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Smoothing ramp events in wind farm based on dynamic programming in energy internet

Jiang LI, Guodong LIU, Shuo ZHANG

《能源前沿（英文）》 2018年第12卷第4期页码 550-559 doi: 10.1007/s11708-018-0593-8

摘要：

The concept of energy internet has been gradually accepted, which can optimize the consumption of fossil energy and renewable energy resources. When wind power is integrated into the main grid, ramp events caused by stochastic wind power fluctuation may threaten the security of power systems. This paper proposes a dynamic programming method in smoothing ramp events. First, the energy internet model of wind power, pumped storage power station, and gas power station is established. Then, the optimization problem in the energy internet is transformed into a multi-stage dynamic programming problem, and the dynamic programming method proposed is applied to solve the optimization problem. Finally, the evaluation functions are introduced to evaluate pollutant emissions. The results show that the dynamic programming method proposed is effective for smoothing wind power and reducing ramp events in energy internet.

关键词： energy internet wind power ramp events dynamic programming

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Unit commitment using dynamic programming–an exhaustive working of both classical and stochastic approach

Balasubramaniyan SARAVANAN, Surbhi SIKRI, K. S. SWARUP, D. P. KOTHARI

《能源前沿（英文）》 2013年第7卷第3期页码 333-341 doi: 10.1007/s11708-013-0259-5

摘要： In the present electricity market, where renewable energy power plants have been included in the power systems, there is a lot of unpredictability in the demand and generation. There are many conventional and evolutionary programming techniques used for solving the unit commitment (UC) problem. Dynamic programming (DP) is a conventional algorithm used to solve the deterministic problem. In this paper DP is used to solve the stochastic model of UC problem. The stochastic modeling for load and generation side has been formulated using an approximate state decision approach. The programs were developed in a MATLAB environment and were extensively tested for a four-unit eight-hour system. The results obtained from these techniques were validated with the available literature and outcome was good. The commitment is in such a way that the total cost is minimal. The novelty of this paper lies in the fact that DP is used for solving the stochastic UC problem.

关键词： unit commitment (UC) deterministic stochastic dynamic programming (DP) optimization state diagram

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动态规划的正向递推方法

张钊,裴燕玲,张仁宝

《中国工程科学》 2005年第7卷第2期页码 62-65

摘要：

动态规划求最优解是一个反向递推的求解过程，以实例为依据，用正向递推的方法求解动态规划的最优值，并推出动态规划的基本方程和密尔顿-雅可比方程，是对动态规划求最优解方法的探讨。利用动态规划的正向递推方法，在应用中可以大大减少计算量，扩大了它的应用范围。

关键词：动态规划多级决策泛函最优值

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多阶段系统多目标优化的模糊优选动态规划方法及应用

熊德琪,殷佩海

《中国工程科学》 2000年第2卷第9期页码 65-69

摘要：

在模糊权距离和隶属度概念的基础上，根据多阶段系统前后阶段联系特点，将模糊优选理论与动态规划原理有机地结合起来，提出能够有效地寻求多阶段多目标优化问题的最优均衡策略的模糊优选动态规划技术，为求解多目标多阶段系统的优化决策问题提供了新路。最后例举一个多级反应器系统最优控制的应用算例。

关键词：多阶段多目标优化模糊优选动态规划隶属度

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动态设定型板形板厚自动控制系统

张进之,段春华

《中国工程科学》 2000年第2卷第6期页码 67-72

摘要：

文章介绍了应用解析板形方程推出板形最佳轧制规程和板形板厚协调控制新方法。该方法的主要特点：系统中采用了静、动态负荷分配，动态设定厚度自动控制系统（DAGC）完成了板形板厚的闭环控制，在算法中采用了贝尔曼动态规划。新方法将会改变目前轧机设计和控制思想：设计合理刚度，强调调度计划、配置轧辊凸度和优化轧制规程等方面的作用，实现信息控制。

关键词：动态负荷分配板形最佳规程动态规划动态设定

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Review on ranking and selection: A new perspective

L. Jeff HONG, Weiwei FAN, Jun LUO

《工程管理前沿（英文）》 2021年第8卷第3期页码 321-343 doi: 10.1007/s42524-021-0152-6

摘要： In this paper, we briefly review the development of ranking and selection (R&S) in the past 70 years, especially the theoretical achievements and practical applications in the past 20 years. Different from the frequentist and Bayesian classifications adopted by Kim and Nelson (2006b) and Chick (2006) in their review articles, we categorize existing R&S procedures into fixed-precision and fixed-budget procedures, as in Hunter and Nelson (2017). We show that these two categories of procedures essentially differ in the underlying methodological formulations, i.e., they are built on hypothesis testing and dynamic programming, respectively. In light of this variation, we review in detail some well-known procedures in the literature and show how they fit into these two formulations. In addition, we discuss the use of R&S procedures in solving various practical problems and propose what we think are the important research questions in the field.

关键词： ranking and selection hypothesis testing dynamic programming simulation

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土石方动态调配模型与可视化研究

胡程顺,钟登华,张静,洪文,李明超

《中国工程科学》 2003年第5卷第12期页码 73-79

摘要：

土石方调配是土石坝或堆石坝施工中的一个核心问题，其合理与否对降低工程造价和保证工程的顺利进行具有重要的经济、技术价值。根据其受时间-空间影响与约束的特点，文章在总结现有研究成果的基础上，采用系统分析的手段，提出了一种将动态问题静态化的方法，并利用线性规划大M单纯形法对问题进行求解。在数学模型上，深入而细致地考虑了实际施工中的一些人为约束因素，增强了模型的通用性与灵活性；借助于GIS技术的强大空间信息处理功能，将土石方调配成果以三维动画的形式显示出来，以达到形象直观的目的；在程序实现上，采用强大的程序设计语言工具VC++开发出了界面友好、操作简单、适用性强的软件。最后，以其在某大型土石坝工程土石方调配项目中的成功应用，验证了此项研究工作的合理性与优越性。

关键词：土石坝施工土石方调配动态调配线性规划可视化

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模拟系统的混合测试优化方法

梅文娟,刘震,李欧行,苏元章,梅渝松,龙泳吉

《信息与电子工程前沿（英文）》 2023年第24卷第9期页码 1302-1315 doi: 10.1631/FITEE.2200512

摘要：由于模拟系统在现代电子设备中起着至关重要作用，模拟系统测试优化已引起学术界和工业界广泛关注。尽管现有方法能实现测试策略的自动生成，但是由于复杂结构和多变的运行环境的影响，模拟系统难以有效生成诊断策略。因此，受到系统拓扑结构和冗余信息的影响，生成的测试策略在实际应用中缺乏可行性。此外，现有方法假设相互独立的测试项需要串行执行，增加了测试时间消耗。为解决上述问题，本文提出用于生成混合测试策略的启发式规划方法。实验证明，相较现有方法生成的策略，启发式规划方法和卷展启发式规划方法生成的策略具有更少层数和更低测试代价。通过对混合“或”节点的自适应优化和测试代价更新，该方法能提供更可行的优化方案并降低测试产生的代价。因此，本文提出的方法具有更高的优化效率。

关键词：故障诊断启发式搜索动态规划测试优化

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基于车联网的信号灯协同控制 Article

李婉, 班学钢

《工程（英文）》 2020年第6卷第12期页码 1463-1472 doi: 10.1016/j.eng.2020.10.009

摘要：

本文提出了一个基于车联网（CV）环境的交通主干道信号灯协同控制的模型及其求解方法。首先，我们将信号优化与协同控制问题归结为一个混合整数非线性规划（MINLP）。通过考虑单个车辆轨迹的最小油耗和行程时间求解最优相位持续时间和相位差。由于模型的复杂性，我们将问题分解为两个层次：使用动态规划（DP）优化相位持续时间的交叉路口层，以及用于优化所有交叉路口相位差的干道交通层。同时，我们开发了一种基于预测的方法以求解上述双层优化模型。在各种场景下，我们利用交通模拟对模型进行了测试。与传统的感应信号灯协同控制相比，求解MINLP和双层优化模型生成的信号时序规划可以合理地提升交通信号灯控制性能和路网的服务水平。在高密度的交通流量的环境中并考虑不同车辆类型时，与感应信号灯相比，上述双层优化模型的求解法使路网总成本降低了3.8%，MINLP的应用使系统总成本降低了5.9%。这也表明对于交通密度相对较高的干道交通来说，本文提出的协同控制方案效果显著。而仿真结果也表明对于同时拥有主要道路和次要道路的交叉路口而言，面向主要道路进行的协同控制对次要道路上的车辆几乎没有影响。

关键词：车联网交通信号灯协同控制动态规划双层优化混合整数非线性规划

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CNC programming system for complex components based on KBE within integrated environment of CAD/CAPP/

Shengwen ZHANG, Guicheng WANG, Liang ZHANG, Xifeng FANG

《机械工程前沿（英文）》 2009年第4卷第1期页码 97-102 doi: 10.1007/s11465-009-0007-z

摘要： To promote the research and development of modern digital and intelligent manufacturing technology and overcome shortcomings of computerized numerical control(CNC) programming for complex components, an innovative idea has been proposed to introduce knowledge based engineering (KBE) into the field of CNC programming within the integrated environment of CAD/CAPP/CAM. This paper constructs the architecture of CNC programming based on KBE within CAD/CAPP/CAM and explores the key technology of applying KBE to CNC programming — knowledge representation, knowledge acquisition, knowledge reasoning, and generalized knowledge base system of CNC programming. The integration of the CAD/CAM system and the CAPP system of enterprises has been achieved by taking the powerful CAD/CAM system of UG NX as a platform. The prototype system of CNC programming for complex components based on KBE within CAD/CAPP/CAM has been developed by means of UG/Open,VC++6.0, and SQL Sever 2000. Finally, a frame example, one of the complex components of a marine diesel, is presented, and the academic production and the intelligence of the system are verified.

关键词： NC programming CAD/CAPP/CAM KBE

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Technology and system of constraint programming for industry production scheduling

Yarong CHEN, Zailin GUAN, Yunfang PENG, Xinyu SHAO, Muhammad HASSEB

《机械工程前沿（英文）》 2010年第5卷第4期页码 455-464 doi: 10.1007/s11465-010-0106-x

摘要： The use of techniques and system of constraint programming enables the implementation of precise, flexible, efficient, and extensible scheduling systems. It has been identified as a strategic direction and dominant form for the application into planning and scheduling of industrial production. This paper systematically introduces the constraint modeling and solving technology for production scheduling problems, including various real-world industrial applications based on the Chip system of Cosytec Company. We trend of some concrete technology, such as modeling, search, constraint propagation, consistency, and optimization of constraint programming for scheduling problems. As a result of the application analysis, a generic application framework for real-life scheduling based on commercial constraint propagation (CP) systems is proposed.

关键词： constraint programming production scheduling constraint propagation search consistency optimization

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Two-stage stochastic programming with robust constraints for the logistics network post-disruption response

《工程管理前沿（英文）》页码 67-81 doi: 10.1007/s42524-022-0240-2

摘要： Logistics networks (LNs) are essential for the transportation and distribution of goods or services from suppliers to consumers. However, LNs with complex structures are more vulnerable to disruptions due to natural disasters and accidents. To address the LN post-disruption response strategy optimization problem, this study proposes a novel two-stage stochastic programming model with robust delivery time constraints. The proposed model jointly optimizes the new-line-opening and rerouting decisions in the face of uncertain transport demands and transportation times. To enhance the robustness of the response strategy obtained, the conditional value at risk (CVaR) criterion is utilized to reduce the operational risk, and robust constraints based on the scenario-based uncertainty sets are proposed to guarantee the delivery time requirement. An equivalent tractable mixed-integer linear programming reformulation is further derived by linearizing the CVaR objective function and dualizing the infinite number of robust constraints into finite ones. A case study based on the practical operations of the JD LN is conducted to validate the practical significance of the proposed model. A comparison with the rerouting strategy and two benchmark models demonstrates the superiority of the proposed model in terms of operational cost, delivery time, and loading rate.

关键词： logistics network design post-disruption response strategy two-stage stochastic programming conditional value at risk robust constraint

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Cutting CO emissions through demand side regulation: Implications from multi-regional input–output linear programming

《工程管理前沿（英文）》页码 452-461 doi: 10.1007/s42524-022-0209-1

摘要： This study combines multi-regional input–output (MRIO) model with linear programming (LP) model to explore economic structure adjustment strategies for the reduction of carbon dioxide (CO₂) emissions. A particular feature of this study is the identification of the optimal regulation sequence of final products in various regions to reduce CO₂ emissions with the minimum loss in gross domestic product (GDP). By using China’s MRIO tables 2017 with 28 regions and 42 economic sectors, results show that reduction in final demand leads to simultaneous reductions in GDP and CO₂ emissions. Nevertheless, certain demand side regulation strategy can be adopted to lower CO₂ emissions at the smallest loss of economic growth. Several key final products, such as metallurgy, nonmetal, metal, and chemical products, should first be regulated to reduce CO₂ emissions at the minimum loss in GDP. Most of these key products concentrate in the coastal developed regions in China. The proposed MRIO–LP model considers the inter-relationship among various sectors and regions, and can aid policy makers in designing effective policy for industrial structure adjustment at the regional level to achieve the national environmental and economic targets.

关键词： CO₂ emissions demand side regulation multi-regional input–output model linear programming model

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Uncertain and multi-objective programming models for crop planting structure optimization

Mo LI,Ping GUO,Liudong ZHANG,Chenglong ZHANG

《农业科学与工程前沿（英文）》 2016年第3卷第1期页码 34-45 doi: 10.15302/J-FASE-2016084

摘要： Crop planting structure optimization is a significant way to increase agricultural economic benefits and improve agricultural water management. The complexities of fluctuating stream conditions, varying economic profits, and uncertainties and errors in estimated modeling parameters, as well as the complexities among economic, social, natural resources and environmental aspects, have led to the necessity of developing optimization models for crop planting structure which consider uncertainty and multi-objectives elements. In this study, three single-objective programming models under uncertainty for crop planting structure optimization were developed, including an interval linear programming model, an inexact fuzzy chance-constrained programming (IFCCP) model and an inexact fuzzy linear programming (IFLP) model. Each of the three models takes grayness into account. Moreover, the IFCCP model considers fuzzy uncertainty of parameters/variables and stochastic characteristics of constraints, while the IFLP model takes into account the fuzzy uncertainty of both constraints and objective functions. To satisfy the sustainable development of crop planting structure planning, a fuzzy-optimization-theory-based fuzzy linear multi-objective programming model was developed, which is capable of reflecting both uncertainties and multi-objective. In addition, a multi-objective fractional programming model for crop structure optimization was also developed to quantitatively express the multi-objective in one optimization model with the numerator representing maximum economic benefits and the denominator representing minimum crop planting area allocation. These models better reflect actual situations, considering the uncertainties and multi-objectives of crop planting structure optimization systems. The five models developed were then applied to a real case study in Minqin County, north-west China. The advantages, the applicable conditions and the solution methods of each model are expounded. Detailed analysis of results of each model and their comparisons demonstrate the feasibility and applicability of the models developed, therefore decision makers can choose the appropriate model when making decisions.

关键词： crop planting structure optimization model uncertainty multi-objective