一种求解半定规划的邻近外梯度算法

本文提出了一种求解半定规划的邻近外梯度算法.通过转化半定规划的最优性条件为变分不等式,在变分不等式满足单调性和Lipschitz连续的前提下,构造包含原投影区域的半空间,产生邻近点序列来逼近变分不等式的解,简化了投影的求解过程.将该算法应用到教育测评问题中,数值实验结果表明,该方法是解大规模半定规划问题的一种可行方法.     

Coincidences of Nonself Operators by a Simpler Algorithm

Abstract

In this article, we introduce a new class of contractive mappings and study analytical and computational aspects of a special case of Jungck-Khan iterative algorithm generated by this class of mappings. In particular, we improve upon strong convergence, rate of convergence and data dependence results existing in the current literature. Analytical as well numerical illustrative examples are given to support the new results.     

Optimization of a highway project planning using a modified genetic algorithm

This paper proposes an optimization method for a national-level highway project planning based on a modified genetic algorithm. The proposed method adds to the existing methods by integrating various planning elements into a single system. A simulation model is used in order to determine the best investment strategy with regard to net present value, time deviation from the initial plan and discrepancy between available resources and investment costs by taking into account economical, social, traffic and political factors. The outcome is a project schedule with an optimized cash flow. The proposed method was tested using the example of the National Highway Programme in Slovenia.     

An algorithm for a bilevel problem with equilibrium and fixed point constraints

We prove the solution existence and propose an iterative algorithm for solving equilibrium problems over the common solutions of a monotone equilibrium problem and the fixed points of a strictly pseudocontractive mapping in Hilbert spaces. The algorithm is a combination of the proximal point and Halpern methods. Strong convergence is established.     

Inertial methods for fixed point problems and zero point problems of the sum of two monotone mappings

ABSTRACT

The purpose of this paper is to investigate the problem of finding a common element of the set of zero points of the sum of two operators and the fixed point set of a quasi-nonexpansive mapping. We introduce modified forward-backward splitting methods based on the so-called inertial forward-backward splitting algorithm, Mann algorithm and viscosity method. We establish weak and strong convergence theorems for iterative sequences generated by these methods. Our results extend and improve some related results in the literature.     

A simple but NP-hard problem of mixed-discrete programming and its solution by approximate algorithms

A NP-hard problem (P) of mixed-discrete linear programming is considered which consists in the minimization of a linear objective function subject to a special non-connected subset of an unbounded polymatroid. For this problem we describe three polynomial approximate algorithms including a greedy algorithm and a fully polynomial approximation scheme solving a special subproblem of (P).     

基于价格选择的集配一体化车辆路径问题研究

在家电的集配一体化过程中,回收价格不仅影响企业的回收成本,而且同样影响车辆路径,然而在家电集配过程中回收价格因素一直未能引起足够的重视.为此,以回收价格为出发点,通过定价系统根据产品可再生利用价值与制造商所给的回收价格的差别研究车辆路径优化问题,建立该问题的数学规划模型,同时结合家电集配一体化的实际性和复杂性的要求设计了改进遗传算法.最后,结合算例进行仿真计算,验证了模型与算法的有效性.     

电动汽车充电站选址问题研究

研究了电动汽车作为通勤工具情况下的充电站选址问题.首先根据城市通勤道路长度、各条道路上的通勤人员拟使用电动汽车的数量,以及电动汽车的最大续航里程等信息,构建了包含两种边的赋权网络图,进一步将电动汽车充电站选址问题转化为赋权网络图的最大覆盖问题,并建立了以极大化满足用户需求为目标的充电站选址问题整数非线性规划模型,设计了求解模型的启发式算法.最后,通过一个具体算例对模型及算法进行了验证,结果显示,模型和算法是解决电动汽车充电站选址问题有效方法.     

基于遗传算法和神经网络的注塑工艺参数优化

基于Moldflow模拟仿真的结果,结合GA算法优化BP网络的结构,建立了模具温度,熔体温度,保压压力,注射速度等工艺参数与塑件体积收缩率的BP网络模型.获得了最优的工艺参数组合,同时预测结果与实际结果吻合.通过神经网络算法(BP)预测注塑工艺参数对塑件质量的影响,可以有效降低其他建模方法的难度和工作量,方法可以推广到塑件其他质量预测过程中.     

基于介质温度数值分布规律的冰盖厚度检测分析方法

针对水文预报领域冰层厚度检测过程中对空气与冰层、冰层与冰下水层的分界点难以判断的难题,提出了一种基于介质温度数值分布规律的冰层厚度检测分析方法.新方法在对空气与冰层、冰层与冰下水层的分界点进行分析判断时采用了聚类分析思想,通过采用改进属性归类规则的K-means算法,对采集到的空气、冰与水不同介质的温度数值分布数据进行分类,并对各自属性的温度梯度分布数据集合进行线性拟合,从各拟合曲线交点可以获得空气与冰层、冰层与冰下水层的分界点,进而计算出冰层厚度数值.采用这一方法对2014.12-2015.3内蒙包头黄河河道冰情采集数据进行分析,证明了新方法的可行性.