algorithms, mixed-integer programming, reliability, time scheduling, transfer time, transit system

    Optimum assignment of trains to platforms under partial schedule compliance

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    The paper develops a linear mixed integer programming formulation for allocating platforms optimally to trains arriving at a busy multi-platform station. The formulation does not assume that all trains arrive as per schedule, in fact it assumes that the exact arrival times of trains are known shortly (an hour or so) before the actual arrivals of the trains. Such variation in arrival times often necessitates delaying of trains (on the entry tracks) due to non-availability of platforms; these delays may also cause queuing up of trains on the tracks. While determining the optimum allocation the formulation takes into account the inconvenience caused due to (i) delay, (ii) allocation of non-preferred platforms (some platforms may be preferred for some trains - as is the case in India), and (iii) last minute reassignment of platforms. The constraints ensure that all physical and safety related restrictions are satisfied. Various problems developed from the schedule of arrivals at a busy station in India are also solved and the results analyzed.

    Place of possibility theory in transportation analysis

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    The transportation phenomena, as a manifestation of the complex human, social, economic, and political interactions, are filled with uncertainties. In order for the analysis of transportation to be scientifically credible, uncertainty must be accounted for properly. Traditionally, probability theory has been used as the only paradigm for dealing with uncertainty without much thought being given to its limits of application. In recent years, a systematized framework of uncertainty theory that handles different types of uncertainty has emerged. In this framework, possibility theory offers a useful way of handling the uncertain situations that often arise in transportation analysis, particularly when incomplete data and perception are involved. This paper describes possibility theory for its mathematical structure, and discusses the reasons why its use is justified for analysis of certain transportation problems. It is shown that the use of a particular theoretical framework depends on the type of information available and the nature of the predicate of the proposition. Probability theory is justified when the propensity of occurrence of well-defined events is the issue. Possibility theory, on the other hand, is justified when the information is partially perceived and evidence points to the nested sets. The dual measures of possibility theory, possibility and necessity, evaluate the truth, optimistically and conservatively. This paper advocates the use of a proper analysis framework that is consistent with the type of information. Such an attitude not only enhances the scientific credibility of the field but also allows the analyst to express how much is known and how much is not known honestly.

    Frameworks to Represent Uncertainty when Level of Service is Determined

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    The introduction of the concept of level of service (LOS) and the process to measure it are important contributions of the Highway Capacity Man ual(HCM). Recently, the usefulness and validity of the LOS categories have been reexamined. One underlying issue is how to handle uncertainty embedded in the definition of LOS, measurement of the flow condition, and matching the measured condition with the LOS categories. HCM suggests the “use of judgment” to handle uncertainty. The aspects of uncertainty involved in LOS analysis are examined, and different approaches to quantify the uncertainty, depending on its nature, are suggested. The truth of the statement “flow condition Xis LOS = Z” is determined by a deterministic, probabilistic, or possibilistic framework, depending on the character of Xand Z For varying combinations of Xand Z, different frames of analysis must be used. Six combinations of types of Xand Zare identified. One extreme is when both X and Zare assumed to be precise; such is the current HCM practice. The other extreme is when the boundaries of Z and X are assumed to be vague. Between these two extremes, four cases are identified, and an appropriate analytical framework is suggested for each. Results indicate that the aspects of uncertainty should be understood and that the mathematical framework selected for analysis should be consistent with the types of uncertainty involved. </jats:p

    New methods and strategies towards total synthesis of (9S)-dihydroerythronolide A

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    Disclosed are studies directed towards the total synthesis of (9S)-dihydroerythronolide A. Towards this goal an advanced intermediate, 14 member bis[allene] macrolactone was synthesized. A general method of cuprate-mediated carbon nucleophile delivery to spirodiepoxides was developed. An unprecedented macrolactonization to form bis[allene] macrolactone and macrocyclic stereocontroled epoxidation of this system was achieved. In a separate study, the highly stereocontroled formation of spirodiepoxides and excellent regiocontroled spirodiepoxide opening was developed. This method relies upon the presence of a silyl substituent on the allene. This finding was applied to the total synthesis of epicitreodiol.Ph.D.Includes bibliographical references
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