A deep reinforcement learning method for multi-stage equipment development planning in uncertain environments

Equipment development planning(EDP)is usually a long-term process often performed in an environment with high uncertainty.The traditional multi-stage dynamic programming cannot cope with this kind of uncertainty with unpredictable situations.To deal with this problem,a multi-stage EDP model based on a deep reinforcement learning(DRL)algorithm is proposed to respond quickly to any environmental changes within a reasonable range.Firstly,the basic problem of multi-stage EDP is described,and a mathematical planning model is constructed.Then,for two kinds of uncertainties(future capabi lity requirements and the amount of investment in each stage),a corresponding DRL framework is designed to define the environment,state,action,and reward function for multi-stage EDP.After that,the dueling deep Q-network(Dueling DQN)algorithm is used to solve the multi-stage EDP to generate an approximately optimal multi-stage equipment development scheme.Finally,a case of ten kinds of equipment in 100 possible environments,which are randomly generated,is used to test the feasibility and effectiveness of the proposed models.The results show that the algorithm can respond instantaneously in any state of the multistage EDP environment and unlike traditional algorithms,the algorithm does not need to re-optimize the problem for any change in the environment.In addition,the algorithm can flexibly adjust at subsequent planning stages in the event of a change to the equipment capability requirements to adapt to the new requirements.

National Planning,Investment & Structural Reform

Along with the further development of its economic structural reform, China’s planning, investment structure reform has made significant headway. A reporter interviewed Gui Shiyong, vice minister of the State Planning Commission on the current situation and orientation of the nation’s planning and investment structural reform.

MAHIS-based analysis and design of financial investment planning system

In financial investment planning,a large number of components that interact in varying and complexways are involved.This leads to complex behavior that is difficult to understand,predict and manage.Asingle intelligent technique can not solve the complicated and elaborate investment planning problems.Itis necessary to study those problems synthetically by combining the multiple intelligent techniques.Weemployed fussy algorithms,genetic algorithms,etc.to solve complicated financial portfolio managementin this paper.We analyse and design an agent-based hybrid intelligent system by following the methodolo-gy for constructing agent-based hybrid intelligent system(MAHIS).The system starts with the financialrisk tolerance evaluation based on fussy algorithms.Asset allocation,portfolio selections,interest predic-tions,and ordered weighted averaging can be conducted by using hybrid intelligent techniques.The plan-ning agent in the system can easily access all the intelligent processing agents,including the agents of fi-nancial risk tolerance assessment,asset allocation,portfolio selection,interest prediction,and decisionaggregation.Overall system robustness is facilitated.

Westinghouse Electric Corp.plans long-term investment in China

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SHAANXI'S KEY PROJECTS FOR FIXED ASSETS INVESTMENT DURING THE NINTH FIVE-YEAR PLAN

During the Eighth Five-Year Planperiod, Shaanxi Province intensifiedthe restructuring of investment andmacro-control in fixed assets investment byimplementing the policy of "limiting totalamount, readjusting structure, rectifying orderand improving efficiency". The wholeprovince realized RMB 110 billion in fixedassets investment, (including RMB 86.5 billionby state-owned units, RMB 14.23 billionthrough loans from the construction bank,making up 16.5 percent), RMB 67 billionmore than in the Seventh Five-Year Planperiod, with an annual increase of 26.5 percent.Thanks to the support, a group of medium-to-large and key projects have been put

China Stresses Private,Quality Investment in Northeast Revival Plan

A multibillion-dollar plan to boost Northeast China’s flagging economy will not just use state funds,but also use private capital to invest.The three-year revival plan is not wholly funded by the state and is not a government'blood transfusion',an official with

Mr.Zhangshou Interviewed the China Area Manager of “Asia Investment Plan”of Europe Union

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Optimal investment for the defined-contribution pension with stochastic salary under a CEV model

In this paper, we study the optimal investment strategy of defined-contribution pension with the stochastic salary. The investor is allowed to invest in a risk-free asset and a risky asset whose price process follows a constant elasticity of variance model. The stochastic salary follows a stochastic differential equation, whose instantaneous volatility changes with the risky asset price all the time. The HJB equation associated with the optimal investment problem is established, and the explicit solution of the corresponding optimization problem for the CARA utility function is obtained by applying power transform and variable change technique. Finally, we present a numerical analysis.

Scenario-based modeling and solving research on robust weapon project planning problems

Weapon project planning(WPP) plays a critical role in the process of national defense development and establishment of the future national defense force. WPP faces the backgrounds of various uncertainties, intense inter-influence of weapon systems and involves modelling, assessment, and optimization procedures.The contents of this paper are mainly divided into three parts: first,the WPP processes are analyzed, and related elements are formulated to transform the qualitative problem to mathematics form;second, the value evaluation model of WPP solutions is proposed based on two criteria of total capability gap and total capability dispersion; third, two robustness optimization models are constructed based on the absolute robustness criterion and the robustness deviation criterion to support the robustness optimization process under multi-scenario. Finally, a case is studied to examine the feasibility and effectiveness of the proposed models and approaches.

Strategic Planning for Avoidance of Catastrophic Flood Consequences

The present study is to deal with the strategic planning in avoidance of all catastrophic consequences of major flood in West Attica region in 2017 and is divided into three main sections.The first one comprises the study of the internal and external environment of the Regional Unit of West Attica with analysis of resources,procedures,culture that governs the internal environment,external bodies and mapping through PESTEL(Political,Economic,Socio-Cultural and Technological)analysis as components of the external environment.The second section comprises the vision and mission of this strategic plan and specializes in reporting and analyzing the strategic objectives as well as the actions that characterize them in order to complete the mission that has been set and to achieve the vision that has been planned.The last section focuses on the feasibility of the above proposals formulated in the midst of actions and strategic objectives with the help of SWOT(Strength,Weakness,Opportunity,and Threat)analysis and concludes with a proposal for the implementation of strategic planning with the implementation of the Integrated Spatial Investment tool.

CEV模型下目标收益型养老金的最优投资和支付策略

该文研究了目标收益计划下养老金的最优投资策略和支付策略.养老金的支付取决于计划的财务状况,且风险由不同代人分担.养老基金可以投资于无风险资产和风险资产,其中风险资产价格由几何布朗运动模型推广为常方差弹性(CEV)模型来驱动.以最小化收益风险和福利风险的组合为目标,利用动态规划原理和HJB方程,推导出了最优投资策略和最优福利调整的闭型解.最后,数值实例分析了模型参数对控制问题的影响.

基于网源协同多阶段投资规划的配电网过网费机制设计

针对分布式电源就地消纳会造成电网企业输配电成本流失,且现行输配电价制定机制尚不能真实反映“余电上网”模式下分布式电源对配电网的实际使用情况,提出一种基于网源协同多阶段投资规划的配电网过网费机制设计。首先,根据负荷增长情况,以投资年份、投资容量为决策变量,将分布式电源规划周期分为若干阶段,在此基础上利用所提过网费模型分别求出各阶段对应的过网费。其中,源网协同多阶段规划模型的建立以分布式电源投资主体效益最大及配电网网损和电压波动最小为目标,过网费计算模型则依据分布式发电市场化交易的输配电资产占用情况、电压等级和电气距离等关键影响要素,构建了含基础费用、阻塞附加费用和交叉补贴费用的分布式电源过网费。仿真结果表明,所提出的与分布式电源投资规划相结合的过网费机制能够保证投资主体的效益和配电网的资产回收,并能在一定程度上提高分布式电源的渗透率和消纳率。

美欧印全球基建计划对一带一路的影响及应对

在“一带一路”建设深入推进和效应显现之际,美欧印等主要经济体连续发布全球性基础设施投资建设计划,标志着美西方对“一带一路”倡议的战略围堵进入新阶段,使共建“一带一路”面临更多外部风险及现实挑战。要深刻认识共建“一带一路”的独特战略价值,继续坚定不移推动共建“一带一路”高质量发展;分类施策,突破美欧印全球基建计划对我的“合围”;巩固共建“一带一路”建设十年形成的基本盘;多维度推动数字丝绸之路、绿色丝绸之路、健康丝绸之路建设;加快“一带一路”规则标准体系建设;全面加强“一带一路”话语体系建设,推进共建“一带一路”更加行稳致远。

经济刺激计划对中国企业出口产品质量的影响研究

利用2003—2013年中国海关数据库、中国工业企业数据库与中国城市统计年鉴的匹配数据,以中国实施“四万亿”经济刺激计划为准自然实验,实证探究企业出口产品质量受经济刺激计划的影响及其影响机制。研究结果表明,经济刺激计划通过提高研发投入与缓解融资约束显著提升企业出口产品质量;因企业性质和贸易方式不同,经济刺激计划对民营、外资企业,从事一般贸易方式的企业和东西部地区企业出口产品质量提升作用更为显著。

互联网金融背景下工薪家庭理财现状及优化——以河北省为例

当前国内有很大一部分的家庭都迈入了小康的门槛,主要由工薪阶层构成。随着居民人均收入的不断上涨,居民的家庭财富也得到了积累,因此越来越多的工薪家庭理财意识觉醒。但有些理财产品具有高风险性,并且他们没有操作经验,很多家庭对理财望而却步,仅仅是选择把钱存入银行。根本原因在于我国居民理财观念形成较晚,理财市场也刚起步不久,居民在进行家庭理财活动的时候还会遇到许许多多的问题。本文以河北省为例,从家庭理财的现状和可能会出现的相关问题入手,剖析现阶段我国居民在家庭理财的过程中容易出现的问题,针对工薪阶层家庭提出合理的理财规划方案,以期帮助他们实现理财目标。

美国国家地震减灾计划近况及新战略规划

美国国家地震减灾计划(NEHRP)是美国联邦政府层面地震减灾的主要协调计划。美国国会以有计划的重新授权形式不定期开展调整。分别在1990年、1997年、2000年和2004年以重新授权的方式对NEHRP工作重点和监督管理做了调整,实际上2004年重新授权法案到2009年已经到期,虽然美国国会每年会继续提供资金,但再次授权一直拖到2018年。在2018年的调整中,NEHRP做出重大方向性调整,以突出地震预警和地震韧性建设。2023年5月,NEHRP在其网站发布《NEHRP 2022—2029财年战略规划》,落实2018年再授权法案的调整要求,梳理整合既有目标及任务,制定了4个集成目标、18项支持任务,确定了8个重点投入领域。最新的法案调整和战略规划对美国下一阶段地震减灾工作有重要影响,对我国相关工作也有较强的参考借鉴意义。