The Experts below are selected from a list of 254481 Experts worldwide ranked by ideXlab platform
Younes Hamdouch - One of the best experts on this subject based on the ideXlab platform.
-
schedule based transit assignment model with vehicle capacity and seat availability
Transportation Research Part B-methodological, 2011Co-Authors: Younes Hamdouch, Agachai Sumalee, Guodong WangAbstract:In this paper, we propose a new schedule-based equilibrium transit assignment model that differentiates the discomfort level experienced by sitting and standing passengers. The notion of seat allocation has not been considered explicitly and analytically in previous schedule-based frameworks. The model assumes that passengers use strategies when traveling from their origin to their destination. When loading a vehicle, standing on-board passengers continuing to the next station have priority to get available seats and waiting passengers are loaded on a First-Come-First-Serve (FCFS) principle. The stimulus of a standing passenger to sit increases with his/her remaining journey length and time already spent on-board. When a vehicle is full, passengers unable to board must wait for the next vehicle to arrive. The equilibrium conditions can be stated as a variational inequality involving a Vector-Valued Function of expected strategy costs. To find a solution, we adopt the method of successive averages (MSA) that generates strategies during each iteration by solving a dynamic program. Numerical results are also reported to show the effects of our model on the travel strategies and departure time choices of passengers.
-
schedule based transit assignment model with travel strategies and capacity constraints
Transportation Research Part B-methodological, 2008Co-Authors: Younes Hamdouch, Siriphong LawphongpanichAbstract:In this paper, we propose a user equilibrium transit assignment model that takes into account transit schedules and individual vehicle capacities explicitly. The model assumes that passengers use travel strategies that can be adaptive over time and graphically represented as subgraphs. When loading a vehicle, on-board passengers continuing to the next stop have priority and waiting passengers can be loaded on a first-come-first-serve basis or in a random manner. The latter is appropriate when passengers mingle on waiting platforms. When a vehicle is full, passengers unable to board must wait for the next vehicle to arrive. The equilibrium conditions can be stated as a variational inequality involving a Vector-Valued Function of expected strategy costs. Although the Function is not necessarily continuous or monotonic, a solution to the variational inequality exists. To find a solution, we propose a method that takes successive averages as its iterates and generates strategies during each iteration by solving a dynamic program. Numerical examples empirically demonstrate that the algorithm converges to an equilibrium solution.
Guodong Wang - One of the best experts on this subject based on the ideXlab platform.
-
schedule based transit assignment model with vehicle capacity and seat availability
Transportation Research Part B-methodological, 2011Co-Authors: Younes Hamdouch, Agachai Sumalee, Guodong WangAbstract:In this paper, we propose a new schedule-based equilibrium transit assignment model that differentiates the discomfort level experienced by sitting and standing passengers. The notion of seat allocation has not been considered explicitly and analytically in previous schedule-based frameworks. The model assumes that passengers use strategies when traveling from their origin to their destination. When loading a vehicle, standing on-board passengers continuing to the next station have priority to get available seats and waiting passengers are loaded on a First-Come-First-Serve (FCFS) principle. The stimulus of a standing passenger to sit increases with his/her remaining journey length and time already spent on-board. When a vehicle is full, passengers unable to board must wait for the next vehicle to arrive. The equilibrium conditions can be stated as a variational inequality involving a Vector-Valued Function of expected strategy costs. To find a solution, we adopt the method of successive averages (MSA) that generates strategies during each iteration by solving a dynamic program. Numerical results are also reported to show the effects of our model on the travel strategies and departure time choices of passengers.
Siriphong Lawphongpanich - One of the best experts on this subject based on the ideXlab platform.
-
schedule based transit assignment model with travel strategies and capacity constraints
Transportation Research Part B-methodological, 2008Co-Authors: Younes Hamdouch, Siriphong LawphongpanichAbstract:In this paper, we propose a user equilibrium transit assignment model that takes into account transit schedules and individual vehicle capacities explicitly. The model assumes that passengers use travel strategies that can be adaptive over time and graphically represented as subgraphs. When loading a vehicle, on-board passengers continuing to the next stop have priority and waiting passengers can be loaded on a first-come-first-serve basis or in a random manner. The latter is appropriate when passengers mingle on waiting platforms. When a vehicle is full, passengers unable to board must wait for the next vehicle to arrive. The equilibrium conditions can be stated as a variational inequality involving a Vector-Valued Function of expected strategy costs. Although the Function is not necessarily continuous or monotonic, a solution to the variational inequality exists. To find a solution, we propose a method that takes successive averages as its iterates and generates strategies during each iteration by solving a dynamic program. Numerical examples empirically demonstrate that the algorithm converges to an equilibrium solution.
Minhphuong Tran - One of the best experts on this subject based on the ideXlab platform.
-
new gradient estimates for solutions to quasilinear divergence form elliptic equations with general dirichlet boundary data
Journal of Differential Equations, 2019Co-Authors: Minhphuong Tran, Thanhnhan NguyenAbstract:Abstract This paper studies a new gradient regularity in Lorentz spaces for solutions to a class of quasilinear divergence form elliptic equations with nonhomogeneous Dirichlet boundary conditions: { div ( A ( x , ∇ u ) ) = div ( | F | p − 2 F ) in Ω , u = σ on ∂ Ω , where Ω ⊂ R n ( n ≥ 2 ), the nonlinearity A is a monotone Caratheodory vector valued Function defined on W 0 1 , p ( Ω ) for p > 1 and the p-capacity uniform thickness condition is imposed on the complement of our bounded domain Ω. Moreover, for given data F ∈ L p ( Ω ; R n ) , the problem is set up with general Dirichlet boundary data σ ∈ W 1 , p ( Ω ) . In this paper, the optimal good-λ type bounds technique is applied to prove some results of fractional maximal estimates for gradient of solutions. And the main ingredients are the action of the cut-off fractional maximal Functions and some local interior and boundary comparison estimates developed in previous works [45] , [52] , [53] and references therein.
-
cut off fractional maximal Functions and gradient estimates for quasilinear divergence form elliptic equations with nonhomogeneous dirichlet boundary data
arXiv: Analysis of PDEs, 2019Co-Authors: Minhphuong TranAbstract:This paper studies the gradient regularity in Lorentz spaces for solutions to a class of quasilinear elliptic equations of $p$-Laplacian type with nonhomogeneous Dirichlet boundary conditions: \begin{align*} \begin{cases} div(A(x,\nabla u)) &= \ div(|F|^{p-2}F) \quad \text{in} \ \ \Omega, \\ \hspace{1.2cm} u &=\ \sigma \qquad \qquad \qquad \text{on} \ \ \partial \Omega. \end{cases} \end{align*} where $\Omega \subset \mathbb{R}^n$ ($n \ge 2$), the nonlinearity $A$ is a monotone Caratheodory vector valued Function defined on $W^{1,p}_0(\Omega)$ for $p>1$ and the $p$-capacity uniform thickness condition is imposed on the complement of our bounded domain $\Omega$. Moreover, for given data $F \in L^p(\Omega;\mathbb{R}^n)$, the problem is set up with general Dirichlet boundary data $\sigma \in C^1(\partial\Omega)$. In this paper, the optimal good-$\lambda$ type bounds technique is applied to prove some results of fractional maximal estimates for gradient of solutions. And the main ingredients are the action of the cut-off fractional maximal Functions and some local interior and boundary comparison estimates developed in previous works \cite{55QH4, MPT2018, MPT2019} and references therein.
-
new gradient estimates for solutions to quasilinear divergence form elliptic equations with general dirichlet boundary data
arXiv: Analysis of PDEs, 2019Co-Authors: Minhphuong Tran, Thanhnhan NguyenAbstract:This paper studies a new gradient regularity in Lorentz spaces for solutions to a class of quasilinear divergence form elliptic equations with nonhomogeneous Dirichlet boundary conditions: \begin{align*} \begin{cases} div(A(x,\nabla u)) &= \ div(|F|^{p-2}F) \quad \text{in} \ \ \Omega, \\ \hspace{1.2cm} u &=\ \sigma \qquad \qquad \qquad \text{on} \ \ \partial \Omega. \end{cases} \end{align*} where $\Omega \subset \mathbb{R}^n$ ($n \ge 2$), the nonlinearity $A$ is a monotone Carath\'eodory vector valued Function defined on $W^{1,p}_0(\Omega)$ for $p>1$ and the $p$-capacity uniform thickness condition is imposed on the complement of our bounded domain $\Omega$. Moreover, for given data $F \in L^p(\Omega;\mathbb{R}^n)$, the problem is set up with general Dirichlet boundary data $\sigma \in W^{1-1/p,p}(\partial\Omega)$. In this paper, the optimal good-$\lambda$ type bounds technique is applied to prove some results of fractional maximal estimates for gradient of solutions. And the main ingredients are the action of the cut-off fractional maximal Functions and some local interior and boundary comparison estimates developed in previous works \cite{55QH4, MPT2018, MPT2019} and references therein.
-
good λ type bounds of quasilinear elliptic equations for the singular case
Nonlinear Analysis-theory Methods & Applications, 2019Co-Authors: Minhphuong TranAbstract:Abstract In this paper, we study the good- λ type bounds for renormalized solutions to nonlinear elliptic problem: − d i v ( A ( x , ∇ u ) ) = μ in Ω , u = 0 on ∂ Ω . where Ω ⊂ R n , μ is a finite Radon measure and A is a monotone Carathedory vector valued Function defined on W 0 1 , p ( Ω ) . The operator A satisfies growth and monotonicity conditions, and the p -capacity uniform thickness condition is imposed on R n ∖ Ω , for the singular case 3 n − 2 2 n − 1 p ≤ 2 − 1 n . In fact, the same good- λ type estimates were also studied by Quoc-Hung Nguyen and Nguyen Cong Phuc. For instance, in Nguyen and Phuc (0000) and Nguyen (0000) authors’ method was also confined to the case of 3 n − 2 2 n − 1 p ≤ 2 − 1 n but under the assumption of Ω is the Reifenberg flat domain and the coefficients of A have small BMO (bounded mean oscillation) semi-norms. Otherwise, the same problem was considered in Phuc (2014) in the regular case of p > 2 − 1 n . In this paper, we extend their results, taking into account the case 3 n − 2 2 n − 1 p ≤ 2 − 1 n and without the hypothesis of Reifenberg flat domain on Ω and small BMO semi-norms of A . Moreover, in rest of this paper, we also give the proof of the boundedness property of maximal Function on Lorentz spaces and also the global gradient estimates of solution.
Kaibin Huang - One of the best experts on this subject based on the ideXlab platform.
-
Reduced-Dimension Design of MIMO Over-the-Air Computing for Data Aggregation in Clustered IoT Networks
IEEE Transactions on Wireless Communications, 2019Co-Authors: Kaibin HuangAbstract:One basic operation of Internet-of-Things (IoT) networks is to acquire a Function of distributed data collected from sensors over wireless channels, called wireless data aggregation (WDA). In the presence of dense sensors, low-latency WDA poses a design challenge for high-mobility or mission critical IoT applications. A promising solution is a low-latency multi-access scheme, called over-the-air computing (AirComp), that supports simultaneous transmission such that an access point (AP) can estimate and receive a summation-form Function of the distributed sensing data by exploiting the waveform-superposition property of a multi-access channel. In this work, we propose a multiple-input-multiple-output (MIMO) AirComp framework for an IoT network with clustered multi-antenna sensors and an AP with large receive arrays. The framework supports low-complexity and low-latency AirComp of a Vector-Valued Function . The contributions of this work are two-fold. Define the AirComp error as the error in the Functional value received at AP due to channel noise. First, under the criterion of minimum error, the optimal receive beamformer at the AP, called decomposed aggregation beamformer (DAB), is shown to have a decomposed architecture: the inner component focuses on channel-dimension reduction and the outer component focuses on joint equalization of the resultant low-dimensional small-scale fading channels. In addition, an algorithm is designed to adjust the ranks of individual components of the DAB for a further performance improvement. Second, to provision DAB with the required channel state information (CSI), a low-latency channel feedback scheme is proposed by intelligently leveraging the AirComp principle to support simultaneous channel feedback by sensors. The proposed framework is shown by simulation to substantially reduce AirComp error compared with the existing design without considering channel structures.
-
Reduced-Dimension Design of MIMO Over-the-Air Computing for Data Aggregation in Clustered IoT Networks
arXiv: Information Theory, 2018Co-Authors: Kaibin HuangAbstract:One basic operation of Internet-of-Things (IoT) networks is aggregating distributed sensing-data over wireless-channels for Function-computation, called wireless-data-aggregation (WDA). Targeting dense sensors, a recently developed technology called over-the-air computing (AirComp) can dramatically reduce the WDA latency by aggregating distributed data "over-the-air" using the waveform-superposition property of a multi-access channel. In this work, we design multiple-input-multiple-output (MIMO) AirComp for computing a Vector-Valued Function in a clustered IoT network with multi-antenna sensors forming clusters and a multi-antenna access-point (AP) performing WDA. The resultant high-dimensional but low-rank MIMO channels makes it important to reduce channel or signal dimensionality in AirComp to avoid exposure to noise from channel null-spaces. Motivated by this, we develop a framework of reduced-dimension MIMO AirComp, featuring decomposed-aggregation-beamforming (DAB). Consider the case of separable channel-clusters with non-overlapping angle-of-arrival ranges. The optimal DAB has the structure where inner-components extract the dominant eigen-spaces of corresponding channel-clusters and outer-components jointly equalize the resultant low-dimensional channels. Consider the more complex case of inseparable clusters. We propose a suboptimal DAB design where the inner-component performs both dimension-reduction and joint-equalization over clustered-channel covariance matrices and the outer-component jointly equalizes the small-scale fading-channels. Furthermore, efficient algorithms for rank-optimization of individual DAB components and channel-feedback leveraging the AirComp principle are developed.
