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城市发展视域下首钢工业遗产保护开发路径及经验启示

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城市学刊 2024年第2期45卷 103-108页

作者：韩露孟芝晴武汉理工大学马克思主义学院武汉430070

工业遗产的保护开发影响着城市发展的质量和水平。以工业遗产的保护开发协同城市的发展建设,是城市治理过程中必须思考的问题之一。首钢工业遗产的保护开发具有重要的历史、文化和经济价值,其在保护开发中采取了积极谋求转型发展、深挖... 详细信息

工业遗产的保护开发影响着城市发展的质量和水平。以工业遗产的保护开发协同城市的发展建设,是城市治理过程中必须思考的问题之一。首钢工业遗产的保护开发具有重要的历史、文化和经济价值,其在保护开发中采取了积极谋求转型发展、深挖文化底蕴、找准战略定位以及抓住重要战略机遇期等方面的举措,在深化城市功能、发挥城市特色、促进城市发展、激活城市潜力等方面,给中国其他地区工业遗产的保护开发提供了经验启示和借鉴蓝本。

关键词：城市发展首钢工业遗产保护开发

DYNAMIC CVAR WITH MULTI-PERIOD RISK PROBLEMS

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Journal of Systems Science & Complexity 2011年第5期24卷 907-918页

作者： zhiqing meng Min JIANG Qiying HU College of Business and Administration Zhejiang University of Technology Hangzhou 310023 China School of Management Fudan University Shanghai 200433 China

This paper studies multi-period risk management problems by presenting a dynamic risk measure. This risk measure is the sum of conditional value-at-risk of each period. The authors model it by Markov decision processes and derive its optimality equation. This equation is further transformed equivalently to an analytically tractable one. The authors then use the model and its results to a multi-period portfolio optimization when the return rate vectors at each period form a Markov chain.

关键词： α-CVaR multi-period optimality equation optimal policy.

An M-Objective Penalty Function Algorithm Under Big Penalty Parameters

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Journal of Systems Science & Complexity 2016年第2期29卷 455-471页

作者： ZHENG Ying meng zhiqing SHEN Rui Basic College Ningbo Dahongying University College of Economics and Management Zhejiang University of Technology

Some classical penalty function algorithms may not always be convergent under big penalty parameters in Matlab software,which makes them impossible to find out an optimal solution to constrained optimization *** this paper,a novel penalty function(called M-objective penalty function) with one penalty parameter added to both objective and constrained functions of inequality constrained optimization problems is *** on the M-objective penalty function,an algorithm is developed to solve an optimal solution to the inequality constrained optimization problems,with its convergence proved under some ***,numerical results show that the proposed algorithm has a much better convergence than the classical penalty function algorithms under big penalty parameters,and is efficient in choosing a penalty parameter in a large range in Matlab software.

关键词： Algorithm constrained optimization problem M-objective penalty function stability.

A QUADRATIC OBJECTIVE PENALTY FUNCTION FOR BILEVEL PROGRAMMING

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Journal of Systems Science & Complexity 2014年第2期27卷 327-337页

作者： JIANG Min meng zhiqing SHEN Rui XU Xinsheng College of Business and Administration Zhejiang University of Technology

The bilevel programming is applied to solve hierarchical intelligence control problems in such fields as industry, agriculture, transportation, military, and so on. This paper presents a quadratic objective penalty function with two penalty parameters for inequality constrained bilevel programming. Under some conditions, the optimal solution to the bilevel programming defined by the quadratic objective penalty function is proved to be an optimal solution to the original bilevel programming. Moreover, based on the quadratic objective penalty function, an algorithm is developed to l^nd an optimal solution to the original bilevel programming, and its convergence proved under some conditions. Furthermore, under the assumption of convexity at function without lower level problems is defined and lower level problems, a quadratic objective penalty is proved equal to the original bilevel programming.

关键词： Algorithm bilevel programming penalty function quadratic objective.

A New Augmented Lagrangian Objective Penalty Function for Constrained Optimization Problems

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Open Journal of Optimization 2017年第2期6卷 39-46页

作者： Ying Zheng zhiqing meng Department of Basic Courses College of Basic Science Ningbo Dahongying University Ningbo China College of Economics and Management Zhejiang University of Technology Hangzhou China

In this paper, a new augmented Lagrangian penalty function for constrained optimization problems is studied. The dual properties of the augmented Lagrangian objective penalty function for constrained optimization problems are proved. Under some conditions, the saddle point of the augmented Lagrangian objective penalty function satisfies the first-order Karush-Kuhn-Tucker (KKT) condition. Especially, when the KKT condition holds for convex programming its saddle point exists. Based on the augmented Lagrangian objective penalty function, an algorithm is developed for finding a global solution to an inequality constrained optimization problem and its global convergence is also proved under some conditions.

关键词： Constrained Optimization Problems Augmented Lagrangian Objective Penalty Function Saddle Point Algorithm

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零售价波动销售策略下的报童模型研究

系统工程理论与实践 2020年第10期40卷 2648-2657页

作者：孟志青郑敏超浙江工业大学管理学院杭州310023

价格波动销售策略普遍存在于各种买卖活动中,并导致了需求的不确定性使得零售商更容易发生供应不足或供过于求的现象,因此,价格波动时的订购问题更为重要.本文研究零售价波动且需求不确定的一次性订货问题.以期望损失最小为目标,建立订... 详细信息

价格波动销售策略普遍存在于各种买卖活动中,并导致了需求的不确定性使得零售商更容易发生供应不足或供过于求的现象,因此,价格波动时的订购问题更为重要.本文研究零售价波动且需求不确定的一次性订货问题.以期望损失最小为目标,建立订货模型,通过对价格区间的划分导出了最优订购量的近似表达式.理论上证明了价格区间划分方法的收敛性和解的存在性,并给出了在有限样本下的求解算法.根据实际销售数据进行了数值实验,证实了所提出的模型可以得到近似最优订购量.实验结果表明采用价格波动模型所得到的期望损失小于传统价格确定报童模型所得的期望损失,价格波动均值以及需求方差的变动会引起最优订购量的明显改变.

关键词：价格波动销售策略最优订购量报童模型需求不确定算法

A Penalty Function Algorithm with Objective Parameters and Constraint Penalty Parameter for Multi-Objective Programming

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American Journal of Operations Research 2014年第6期4卷 331-339页

作者： zhiqing meng Rui Shen Min Jiang College of Business and Administration Zhejiang University of Technology Hangzhou China

In this paper, we present an algorithm to solve the inequality constrained multi-objective programming (MP) by using a penalty function with objective parameters and constraint penalty parameter. First, the penalty function with objective parameters and constraint penalty parameter for MP and the corresponding unconstraint penalty optimization problem (UPOP) is defined. Under some conditions, a Pareto efficient solution (or a weakly-efficient solution) to UPOP is proved to be a Pareto efficient solution (or a weakly-efficient solution) to MP. The penalty function is proved to be exact under a stable condition. Then, we design an algorithm to solve MP and prove its convergence. Finally, numerical examples show that the algorithm may help decision makers to find a satisfactory solution to MP.

关键词： Multi-Objective Programming Penalty Function Objective Parameters Constraint Penalty Parameter Pareto Weakly-Efficient Solution

基于级联卷积神经网络的复杂花色布匹瑕疵检测算法

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模式识别与人工智能 2020年第12期33卷 1135-1144页

作者：孟志青邱健数浙江工业大学管理学院杭州310014

当布匹的背景信息复杂多变时,复杂花色布匹的瑕疵定位与分类较为困难.针对这一问题,文中提出基于级联卷积神经网络的复杂花色布匹瑕疵检测算法.首先,使用双路残差的骨干特征提取网络,在缺陷图和模板图上提取并融合特征.然后,设计密度聚... 详细信息

当布匹的背景信息复杂多变时,复杂花色布匹的瑕疵定位与分类较为困难.针对这一问题,文中提出基于级联卷积神经网络的复杂花色布匹瑕疵检测算法.首先,使用双路残差的骨干特征提取网络,在缺陷图和模板图上提取并融合特征.然后,设计密度聚类边框生产器,指导框架中区域候选网络的预检测框设计.最后,通过级联回归方法完成瑕疵的精确定位和分类.采用工业现场采集的布匹图像数据进行训练与预测,结果表明,文中算法的精准率和召回率较高.

关键词：布匹瑕疵检测级联卷积神经网络目标检测瑕疵分类

An Objective Penalty Functions Algorithm for Multiobjective Optimization Problem

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American Journal of Operations Research 2011年第4期1卷 229-235页

作者： zhiqing meng Rui Shen Min Jiang 不详

By using the penalty function method with objective parameters, the paper presents an interactive algorithm to solve the inequality constrained multi-objective programming (MP). The MP is transformed into a single objective optimal problem (SOOP) with inequality constrains;and it is proved that, under some conditions, an optimal solution to SOOP is a Pareto efficient solution to MP. Then, an interactive algorithm of MP is designed accordingly. Numerical examples show that the algorithm can find a satisfactory solution to MP with objective weight value adjusted by decision maker.

关键词： Multiobjective Optimization Problem Objective Penalty Function Pareto Efficient Solution Interactive Algorithm