考虑避碰约束的编队卫星入网路径规划

提出了一种新的考虑避碰约束的编队卫星入网路径规划策略。首先通过常规编队卫星入网的多脉冲线性规划方法,得到一组卫星入网的脉冲序列,以此预测轨道机动过程中各星之间的最小距离,当最小距离小于安全距离时,将最小距离前后脉冲施加时刻的相对位置作为约束条件,重新规划卫星入网轨迹,迭代进行直到满足避碰要求。仿真结果表明,该方法由于减少了路径规划过程中约束条件的个数,能够快速地规划出考虑避碰约束时的编队卫星入网轨迹,且有效节省燃料消耗。     

民办高校教务管理信息化建设实践与展望——以江西科技学院为例

近年来,随着我校教学改革不断深化,招生规模越来越大和培养目标的转变,不断增加了教务管理的工作难度。为了满足我校应用型本科教育的需要,原有的教务管理系统已成为教学管理的瓶颈,教务系统的更新和升级已经迫在眉睫。教务管理怎样去适应当前学校发展的新举措,提高教学质量和管理水平,实现学校打造精品加特色的培养目标,培育出适应社会需求的各种人才,为区域经济发展服务,是我校教务管理人员急需解决的重要问题。     

高校新区建设项目后评估研究

阐述了新校区建设项目后评估的内容,对目前新校区建设项目存在的项目建设目标的完成情况不够理想、学校负债严重、对社会和环境的影响的评估不够全面和师生满意度不高等问题进行了分析和探讨,提出充分共享资源、多渠道筹措资金和加强节约型校园建设的后评估建议。     

一种新的边缘检测算法研究

为了提高边缘检测的运行效率和检测精度,提出了一种新的边缘检测算法,该算法由一个自适应神经模糊推理系统和一个后处理程序组成.选取与边缘方向和梯度双重信息相关的4个目标函数作为自适应神经模糊推理系统的输入,采用计算机合成图像对自适应神经模糊推理系统进行训练.运用一个后处理程序,判断自适应神经模糊推理系统的输出值是否小于门限值,若小于则该像素点为边缘点.仿真实验表明,该方法边缘检测效果优于传统方法和当前文献报道方法.     

基于目标函数的递推子空间辨识算法

针对实际工程中要求对系统参数进行在线估计的问题, 提出一种递推子空间辨识的新方法. 通过引入辅助变量关系将递推子空间辨识问题转化为目标函数的迭代最小化问题. 采用递推最小二乘算法在线估计参数并由传播方法得到更新的广义能观性矩阵, 进而求得子空间辨识模型系统参数. 该算法简单有效且对初值具有鲁棒性. 最后, 通过仿真实例验证算法的有效性.     

大间距无监督正交特征提取算法

以主成分分析和局部保持投影为理论基础,提出了一种同时考虑数据样本的全局和局部特性的大间距无监督正交特征提取算法,算法的目标函数采用大间距准则,避免了由于矩阵求逆带来的小样本问题,同时为了进一步增强算法的识别性能,对所求取的投影矩阵进行了正交化约束,最后人脸库上的实验结果表明所提方法的有效性.     

An integrated model for closed-loop supply chain configuration and supplier selection: Multi-objective approach

Reverse logistics consists of all operations related to the reuse of products. External suppliers are one of the important members of reverse logistics and closed loop supply chain (CLSC) networks. However in CLSC network configuration models, suppliers are assessed based on purchasing cost and other factors such as on-time delivery are ignored. In this research, a general closed loop supply chain network is examined that includes manufacturer, disassembly, refurbishing, and disposal sites. Meanwhile, it is managed by the manufacturer. We propose an integrated model which has two phases. In the first phase, a framework for supplier selection criteria in RL is proposed. Besides, a fuzzy method is designed to evaluate suppliers based on qualitative criteria. The output of this stage is the weight of each supplier according to each part. In the second phase, we propose a multi objective mixed-integer linear programming model to determine which suppliers and refurbishing sites should be selected (strategic decisions), and find out the optimal number of parts and products in CLSC network (tactical decisions). The objective functions maximize profit and weights of suppliers, and one of them minimizes defect rates. To our knowledge, this model is the first effort to consider supplier selection, order allocation, and CLSC network configuration, simultaneously. The mathematical programming model is validated through numerical analysis.     

Multi‐objective optimization using metaheuristics: non‐standard algorithms

In recent years, the application of metaheuristic techniques to solve multi‐objective optimization problems has become an active research area. Solving this kind of problems involves obtaining a set of Pareto‐optimal solutions in such a way that the corresponding Pareto front fulfils the requirements of convergence to the true Pareto front and uniform diversity. Most of the studies on metaheuristics for multi‐objective optimization are focused on Evolutionary Algorithms, and some of the state‐of‐the‐art techniques belong this class of algorithms. Our goal in this paper is to study open research lines related to metaheuristics but focusing on less explored areas to provide new perspectives to those researchers interested in multi‐objective optimization. In particular, we focus on non‐evolutionary metaheuristics, hybrid multi‐objective metaheuristics, parallel multi‐objective optimization and multi‐objective optimization under uncertainty. We analyze these issues and discuss open research lines.     

Integrating carrier selection with supplier selection decisions to improve supply chain security

Supply chain security is a major concern for logistics managers who have responsibility for inbound and outbound shipments to and from both domestic and international locations. We propose here that logistics decisions concerning security in the supply chain will be made more effectively when made in concert with decisions in related supply chain processes, especially supplier and carrier selection. Indeed, managers may minimize cost, transit time, and security risk by integrating decision processes internally, as well as with their carrier's and supplier's operations. Thus, we account for both intra‐firm collaboration between logistics and purchasing managers, as well as inter‐firm collaboration among buyers, suppliers, and carriers in a supply chain. In this paper, we propose a decision process that features a set of security rules and a multi‐objective optimization model to accomplish this aim. We then provide an illustration to demonstrate the potential usefulness of these concepts in practice.     

New approaches for determining a common set of weights for a voting system

Data Envelopment Analysis (DEA) is one of the methods that have been proposed to determine the weights in a ranked voting system. DEA solves one model corresponding to each candidate and evaluates candidates with their own weights. However, sometimes solving only one model, and evaluating the candidates based on a common set of weights, is preferred. In this paper, some drawbacks of existing models are explained and new approaches for determining a common set of weights are proposed. Numerical examples are utilized to illustrate the content of the paper.