DATA-DRIVEN CAPACITY MANAGEMENT AND REVENUE MAXIMIZATION OF RIDE-HAILING SERVICE WITH PRESCRIPTIVE ANALYTICS AND DEEP LEARNING

This paper studies capacity management of ride-hailing service with unstable passenger demand. In existing parametric approaches in the literature, normally a two-stage prediction-then-optimization (PTO) paradigm is used to implement demand prediction, capacity and revenue optimization sequentially, which generally achieves suboptimal performance due to the information loss in demand prediction. To attain optimality, in this study, we integrate these two stages into a prediction & optimization (P&O) paradigm considering both Cobb-Douglas matching function and perfect matching function, and formulate a weighted sample average approximation (WSAA) approach embedded with k-nearest neighbors, kernel regression and decision tree, as well as an innovative deep learning approach that couples decomposition, convolution, and attention together. The WSAA approach was proven to be asymptotically optimal when a sufficient number of samples are collected, while the deep learning approach based on P&O paradigm demonstrated superior performance in capacity management. Finally, as an extension, we combine WSAA and deep learning approaches to potentially achieve further improvement on optimality

Superior thermal conductivity and extremely high mechanical strength in polyethylene chains from {\it ab initio} calculation

The upper limit of the thermal conductivity and the mechanical strength are predicted for the polyethylene chain, by performing the {\it ab initio} calculation and applying the quantum mechanical non-equilibrium Green's function approach. Specially, there are two main findings from our calculation: (1). the thermal conductivity can reach a high value of 310 W/K/m in a 100 nm polyethylene chain at room temperature; (2). the Young's modulus in the polyethylene chain is as high as 374.5 GPa, and the polyethylene chain can sustain $32.85$ (ultimate) strain before undergoing structural phase transition into gaseous ethylene.Comment: published in J. Appl. Phys. (2012

Stability of a Class of Coupled Systems

We consider a class of coupled systems with damping terms. By using multiplier method and the estimation techniques of the energy, we show that even if the kernel function is nonincreasing and integrable without additional conditions, the energy of the system decays also to zero in a good rate

Universal R-matrix Of The Super Yangian Double DY(gl(1|1))

Based on Drinfeld realization of super Yangian Double DY(gl(1|1)), its pairing relations and universal R-matrix are given. By taking evaluation representation of universal R-matrix, another realization $L^{\pm}(u)$ of DY(gl(1|1)) is obtained. These two realizations of DY(gl(1|1)) are related by the supersymmetric extension of Ding-Frenkel map.Comment: 6 pages, latex, no figure