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电力施工企业物资采购管理优化探讨
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作者 李坤 《中文科技期刊数据库(全文版)经济管理》 2019年第3期142-142,144,共2页
当前随着国内电厂机组的不断建设以及国家环保政策的要求,国内火电机组已趋于饱和,传统电建行业在不断转行,同时国际市场竞争日趋激烈,电力施工企业要想在不断变化的市场环境中生存,就必须要重视对工程建设的管理,物资采购作为工程建设... 当前随着国内电厂机组的不断建设以及国家环保政策的要求,国内火电机组已趋于饱和,传统电建行业在不断转行,同时国际市场竞争日趋激烈,电力施工企业要想在不断变化的市场环境中生存,就必须要重视对工程建设的管理,物资采购作为工程建设的重要组成部分,对电力施工企业工程施工方案的制定有着重要影响,物资采购管理工作在实施过程中存在着一定的复杂性,电力施工企业必须要控制好物资采购各环节的变量,加强物资采购管理,为电建项目建设,尤其是经济效益的提升进行更好的服务。本文首先分析了国有电力企业物资采购管理的意义,接着提出了国有电力企业物资采购管理遇到的问题,包括管理制度不严谨、物资采购监管制度不完善、传统物资采购模式难以满足企业发展需求等,针对问题提出了相应的解决对策。 展开更多
关键词 电力施工企业 物资采购管理 优化模式分析
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Accelerated Matrix Recovery via Random Projection Based on Inexact Augmented Lagrange Multiplier Method 被引量:4
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作者 王萍 张楚涵 +1 位作者 蔡思佳 李林昊 《Transactions of Tianjin University》 EI CAS 2013年第4期293-299,共7页
In this paper, a unified matrix recovery model was proposed for diverse corrupted matrices. Resulting from the separable structure of the proposed model, the convex optimization problem can be solved efficiently by ad... In this paper, a unified matrix recovery model was proposed for diverse corrupted matrices. Resulting from the separable structure of the proposed model, the convex optimization problem can be solved efficiently by adopting an inexact augmented Lagrange multiplier (IALM) method. Additionally, a random projection accelerated technique (IALM+RP) was adopted to improve the success rate. From the preliminary numerical comparisons, it was indicated that for the standard robust principal component analysis (PCA) problem, IALM+RP was at least two to six times faster than IALM with an insignificant reduction in accuracy; and for the outlier pursuit (OP) problem, IALM+RP was at least 6.9 times faster, even up to 8.3 times faster when the size of matrix was 2 000×2 000. 展开更多
关键词 matrix recovery random projection robust principal component analysis matrix completion outlier pursuit inexact augmented Lagrange multiplier method
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An optimal incentive contract to venture capitalist
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作者 LIANG Peng 《Journal of Modern Accounting and Auditing》 2008年第4期23-31,共9页
This paper aims to study the principal-agent relationship between investors and venture capitalists (VCs), makes research on the moral hazard issues under this relationship, and how to design an effective incentive ... This paper aims to study the principal-agent relationship between investors and venture capitalists (VCs), makes research on the moral hazard issues under this relationship, and how to design an effective incentive mechanism to avoid it. By constructing a new incentive model, this paper provides the reference for investors to establish a reasonable payment contract. The designed incentive contract is a kind of dominant consecutive payment mode, which plays a strong incentive role to the VCs, in addition, it also requires the VCs to invest certain capital to the project, which can effectively prevent the slapdash action of VCs, and reduce the agent cost of investors. 展开更多
关键词 INVESTOR venture capitalists principal-agent relationship
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Product Family Hierarchical Associated Design and Its Hierarchical Optimization
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作者 Gang Du Jianzhong Wang 《Journal of Systems Science and Information》 2009年第3期245-252,共8页
After reviewing the literature and methodology-related issues within the field of product family design, a deficiency in the current design and development of product family is pointed out. The concept of hierarchical... After reviewing the literature and methodology-related issues within the field of product family design, a deficiency in the current design and development of product family is pointed out. The concept of hierarchical associated design is proposed in this article, according to the deficiency~ and the methods and models for realizing the notion above are described. A two-dimensional analytical model is constructed based on the composing levels and developing processes of product family. The optimization models to hierarchical associated design problems are grouped into two categories: overall-local and key-subordinate. The algorithms of the models are discussed in this paper 展开更多
关键词 product family design hierarchical optimization the two-dimensional framework
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