2,649 research outputs found
An analysis of parking behaviour using discrete choice models calibrated on SP datasets
Parking policy is an important component of contemporary travel demand management policies. The effectiveness of many parking policy measures depends on influencing parking type choice, so that understanding the factors affecting these choices is of considerable practical importance. Yet, academic interest in this issue has been, at best, intermittent. This paper reports the results of an analysis of parking choice behaviour, based on a stated preference (SP) dataset, collected in various city centre locations in the UK. The analysis advances the state of the art in the analysis of parking choice behaviour by using a mixed multinomial logit (MMNL) model, capable of accommodating random heterogeneity in travellers’ tastes and potential correlation structure induced by repeated observations being made of the same individuals. The results of the analysis indicate that taste heterogeneity is a major factor in parking type choice. Accommodating this heterogeneity leads to significantly different conclusions regarding the influence of substantive factors such as access, search and egress time and on the treatment of potential fines for illegal parking. It also has important effects on the implied willingness to pay for timesavings and on the distribution of this willingness in the population. Our analysis also reveals important differences in parking behaviour across different journey purposes, and the models reveal an important locational effect, in such that the results of the analysis vary substantively across the three locations used in the SP surveys. Finally, the paper also discusses a number of technical issues related to the specification of taste heterogeneity that are of wider significance in the application of the MMNL model.
Tools for Quantum Algorithms
We present efficient implementations of a number of operations for quantum
computers. These include controlled phase adjustments of the amplitudes in a
superposition, permutations, approximations of transformations and
generalizations of the phase adjustments to block matrix transformations. These
operations generalize those used in proposed quantum search algorithms.Comment: LATEX, 15 pages, Minor changes: one author's e-mail and one reference
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Quantum rotor description of the Mott-insulator transition in the Bose-Hubbard model
We present the novel approach to the Bose-Hubbard model using the
quantum rotor description. The effective action formalism
allows us to formulate a problem in the phase only action and obtain an
analytical formulas for the critical lines. We show that the nontrivial
phase field configurations have an impact on the phase
diagrams. The topological character of the quantum field is governed by terms
of the integer charges - winding numbers. The comparison presented results to
recently obtained quantum Monte Carlo numerical calculations suggests that the
competition between quantum effects in strongly interacting boson systems is
correctly captured by our model.Comment: accepted to PR
A unified evaluation of iterative projection algorithms for phase retrieval
Iterative projection algorithms are successfully being used as a substitute
of lenses to recombine, numerically rather than optically, light scattered by
illuminated objects. Images obtained computationally allow aberration-free
diffraction-limited imaging and the possibility of using radiation for which no
lenses exist. The challenge of this imaging technique is transfered from the
lenses to the algorithms. We evaluate these new computational ``instruments''
developed for the phase retrieval problem, and discuss acceleration strategies.Comment: 12 pages, 9 figures, revte
An Introduction to Quantum Computing for Non-Physicists
Richard Feynman's observation that quantum mechanical effects could not be simulated efficiently on a computer led to speculation that computation in general could be done more efficiently if it used quantum effects. This speculation appeared justified when Peter Shor described a polynomial time quantum algorithm for factoring integers. In quantum systems, the computational space increases exponentially with the size of the system which enables exponential parallelism. This parallelism could lead to exponentially faster quantum algorithms than possible classically. The catch is that accessing the results, which requires measurement, proves tricky and requires new non-traditional programming techniques. The aim of this paper is to guide computer scientists and other non-physicists through the conceptual and notational barriers that separate quantum computing from conventional computing. We introduce basic principles of quantum mechanics to explain where the power of quantum computers comes from and why it is difficult to harness. We describe quantum cryptography, teleportation, and dense coding. Various approaches to harnessing the power of quantum parallelism are explained, including Shor's algorithm, Grover's algorithm, and Hogg's algorithms. We conclude with a discussion of quantum error correction
Knapsack and Subset Sum with Small Items
Knapsack and Subset Sum are fundamental NP-hard problems in combinatorial optimization. Recently there has been a growing interest in understanding the best possible pseudopolynomial running times for these problems with respect to various parameters. In this paper we focus on the maximum item size s and the maximum item value v. We give algorithms that run in time O(n + s³) and O(n + v³) for the Knapsack problem, and in time Õ(n + s^{5/3}) for the Subset Sum problem. Our algorithms work for the more general problem variants with multiplicities, where each input item comes with a (binary encoded) multiplicity, which succinctly describes how many times the item appears in the instance. In these variants n denotes the (possibly much smaller) number of distinct items. Our results follow from combining and optimizing several diverse lines of research, notably proximity arguments for integer programming due to Eisenbrand and Weismantel (TALG 2019), fast structured (min,+)-convolution by Kellerer and Pferschy (J. Comb. Optim. 2004), and additive combinatorics methods originating from Galil and Margalit (SICOMP 1991)
Modelling airport and airline choice behaviour with the use of stated preference survey data
The majority of studies of air travel choice behavior make use of revealed preference (RP) data, generally in the form of survey data collected from departing passengers. While the use of RP data has certain methodological advantages over the use of stated preference (SP) data, major issues arise because of the often low quality of the data relating to the un-chosen alternatives, in terms of explanatory variables as well as availability. As such, studies using RP survey data often fail to recover a meaningful fare coefficient, and are generally not able to offer a treatment of the effects of airline allegiance. In this paper, we make use of SP data for airport and airline choice collected in the US in 2001. The analysis retrieves significant effects relating to factors such as airfare, access time, flight time and airline and airport allegiance, illustrating the advantages of SP data in this context. Additionally, the analysis explores the use of non-linear transforms of the explanatory variables, as well as the treatment of continuous variations in choice behavior across respondents
Global and Local Information in Traffic Congestion
A generic network flow model of transport (of relevance to information
transport as well as physical transport) is studied under two different control
protocols. The first involves information concerning the global state of the
network, the second only information about nodes' nearest neighbors. The global
protocol allows for a larger external drive before jamming sets in, at the
price of significant larger flow fluctuations. By triggering jams in
neighboring nodes, the jamming perturbation grows as a pulsating core. This
feature explains the different results for the two information protocols.Comment: 4 pages, 5 figures, preprint; corrected typos and minor format issue
Analiza materijala i protoka informacija u logističkom sustavu neke odabrane čeličane
Tough competition on the steel product market causes the functioning of steelworks largely to depend on their abilities to respond flexibly to the market needs and offer the right product, at the right price and in the right time. A tool which is more and more commonly used for achieving this goal is logistics. The function of logistics in a production company is the optimal shaping of the stream of materials and information flowing through the company. The article reports the result of an analysis of material and information flows on the example of a selected metallurgical enterprise.Jaka konkurencija na tržištu čeličnih proizvoda dovodi do toga da funkcioniranje čeličana uvelike ovisi o njihovoj sposobnosti da fleksibilno odgovore potrebama tržišta i ponude pravi proizvod po pravoj cijeni u pravo vrijeme. Sve se više koristi za postizanje tog cilja logistika. Funkcija logistike u nekom proizvodnom poduzeću je u tome da osigura optimalan protok materijala i informacija kroz poduzeće. Članak predstavlja rezultat analize protoka materijala i informacija na primjeru jednog metalurškog poduzeća
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