基于拟相对内部集值优化问题弱有效元的最优性条件

本文研究了基于拟相对内部的非凸集值优化问题弱有效元的最优性条件.首先,讨论了弱有效元与线性子空间之间的关系,利用涉及拟相对内部的凸集分离定理,获得了弱有效元的最优性条件.其次,给出了基于拟相对内部弱有效元的Lagrange乘子定理.     

水化硅酸钙纳米压痕分子动力学模拟方法优化

针对水化硅酸钙纳米压痕模型忽视了压头与基底之间相互作用的问题，由尺寸差异引起的金刚石压头难以计算的问题，以及Wittmann模型无法得到实际接触面积的问题，提出了新的模型与计算方法．结合分子动力学方法，采用金刚石压头-Wittmann模型基底的组合方式构建无定形态水化硅酸钙纳米压痕试验模型．在建模阶段，考虑到压头模型与基底模型粒子间尺寸差异，提出了等比例替换模型，通过公式推导并就不同尺寸模拟结果验证了等比例替换模型的可行性．在计算阶段，提出了局部前处理的弛豫方法进行模拟．确定最大荷载位置处的接触面积为546 nm2，进而求出水化硅酸钙模型硬度H为0.84 GPa、折合模量Er为30.52 GPa．并通过纳米压痕试验，验证了模拟结果的准确性，证明了模型的科学性，对今后水化硅酸钙(C-S-H)纳米层面的模拟具有重要借鉴意义．     

A lightweight cell switching and traffic offloading scheme for energy optimization in ultra-dense heterogeneous networks

One of the major capacity boosters for 5G networks is the deployment of ultra-dense heterogeneous networks (UDHNs). However, this deployment results in a tremendous increase in the energy consumption of the network due to the large number of base stations (BSs) involved. In addition to enhanced capacity, 5G networks must also be energy efficient for it to be economically viable and environmentally friendly. Dynamic cell switching is a very common way of reducing the total energy consumption of the network, but most of the proposed methods are computationally demanding, which makes them unsuitable for application in ultra-dense network deployment with massive number of BSs. To tackle this problem, we propose a lightweight cell switching scheme also known as Threshold-based Hybrid cEll swItching Scheme (THESIS) for energy optimization in UDHNs. The developed approach combines the benefits of clustering and exhaustive search (ES) algorithm to produce a solution whose optimality is close to that of the ES (which is guaranteed to be optimal), but is computationally more efficient than ES and as such can be applied for cell switching in real networks even when their dimension is large. The performance evaluation shows that THESIS significantly reduces the energy consumption of the UDHN and can reduce the complexity of finding a near-optimal solution from exponential to polynomial complexity.     

An artificial hummingbird algorithm based localization with reduced number of reference nodes for wireless sensor networks

Wireless Sensor Networks (WSN) are widely used in recent years due to the advancements in wireless and sensor technologies. Many of these applications require to know the location information of nodes. This information is useful to understand the collected data and to act on them. Existing localization algorithms make use of a few reference nodes for estimating the locations of sensor nodes. But, the positioning and utilization of reference nodes increase the cost and complexity of the network. To reduce the dependency on reference nodes, in this paper, we have developed a novel optimization based localization method using only two reference nodes for the localization of the entire network. This is achieved by reference nodes identifying a few more nodes as reference nodes by the analysis of the connectivity information. The sensor nodes then use the reference nodes to identify their locations in a distributive manner using Artificial Hummingbird Algorithm (AHA). We have observed that the localization performance of the reported algorithm at a lower reference node ratio is comparable with other algorithms at higher reference node ratios.     

A method of segment protection based on p-cycle for dynamic multicast with limited-range wavelength converter in WDM network

In the optical multicast network, node and link failures have very important influence on the network survivability which may lead to multiple destinations cannot receive data. Based on the wavelength layered-graph method, a method of efficiency-score based on heuristic algorithm of pre-configured cycle (p-Cycle) based-segment protection (ESHS) for dynamic multicast with limited-range wavelength conversion was presented in this paper. By finding the multicast tree segment protection, the total available p-Cycles are constructed for the multicast. Then we calculate each p-Cycle efficiency-score, the highest efficient-score p-Cycle is selected as the multicast route protection p-Cycle. The simulation results show that the ESHS can get higher performance than the existing ESHT algorithm, in terms of multicast request blocking probability and wavelength utilization.     

High level ab initio,DFT, and RRKM calculations for the unimolecular decomposition reaction of ethylamine

Mechanisms for the decomposition reaction of ethylamine, CH₃CH₂NH₂, were investigated using ab initio, DFT, and RRKM calculations. Optimized geometries of reactants, transition states, intermediates, and products were determined at HF, MP2, and B3LYP levels of theory using the 6-31G(d) and 6-31+G(d) basis sets. Single point energies were also determined at G3MP2B3 and G3B3 levels of theory. Thermodynamic properties, activation energies, enthalpies and Gibbs energies of activation were calculated for each reaction pathway investigated. Intrinsic reaction coordinate (IRC) analysis was performed to characterize the transition states on the potential energy surface. The conformational change and planarity of the ethylamine moiety along with the twist angle of the amino group about the CN axis are examined. Four pathways for the decomposition reaction of ethylamine were studied. All pathways involve a 1,2-elimination reaction and 1,3-proton shift to produce ethene, ethanimine, ethenamine, and methanimine. All pathways are single-step mechanisms. Elimination of the NH₃ dominates the decomposition behavior up to 1200 K whereas after this temperature, secession of the C–N gradually holds more importance. While pathways signifying departures of NH₃ and NH₂ exhibit pressure-dependent behavior, branching ratios for these two channels are generally not influenced by variation in pressure higher than the atmospheric pressure.     

Optimal deterministic algorithms for some variants of Online Quota Traveling Salesman Problem

This paper is concerned with the Online Quota Traveling Salesman Problem. Depending on the symmetry of the metric and the requirement for the salesman to return to the origin, four variants are analyzed. We present optimal deterministic algorithms for each variant defined on a general space, a real line, or a half-line. As a byproduct, an improved lower bound for a variant of Online TSP on a half-line is also obtained.     

基于马尔可夫决策过程的医疗检查预约优化模型

医技部门的医疗检查如电子计算机断层扫描（CT）、核磁共振成像设备（MRI）、X射线（X－rays）常常有如下三种病人类型：门诊病人、住院病人和急诊病人。针对不同病人类型的需求特点，运用马尔可夫决策过程原理和动态规划方法，建立了医疗检查设备的预约优化模型，并证明了模型的最优性质，得出了不同病人类型的最优预约策略。数值算例的结果表明：本文的预约策略不仅易于实施，而且，通过该模型获得的最大收益比按传统先来先预约的模式所获得的收益要大。