Solving Mathematical Programs with Equilibrium Constraints as Nonlinear Programming: A New Framework

We present a new framework for the solution of mathematical programs with equilibrium constraints (MPECs). In this algorithmic framework, an MPECs is viewed as a concentration of an unconstrained optimization which minimizes the complementarity measure and a nonlinear programming with general constraints. A strategy generalizing ideas of Byrd-Omojokun's trust region method is used to compute steps. By penalizing the tangential constraints into the objective function, we circumvent the problem of not satisfying MFCQ. A trust-funnel-like strategy is used to balance the improvements on feasibility and optimality. We show that, under MPEC-MFCQ, if the algorithm does not terminate in finite steps, then at least one accumulation point of the iterates sequence is an S-stationary point

Counterions and water molecules in charged silicon nanochannels: the influence of surface charge discreteness

In order to detect the effect of the surface charge discreteness on the properties at the solid-liquid interface, molecular dynamics simulation model taking consideration of the vibration of wall atoms was used to investigate the ion and water performance under different charge distributions. Through the comparison between simulation results and the theoretical prediction, it was found that, with the degree of discreteness increasing, much more counterions were attracted to the surface. These ions formed a denser accumulating layer which located much nearer to the surface and caused charge inversion. The ions in this layer were non-hydrated or partially hydrated. When a voltage was applied across the nanochannel, this dense accumulating layer did not move unlike the ions near uniformly charged surface. From the water density profiles obtained in nanochannels with different surface charge distributions, the influence of the surface charge discreteness on the water distributions could be neglected

Analysis and Optimization of Cellular Network with Burst Traffic

In this paper, we analyze the performance of cellular networks and study the optimal base station (BS) density to reduce the network power consumption. In contrast to previous works with similar purpose, we consider Poisson traffic for users' traffic model. In such situation, each BS can be viewed as M/G/1 queuing model. Based on theory of stochastic geometry, we analyze users' signal-to-interference-plus-noise-ratio (SINR) and obtain the average transmission time of each packet. While most of the previous works on SINR analysis in academia considered full buffer traffic, our analysis provides a basic framework to estimate the performance of cellular networks with burst traffic. We find that the users' SINR depends on the average transmission probability of BSs, which is defined by a nonlinear equation. As it is difficult to obtain the closed-form solution, we solve this nonlinear equation by bisection method. Besides, we formulate the optimization problem to minimize the area power consumption. An iteration algorithm is proposed to derive the local optimal BS density, and the numerical result shows that the proposed algorithm can converge to the global optimal BS density. At the end, the impact of BS density on users' SINR and average packet delay will be discussed.Comment: This paper has been withdrawn by the author due to missuse of queue model in Section Fou

A first order system least squares method for the Helmholtz equation

We present a first order system least squares (FOSLS) method for the Helmholtz equation at high wave number k, which always deduces Hermitian positive definite algebraic system. By utilizing a non-trivial solution decomposition to the dual FOSLS problem which is quite different from that of standard finite element method, we give error analysis to the hp-version of the FOSLS method where the dependence on the mesh size h, the approximation order p, and the wave number k is given explicitly. In particular, under some assumption of the boundary of the domain, the L2 norm error estimate of the scalar solution from the FOSLS method is shown to be quasi optimal under the condition that kh/p is sufficiently small and the polynomial degree p is at least O(\log k). Numerical experiments are given to verify the theoretical results