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遗传算法 22

动态规划 5

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遗传算法在工程爆破参数优化中的应用

许红涛,卢文波

《中国工程科学》 2005年 第7卷 第1期   页码 76-80

摘要：

工程爆破中的参数优化问题是个复杂的非线性规划问题。以矿山爆破参数优化数学模型为例，采用遗传算法实现了爆破参数的优化。结果证实了利用遗传算法进行爆破参数优化的可行性与高效性，为求解该问题提供了一个有效的新途径。

关键词： 工程爆破     采矿     优化     数学模型     非线性规划     遗传算法    

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Prediction of cost and emission from Indian coal-fired power plants with CO

Naushita SHARMA, Udayan SINGH, Siba Sankar MAHAPATRA

《能源前沿（英文）》 2019年 第13卷 第1期   页码 149-162 doi: 10.1007/s11708-017-0482-6

摘要： Coal-fired power plants are one of the most important targets with respect to reduction of CO emissions. The reasons for this are that coal-fired power plants offer localized large point sources (LPS) of CO and that the Indian power sector contributes to roughly half of all-India CO emissions. CO capture and storage (CCS) can be implemented in these power plants for long-term decarbonisation of the Indian economy. In this paper, two artificial intelligence (AI) techniques—adaptive network based fuzzy inference system (ANFIS) and multi gene genetic programming (MGGP) are used to model Indian coal-fired power plants with CO capture. The data set of 75 power plants take the plant size, the capture type, the load and the CO emission as the input and the COE and annual CO emissions as the output. It is found that MGGP is more suited to these applications with an value of more than 99% between the predicted and actual values, as against the ~96% correlation for the ANFIS approach. MGGP also gives the traditionally expected results in sensitivity analysis, which ANFIS fails to give. Several other parameters in the base plant and CO capture unit may be included in similar studies to give a more accurate result. This is because MGGP gives a better perspective toward qualitative data, such as capture type, as compared to ANFIS.

关键词： carbon capture and storage     power plants     artificial intelligence     genetic programming     neuro fuzzy    

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Characterization of the tensile properties of friction stir welded aluminum alloy joints based on axial force, traverse speed, and rotational speed

Biranchi PANDA,A. GARG,Zhang JIAN,Akbar HEIDARZADEH,Liang GAO

《机械工程前沿（英文）》 2016年 第11卷 第3期   页码 289-298 doi: 10.1007/s11465-016-0393-y

摘要：

Friction stir welding (FSW) process has gained attention in recent years because of its advantages over the conventional fusion welding process. These advantages include the absence of heat formation in the affected zone and the absence of large distortion, porosity, oxidation, and cracking. Experimental investigations are necessary to understand the physical behavior that causes the high tensile strength of welded joints of different metals and alloys. Existing literature indicates that tensile properties exhibit strong dependence on the rotational speed, traverse speed, and axial force of the tool that was used. Therefore, this study introduces the experimental procedure for measuring tensile properties, namely, ultimate tensile strength (UTS) and tensile elongation of the welded AA 7020 Al alloy. Experimental findings suggest that a welded part with high UTS can be achieved at a lower heat input compared with the high heat input condition. A numerical approach based on genetic programming is employed to produce the functional relationships between tensile properties and the three inputs (rotational speed, traverse speed, and axial force) of the FSW process. The formulated models were validated based on the experimental data, using the statistical metrics. The effect of the three inputs on the tensile properties was investigated using 2D and 3D analyses. A high UTS was achieved, including a rotational speed of 1050 r/min and traverse speed of 95 mm/min. The results also indicate that 8 kN axial force should be set prior to the FSW process.

关键词： tensile properties     ultimate tensile strength     tensile elongation     friction stir welding     tool rotational speed     genetic programming     welding speed    

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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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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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Machine learning modeling identifies hypertrophic cardiomyopathy subtypes with genetic signature

《医学前沿（英文）》 2023年 第17卷 第4期   页码 768-780 doi: 10.1007/s11684-023-0982-1

摘要： Previous studies have revealed that patients with hypertrophic cardiomyopathy (HCM) exhibit differences in symptom severity and prognosis, indicating potential HCM subtypes among these patients. Here, 793 patients with HCM were recruited at an average follow-up of 32.78 ± 27.58 months to identify potential HCM subtypes by performing consensus clustering on the basis of their echocardiography features. Furthermore, we proposed a systematic method for illustrating the relationship between the phenotype and genotype of each HCM subtype by using machine learning modeling and interactome network detection techniques based on whole-exome sequencing data. Another independent cohort that consisted of 414 patients with HCM was recruited to replicate the findings. Consequently, two subtypes characterized by different clinical outcomes were identified in HCM. Patients with subtype 2 presented asymmetric septal hypertrophy associated with a stable course, while those with subtype 1 displayed left ventricular systolic dysfunction and aggressive progression. Machine learning modeling based on personal whole-exome data identified 46 genes with mutation burden that could accurately predict subtype propensities. Furthermore, the patients in another cohort predicted as subtype 1 by the 46-gene model presented increased left ventricular end-diastolic diameter and reduced left ventricular ejection fraction. By employing echocardiography and genetic screening for the 46 genes, HCM can be classified into two subtypes with distinct clinical outcomes.

关键词： machine learning methods     hypertrophic cardiomyopathy     genetic risk    

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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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Interplay between diet and genetic susceptibility in obesity and related traits

Tiange Wang, Min Xu, Yufang Bi, Guang Ning

《医学前沿（英文）》 2018年 第12卷 第6期   页码 601-607 doi: 10.1007/s11684-018-0648-6

摘要：

The incidence of obesity has been rapidly increasing, and this condition has become a major public health threat. A substantial shift in environmental factors and lifestyle, such as unhealthy diet, is among the major driving forces of the global obesity pandemic. Longitudinal studies and randomized intervention trials have shown that genetic susceptibility to obesity may interact with dietary factors in relation to the body mass index and risk of obesity. This review summarized data from recent longitudinal studies and intervention studies on variations and diets and discussed the challenges and future prospects related to this area and public health implications.

关键词： diet     genetic susceptibility     obesity     interaction    

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Optimal design of steel skeletal structures using the enhanced genetic algorithm methodology

Tugrul TALASLIOGLU

《结构与土木工程前沿（英文）》 2019年 第13卷 第4期   页码 863-889 doi: 10.1007/s11709-019-0523-9

摘要： This study concerns with the design optimization of steel skeletal structures thereby utilizing both a real-life specification provisions and ready steel profiles named hot-rolled I sections. For this purpose, the enhanced genetic algorithm methodology named EGAwMP is utilized as an optimization tool. The evolutionary search mechanism of EGAwMP is constituted on the basis of generational genetic algorithm (GGA). The exploration capacity of EGAwMP is improved in a way of dividing an entire population into sub-populations and using of a radial basis neural network for dynamically adjustment of EGAwMP’s genetic operator parameters. In order to improve the exploitation capability of EGAwMP, the proposed neural network implementation is also utilized for prediction of more accurate design variables associating with a new design strategy, design codes of which are based on the provisions of LRFD_AISC V3 specification. EGAwMP is applied to determine the real-life ready steel profiles for the optimal design of skeletal structures with 105, 200, 444, and 942 members. EGAwMP accomplishes to increase the quality degrees of optimum designations Furthermore, the importance of using the real-life steel profiles and design codes is also demonstrated. Consequently, EGAwMP is suggested as a design optimization tool for the real-life steel skeletal structures.

关键词： design optimization     genetic algorithm     multiple populations     neural network    

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Research progress on genetic improvement of

Chuanping YANG

《农业科学与工程前沿（英文）》 2017年 第4卷 第4期   页码 391-401 doi: 10.15302/J-FASE-2017183

摘要： Suk. is one of the most widely distributed species of , the fourth most valuable timber species in north-eastern China and also a common tree species for landscaping. Over the past 30 years, effective progress has been made in genetic improvement and molecular breeding of . There has been extensive research on breeding techniques, including the collection and conservation of germplasm resources, provenance trials, intensive breeding techniques, crossbreeding and asexual propagation techniques, ploidy breeding and mutation breeding technology, genome sequencing, gene cloning, transgenic and molecular mechanisms of wood formation. A germplasm resource collection has been established by collecting different provenances, and full-sib and half-sib families. In addition, the geographic variation patterns of provenances have been revealed, and the provenance division and superior provenance selections made. flowering and seeding have been improved through intensive breeding techniques. Interspecific hybridization, intraspecific hybridization and parallel crosses were made using fine parents, and intensive seed orchards have been established. Systems of asexual propagation, including cuttings, grafting and tissue culture have been established. A tetraploid was successfully constructed and a triploid seed orchard established. The growth, wood property and resistance genes of have been cloned. An efficient transgenic system mediated by was established, and genes encoding insect resistance, drought resistance and salt tolerance, lignin synthesis, flowering, hormone transport and balance obtained. molecular markers were developed and the high density genetic map constructed. All this research has provided a model and data for the foundation of forest genetic improvement and applied research.

关键词： Betula platyphylla     genetic improvement     molecular breeding     seed orchard    

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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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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    

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标题 作者 时间 类型 操作

遗传算法在工程爆破参数优化中的应用

许红涛,卢文波

期刊论文

Prediction of cost and emission from Indian coal-fired power plants with CO

Naushita SHARMA, Udayan SINGH, Siba Sankar MAHAPATRA

期刊论文

Characterization of the tensile properties of friction stir welded aluminum alloy joints based on axial force, traverse speed, and rotational speed

Biranchi PANDA,A. GARG,Zhang JIAN,Akbar HEIDARZADEH,Liang GAO

期刊论文

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

Jiang LI, Guodong LIU, Shuo ZHANG

期刊论文

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

Shengwen ZHANG, Guicheng WANG, Liang ZHANG, Xifeng FANG

期刊论文

Technology and system of constraint programming for industry production scheduling

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

期刊论文

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

期刊论文

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

期刊论文

Machine learning modeling identifies hypertrophic cardiomyopathy subtypes with genetic signature

期刊论文

动态规划的正向递推方法

张钊,裴燕玲,张仁宝

期刊论文

Interplay between diet and genetic susceptibility in obesity and related traits

Tiange Wang, Min Xu, Yufang Bi, Guang Ning

期刊论文

Optimal design of steel skeletal structures using the enhanced genetic algorithm methodology

Tugrul TALASLIOGLU

期刊论文

Research progress on genetic improvement of

Chuanping YANG

期刊论文

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

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

期刊论文

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

Mo LI,Ping GUO,Liudong ZHANG,Chenglong ZHANG

期刊论文