As a basic chemical raw material, olefins play a very important role in optimizing product structure and promoting economic development. In recent years, the olefin industry has faced unfavorable external environmental challenges such as low oil prices and the spread of the epidemic, and the uncertainty of industry development has greatly increased. Due to the huge demand, technological innovation in olefin production has become a top priority. Ethanol, which is the feedstock for C4 olefins, has an impact on the selectivity and yield of C4 olefins under different catalyst combinations and temperatures. Therefore, the study of ethanol-coupled preparation of C4 olefins under different conditios is conducive to improving the synthesis efficiency of C4 olefins and providing decision-making suggestions for the optimization and nconfiguration of chemicals. In this paper, 120 sets of experimental data are analyzed and processed, which provides a universal calculation step and solution for the parameter selection of ethanol-coupled to prepare C4 olefins under specific conditions. First, the by-product relationship was determined by cluster analysis in order to analyze the factors affecting ethanol utilization and C4 yield. Then, using multiple linear regression and partial least squares regression, the quantitative relationship between the variables was found, and the yield of C4 olefins at a temperature of 400 degrees, catalyst quality of 200 mg Co/SiO2-200 mg HAP, Co support of 1.1 Wt%, Co/SiO2 concentration of 1.06 wt%, and C4 olefin yield of 1.15 ml/min of ethanol concentration reached a maximum value of 77.21%. Finally, after error analysis and validity test, it is concluded that it is suitable for chemical reactions in most industrial production and can be used for efficient extraction of the target product in actual production. In the future, it will be optimized in a larger amount of experimental data, further optimized in combination with deep learning, to improve accuracy and accuracy.
{"title":"The Study on the Optimization Model for Producing Olefin by Coupling Reaction of Ethanol Based on Clustering Analysis and Multiple Regression","authors":"Xingzou Liu, Siyuan Shang, Xinyu Zhao, Liguo Fang","doi":"10.1145/3547578.3547580","DOIUrl":"https://doi.org/10.1145/3547578.3547580","url":null,"abstract":"As a basic chemical raw material, olefins play a very important role in optimizing product structure and promoting economic development. In recent years, the olefin industry has faced unfavorable external environmental challenges such as low oil prices and the spread of the epidemic, and the uncertainty of industry development has greatly increased. Due to the huge demand, technological innovation in olefin production has become a top priority. Ethanol, which is the feedstock for C4 olefins, has an impact on the selectivity and yield of C4 olefins under different catalyst combinations and temperatures. Therefore, the study of ethanol-coupled preparation of C4 olefins under different conditios is conducive to improving the synthesis efficiency of C4 olefins and providing decision-making suggestions for the optimization and nconfiguration of chemicals. In this paper, 120 sets of experimental data are analyzed and processed, which provides a universal calculation step and solution for the parameter selection of ethanol-coupled to prepare C4 olefins under specific conditions. First, the by-product relationship was determined by cluster analysis in order to analyze the factors affecting ethanol utilization and C4 yield. Then, using multiple linear regression and partial least squares regression, the quantitative relationship between the variables was found, and the yield of C4 olefins at a temperature of 400 degrees, catalyst quality of 200 mg Co/SiO2-200 mg HAP, Co support of 1.1 Wt%, Co/SiO2 concentration of 1.06 wt%, and C4 olefin yield of 1.15 ml/min of ethanol concentration reached a maximum value of 77.21%. Finally, after error analysis and validity test, it is concluded that it is suitable for chemical reactions in most industrial production and can be used for efficient extraction of the target product in actual production. In the future, it will be optimized in a larger amount of experimental data, further optimized in combination with deep learning, to improve accuracy and accuracy.","PeriodicalId":381600,"journal":{"name":"Proceedings of the 14th International Conference on Computer Modeling and Simulation","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133926041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Smoothness and rapidity are two important performance indexes for crane lifting path planning. Traditionally, cranes are modeled as multi-freedom robots and use robot path planning algorithms to plan path in continuous space. However, the paths planned by these methods are not smooth enough to operate. In addition, presently, most of proposed lifting path planning algorithms focus on static environments, requiring accurate environmental information to build maps, which is too computation expensive to meet the requirement of real-time path planning. In this paper, we propose a deep reinforcement learning-based lifting path planning algorithm for hybrid action spaces. The network structure is developed based on TD3. A new reward function is designed and hindsight experience replay is used to solve the reward sparsity problem in long distance path planning. The planning path is smooth and can achieve real-time path planning in unknown environments. The result of simulation experiments demonstrates the effectiveness of the proposed approach.
{"title":"A Real-time Smooth Lifting Path Planning for Tower Crane Based on TD3 with Discrete-Continuous Hybrid Action Space","authors":"Zhiyuan Yin, Kai Wang, Xin Ma","doi":"10.1145/3547578.3547592","DOIUrl":"https://doi.org/10.1145/3547578.3547592","url":null,"abstract":"Smoothness and rapidity are two important performance indexes for crane lifting path planning. Traditionally, cranes are modeled as multi-freedom robots and use robot path planning algorithms to plan path in continuous space. However, the paths planned by these methods are not smooth enough to operate. In addition, presently, most of proposed lifting path planning algorithms focus on static environments, requiring accurate environmental information to build maps, which is too computation expensive to meet the requirement of real-time path planning. In this paper, we propose a deep reinforcement learning-based lifting path planning algorithm for hybrid action spaces. The network structure is developed based on TD3. A new reward function is designed and hindsight experience replay is used to solve the reward sparsity problem in long distance path planning. The planning path is smooth and can achieve real-time path planning in unknown environments. The result of simulation experiments demonstrates the effectiveness of the proposed approach.","PeriodicalId":381600,"journal":{"name":"Proceedings of the 14th International Conference on Computer Modeling and Simulation","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121272205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Information integration for analytics and business intelligence activities from difference data sources in different formats and different database systems necessitates the use of data warehouses. Different data format and coding of the data sources requires extract, transfer, load, or ETL operations to enterprise data warehouses. Fact and dimension tables are main data structures in typical data warehouses. A typical fact table relates to several dimension tables, one of which is a time dimension. A fact instance is based on a point in time. The time granularity depends on the users’ requirements. Dimension tables comprises several attributes, some of which may be time varying over periods of time. These dimensions with time-varying attributes are called slowly changing dimensions (SCD). SCD may cause incorrect analytic problems. Known proposed solutions still have deficiencies. This paper presents a temporal data warehouse. It is a data warehouse which allows multiple temporal attributes for each time varying dimension and solve the SCD-related problems. The proposed design can be implemented by using temporal relational database technology which is currently a part of the SQL standard. Thus, improves productivity, reduces development time, and ease application maintenance. Key temporal data warehouse operations using the temporal features of SQL:2011 are demonstrated.
{"title":"Information Integration and Multiple Slowly Changing Dimensions Modeling","authors":"Thanapol Phungtua-Eng, S. Chittayasothorn","doi":"10.1145/3547578.3547611","DOIUrl":"https://doi.org/10.1145/3547578.3547611","url":null,"abstract":"Information integration for analytics and business intelligence activities from difference data sources in different formats and different database systems necessitates the use of data warehouses. Different data format and coding of the data sources requires extract, transfer, load, or ETL operations to enterprise data warehouses. Fact and dimension tables are main data structures in typical data warehouses. A typical fact table relates to several dimension tables, one of which is a time dimension. A fact instance is based on a point in time. The time granularity depends on the users’ requirements. Dimension tables comprises several attributes, some of which may be time varying over periods of time. These dimensions with time-varying attributes are called slowly changing dimensions (SCD). SCD may cause incorrect analytic problems. Known proposed solutions still have deficiencies. This paper presents a temporal data warehouse. It is a data warehouse which allows multiple temporal attributes for each time varying dimension and solve the SCD-related problems. The proposed design can be implemented by using temporal relational database technology which is currently a part of the SQL standard. Thus, improves productivity, reduces development time, and ease application maintenance. Key temporal data warehouse operations using the temporal features of SQL:2011 are demonstrated.","PeriodicalId":381600,"journal":{"name":"Proceedings of the 14th International Conference on Computer Modeling and Simulation","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127290823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In order to reveal the cross-platform communication characteristics of information in social networks, a three-layer coupled network communication model (TCNM) of "user layer-medium layer-platform layer" is constructed using the SIR communication mechanism and social behavior characteristics, and the three categories of node nearest neighbor, node path and node feature vector are used to determine the node importance and seven indicators to select the communication sources, and the correlation between inter-layer coupling mechanism and communication conditions, communication period and peak value is analyzed. Combined with the experiments, it is concluded that the stronger the inter-layer coupling, the shorter the information propagation period, the faster the peak and the higher the peak; when the inter-layer coupling is weak, the information propagation is fastest when the source is in the platform layer, and the period is smallest and the peak is highest when it is in the media layer. The choice of different source indicators has different effects on the information dissemination cycle and peak value.
{"title":"Analysis of Information Propagation Characteristics in a Class of Three-layer Coupled Networks","authors":"Youpeng Qin, Yuzhi Xiao, Lin-Zong Zhou, Peng Liu","doi":"10.1145/3547578.3547612","DOIUrl":"https://doi.org/10.1145/3547578.3547612","url":null,"abstract":"In order to reveal the cross-platform communication characteristics of information in social networks, a three-layer coupled network communication model (TCNM) of \"user layer-medium layer-platform layer\" is constructed using the SIR communication mechanism and social behavior characteristics, and the three categories of node nearest neighbor, node path and node feature vector are used to determine the node importance and seven indicators to select the communication sources, and the correlation between inter-layer coupling mechanism and communication conditions, communication period and peak value is analyzed. Combined with the experiments, it is concluded that the stronger the inter-layer coupling, the shorter the information propagation period, the faster the peak and the higher the peak; when the inter-layer coupling is weak, the information propagation is fastest when the source is in the platform layer, and the period is smallest and the peak is highest when it is in the media layer. The choice of different source indicators has different effects on the information dissemination cycle and peak value.","PeriodicalId":381600,"journal":{"name":"Proceedings of the 14th International Conference on Computer Modeling and Simulation","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124832689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As the economy grows, more and more people are profiting from investment products, such as gold, bitcoin, etc. Many people make decisions about their investment options by predicting the future price trend of investment products. We combine the prediction results with investors’ mental expectations to give a new model to help investors better decide their investment options. In this paper, we model portfolio of bitcoin and gold based on the price trend data of bitcoin and gold in the last five years. After predicting the trading price trend, we build a psychological expectation investment model to quantify the investors' psychological expectations and get an investment plan with both return and protection. And thus, we show that quantifying the change in investor psychology is a feasible and universal algorithm.
{"title":"Investment Algorithm based on the Psychological Expectation","authors":"Guanlin Li, Xinyu Chen, Yilin Zhang","doi":"10.1145/3547578.3547618","DOIUrl":"https://doi.org/10.1145/3547578.3547618","url":null,"abstract":"As the economy grows, more and more people are profiting from investment products, such as gold, bitcoin, etc. Many people make decisions about their investment options by predicting the future price trend of investment products. We combine the prediction results with investors’ mental expectations to give a new model to help investors better decide their investment options. In this paper, we model portfolio of bitcoin and gold based on the price trend data of bitcoin and gold in the last five years. After predicting the trading price trend, we build a psychological expectation investment model to quantify the investors' psychological expectations and get an investment plan with both return and protection. And thus, we show that quantifying the change in investor psychology is a feasible and universal algorithm.","PeriodicalId":381600,"journal":{"name":"Proceedings of the 14th International Conference on Computer Modeling and Simulation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124352777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dianjun Fang, Zhuoyuan Zheng, Hongyan Jiang, Xiaoxia Ren, Wen-Biaug Yang
China has a massive road freight volume and cargo turnover forming a vast market, but some problems need to be solved urgently. With the rapid development of self-driving systems, the establishment of dedicated freight lines based on self-driving trucks may bring many advantages. An analysis model integrating multiple indexes, including essential operation, time, environment and safety was proposed using the benefit-cost analysis (BCA) method. A case study was carried out according to the actual data of the Beijing-Shanghai Expressway, comparing the diesel-driven and electric-driven self-driving freight lines with the conventional transportation scheme. The analysis result indicates that the diesel-driven self-driving freight line has obvious benefits compared with the conventional scheme. Still, the electric-driven self-driving freight line reflects increased cost on the contrary, which is limited by the current battery technology level.
{"title":"Benefit-cost Analysis-based Modeling of the Self-driving Freight Line","authors":"Dianjun Fang, Zhuoyuan Zheng, Hongyan Jiang, Xiaoxia Ren, Wen-Biaug Yang","doi":"10.1145/3547578.3547588","DOIUrl":"https://doi.org/10.1145/3547578.3547588","url":null,"abstract":"China has a massive road freight volume and cargo turnover forming a vast market, but some problems need to be solved urgently. With the rapid development of self-driving systems, the establishment of dedicated freight lines based on self-driving trucks may bring many advantages. An analysis model integrating multiple indexes, including essential operation, time, environment and safety was proposed using the benefit-cost analysis (BCA) method. A case study was carried out according to the actual data of the Beijing-Shanghai Expressway, comparing the diesel-driven and electric-driven self-driving freight lines with the conventional transportation scheme. The analysis result indicates that the diesel-driven self-driving freight line has obvious benefits compared with the conventional scheme. Still, the electric-driven self-driving freight line reflects increased cost on the contrary, which is limited by the current battery technology level.","PeriodicalId":381600,"journal":{"name":"Proceedings of the 14th International Conference on Computer Modeling and Simulation","volume":"1 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125761679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, by comparing various deduction methods such as on-the-spot deduction, on-map deduction, sand table deduction, war chess deduction, computer deduction, etc., and comprehensively considering the performance of various methods in deduction efficiency, portability and observability, combining with the purpose of electronic blue army tactical deduction (scheme deduction, optimization and optimization), it is determined that the electronic blue army tactical deduction system is mainly composed of electronic sand table and computer simulation system, and its core function is to form a reasonable electronic blue army operational scheme. On this basis, OPM is used to analyze the tactical deduction system of electronic blue army in detail, and the essential components and functions of the system are obtained.
{"title":"Composition and Function Analysis of Electronic Blue Army Tactical Deduction System based on OPM","authors":"Jingping Huang, Xianlong Li, Yamiao Zhang, Lily. Shui","doi":"10.1145/3547578.3547605","DOIUrl":"https://doi.org/10.1145/3547578.3547605","url":null,"abstract":"In this paper, by comparing various deduction methods such as on-the-spot deduction, on-map deduction, sand table deduction, war chess deduction, computer deduction, etc., and comprehensively considering the performance of various methods in deduction efficiency, portability and observability, combining with the purpose of electronic blue army tactical deduction (scheme deduction, optimization and optimization), it is determined that the electronic blue army tactical deduction system is mainly composed of electronic sand table and computer simulation system, and its core function is to form a reasonable electronic blue army operational scheme. On this basis, OPM is used to analyze the tactical deduction system of electronic blue army in detail, and the essential components and functions of the system are obtained.","PeriodicalId":381600,"journal":{"name":"Proceedings of the 14th International Conference on Computer Modeling and Simulation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125872380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, a complete automatic control system is designed for a set of chemical production system. According to the relevant theories of experimental design and regression analysis, orthogonal experiments are designed for the proportion of raw materials and the amount of catalyst in the chemical production system. The regression analysis model is established by using the experimental data, and MATLAB programming is used to seek the regression model parameters and the optimal chemical reaction process parameters. The experimental verification of the optimal process parameters shows that the errors between the predicted value and the verified value are 0.0816% and 0.75445% respectively. This regression model fully meets the actual needs of production. Matlab software, regression analysis mathematical model and orthogonal experiment have important guiding significance for practical production.
{"title":"Design of Chemical Reaction Control System and Optimization of Process Parameters Based on Regression Model Analysis","authors":"Jie Lu","doi":"10.1145/3547578.3547584","DOIUrl":"https://doi.org/10.1145/3547578.3547584","url":null,"abstract":"In this paper, a complete automatic control system is designed for a set of chemical production system. According to the relevant theories of experimental design and regression analysis, orthogonal experiments are designed for the proportion of raw materials and the amount of catalyst in the chemical production system. The regression analysis model is established by using the experimental data, and MATLAB programming is used to seek the regression model parameters and the optimal chemical reaction process parameters. The experimental verification of the optimal process parameters shows that the errors between the predicted value and the verified value are 0.0816% and 0.75445% respectively. This regression model fully meets the actual needs of production. Matlab software, regression analysis mathematical model and orthogonal experiment have important guiding significance for practical production.","PeriodicalId":381600,"journal":{"name":"Proceedings of the 14th International Conference on Computer Modeling and Simulation","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124187332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cong Huang, Chaozhe Wang, S. Chai, Qiqi Tong, Yong Li
Aiming at the policy problem of unmanned combat aerial vehicle (UCAV) evading infrared air-to-air missiles in close air combat, based on the establishment of an infrared offensive and defensive confrontation simulation system, the application of soft actor critic algorithm is studied to train the agent to learn the escape maneuver policy and decoy launching policy of UCAV to evade missiles. The three-dimensional coordinates of the missile in the UCAV body coordinate system and the number of remaining decoys are taken as the input states. The joystick, throttle stick control stroke and the decoy launching pulse are taken as the output actions. The dense reward composed of relative situational parameters and flight parameters and the sparse reward constituted by the result of the decoy interference and the result of the engagement are designed. The soft actor critic (SAC) algorithm is improved to adapt to the action space of mixed continuous action and discrete action, and finally the end-to-end UCAV escape maneuver policy and decoy launching policy from state input to control output is obtained. Through simulation verification, the escape rates of the UCAV with and without the decoys are compared, and the results show that the escape rate with escape maneuver policy realized by the agent can reach 59.0%, and the escape rate combined with the decoy launching policy will increase by 6.7%, finally the UCAV escape rate can reach 65.7%.
{"title":"Research on Evasion Policy of UCAV Against Infrared Air-to-Air Missile Based on Soft Actor Critic Algorithm","authors":"Cong Huang, Chaozhe Wang, S. Chai, Qiqi Tong, Yong Li","doi":"10.1145/3547578.3547602","DOIUrl":"https://doi.org/10.1145/3547578.3547602","url":null,"abstract":"Aiming at the policy problem of unmanned combat aerial vehicle (UCAV) evading infrared air-to-air missiles in close air combat, based on the establishment of an infrared offensive and defensive confrontation simulation system, the application of soft actor critic algorithm is studied to train the agent to learn the escape maneuver policy and decoy launching policy of UCAV to evade missiles. The three-dimensional coordinates of the missile in the UCAV body coordinate system and the number of remaining decoys are taken as the input states. The joystick, throttle stick control stroke and the decoy launching pulse are taken as the output actions. The dense reward composed of relative situational parameters and flight parameters and the sparse reward constituted by the result of the decoy interference and the result of the engagement are designed. The soft actor critic (SAC) algorithm is improved to adapt to the action space of mixed continuous action and discrete action, and finally the end-to-end UCAV escape maneuver policy and decoy launching policy from state input to control output is obtained. Through simulation verification, the escape rates of the UCAV with and without the decoys are compared, and the results show that the escape rate with escape maneuver policy realized by the agent can reach 59.0%, and the escape rate combined with the decoy launching policy will increase by 6.7%, finally the UCAV escape rate can reach 65.7%.","PeriodicalId":381600,"journal":{"name":"Proceedings of the 14th International Conference on Computer Modeling and Simulation","volume":"151 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127762354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In practical application, in order to make the solution obtained from optimization problems have higher practical significance and value in the real world, it is necessary to develop effective optimization methods under uncertainty. The multi-objective optimization method based on evolutionary algorithm is devoted to improving the performance of multi-objective optimization and dealing with uncertainty disturbance, which is very suitable for the related problems to be studied in this paper. In this paper, a new multi-objective evolutionary optimization method is proposed for multi-objective optimization problems with uncertainty in decision space, which aims to find a set of robust optimal solutions and achieve the optimal balance between optimality and robustness. The proposed algorithm uses the idea of multi-tasking and knowledge transfer and uses one population to solve two optimization problems. In this paper, a vector archive updating strategy based on memory mechanism is proposed to maintain the robustness and optimality of Pareto solution set, measure the average and worst case of solutions under different disturbance degrees, and evaluate each solution comprehensively. Experiments show that the proposed robust multi-objective optimization method can obtain a set of robust Pareto optimal solutions in the presence of disturbances, and its robust performance is better than other algorithms in most test problems.
{"title":"Robust Multi-objective Optimization based on the idea of multi-tasking and knowledge transfer","authors":"Yuanjie. Yang","doi":"10.1145/3547578.3547617","DOIUrl":"https://doi.org/10.1145/3547578.3547617","url":null,"abstract":"In practical application, in order to make the solution obtained from optimization problems have higher practical significance and value in the real world, it is necessary to develop effective optimization methods under uncertainty. The multi-objective optimization method based on evolutionary algorithm is devoted to improving the performance of multi-objective optimization and dealing with uncertainty disturbance, which is very suitable for the related problems to be studied in this paper. In this paper, a new multi-objective evolutionary optimization method is proposed for multi-objective optimization problems with uncertainty in decision space, which aims to find a set of robust optimal solutions and achieve the optimal balance between optimality and robustness. The proposed algorithm uses the idea of multi-tasking and knowledge transfer and uses one population to solve two optimization problems. In this paper, a vector archive updating strategy based on memory mechanism is proposed to maintain the robustness and optimality of Pareto solution set, measure the average and worst case of solutions under different disturbance degrees, and evaluate each solution comprehensively. Experiments show that the proposed robust multi-objective optimization method can obtain a set of robust Pareto optimal solutions in the presence of disturbances, and its robust performance is better than other algorithms in most test problems.","PeriodicalId":381600,"journal":{"name":"Proceedings of the 14th International Conference on Computer Modeling and Simulation","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130123114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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