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Niu H.,Lanzhou Jiaotong University | Zhou X.,Arizona State University
Transportation Research Part C: Emerging Technologies

This article focuses on optimizing a passenger train timetable in a heavily congested urban rail corridor. When peak-hour demand temporally exceeds the maximum loading capacity of a train, passengers may not be able to board the next arrival train, and they may be forced to wait in queues for the following trains. A binary integer programming model incorporated with passenger loading and departure events is constructed to provide a theoretic description for the problem under consideration. Based on time-dependent, origin-to-destination trip records from an automatic fare collection system, a nonlinear optimization model is developed to solve the problem on practically sized corridors, subject to the available train-unit fleet. The latest arrival time of boarded passengers is introduced to analytically calculate effective passenger loading time periods and the resulting time-dependent waiting times under dynamic demand conditions. A by-product of the model is the passenger assignment with strict capacity constraints under oversaturated conditions. Using cumulative input-output diagrams, we present a local improvement algorithm to find optimal timetables for individual station cases. A genetic algorithm is developed to solve the multi-station problem through a special binary coding method that indicates a train departure or cancellation at every possible time point. The effectiveness of the proposed model and algorithm are evaluated using a real-world data set. © 2013 Elsevier Ltd. Source

Sun B.,Tongji University | Ma W.,Lanzhou Jiaotong University
Artificial Intelligence Review

Recently, the theory and applications of soft set has brought the attention by many scholars in various areas. Especially, the researches of the theory for combining the soft set with the other mathematical theory have been developed by many authors. In this paper, we propose a new concept of soft fuzzy rough set by combining the fuzzy soft set with the traditional fuzzy rough set. The soft fuzzy rough lower and upper approximation operators of any fuzzy subset in the parameter set were defined by the concept of the pseudo fuzzy binary relation (or pseudo fuzzy soft set) established in this paper. Meanwhile, several deformations of the soft fuzzy rough lower and upper approximations are also presented. Furthermore, we also discuss some basic properties of the approximation operators in detail. Subsequently, we give an approach to decision making problem based on soft fuzzy rough set model by analyzing the limitations and advantages in the existing literatures. The decision steps and the algorithm of the decision method were also given. The proposed approach can obtain a object decision result with the data information owned by the decision problem only. Finally, the validity of the decision methods is tested by an applied example.©Springer Science+Business Media B.V. 2011. Source

Yan E.,Lanzhou Jiaotong University
Physica B: Condensed Matter

Pseudopotentials and plane-wave basis set method is used to investigate the electronic structure and magnetic properties for state-of-the-art zinc-blende and rocksalt M N (M=K, Na) alloys. We find that these compounds exhibit half-metallic characters with an integer magnetic moment of 2.00 μB. The half-metallic properties result from a fully spin-polarization of s and p states. The origin of energy gap mainly comes from the hybridization both s and p states. Total energies calculations indicate the rocksalt phase is lower in energy than the zinc-blende one. The difference of total energy are about 0.035 Ry per formula unit for KN and NaN, respectively. For these compounds, SlaterPauling curve Mt=( Zt-4) (in μB unit) is obeyed between valence electrons and total magnetic moment. Meanwhile, we also find the preservation of half metallic characters when the lattice parameter is moderate compressed. © 2011 Elsevier B.V.All rights reserved. Source

Incorporation of fillers with high thermal conductivity to base materials has been recognized as an efficient way to increase the thermal conductivity of composite materials. In this study, the effects of the prismatic filler arrangement and cross-sectional shape on the thermal conductivity of the composites were investigated. This research addresses these problems by solving the heterogeneous two-dimensional heat conduction problem in the composite materials. A validated commercial software-FLUENT and finite volume method was used in the analysis. The close-packed, directional and random filler arrangements were considered. It was found that the prismatic filler arrangement and cross-sectional shape have great impacts on the thermal conductivity of the composite materials. Double Y shaped, I shaped, T shaped, elliptical, rhombic and rectangular cross-sectional fillers can greatly increase the thermal conductivity only in directional arrangement. The effects of circular, square, triangular and Y shaped cross-sectional are similar in directional and random arrangements. The close-packed arrangements for all cross-sectional shapes have small thermal conductivity. The double Y shaped, Y shaped and I shaped cross-sectional were found to be the best choice for composite materials regardless of the filler arrangements. © BME-PT. Source

Niu H.,Lanzhou Jiaotong University
International Journal of Computational Intelligence Systems

This study focuses on how to determine the skip-stop scheduling for a congested urban transit line during the morning rush hours. A transit schedule with uneven headways and skip-stop operations is adopted to match the time-dependent demands and accelerate the circulative utilizations of vehicles. This schedule allows the buses to run on unequal vehicle-departure intervals and to skip some stations. A nonlinear programming model is formulated to minimize the overall waiting times and the in-vehicle crowded costs subjected to a limited number of vehicles. According to the layered characteristics of the skip-stop scheduling, a bilevel genetic algorithm is developed to solve the proposed model. The possible departure times of vehicles at the terminal are searched by the outer genetic algorithm and the skip-stop operations are solved by the inner genetic algorithm. Finally, the proposed model and algorithm are successfully tested with the help of a real-world case. © 2011 Copyright Taylor and Francis Group, LLC. Source

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