2012 IEEE Congress on Evolutionary Computation最新文献_第10页

Multi-objectivization of short-term unit commitment under uncertainty using evolutionary algorithm 不确定条件下短期机组承诺的多目标化进化算法

2012 IEEE Congress on Evolutionary Computation Pub Date : 2012-06-10 DOI: 10.1109/CEC.2012.6256148

Anupam Trivedi, D. Sharma, D. Srinivasan

{"title":"Multi-objectivization of short-term unit commitment under uncertainty using evolutionary algorithm","authors":"Anupam Trivedi, D. Sharma, D. Srinivasan","doi":"10.1109/CEC.2012.6256148","DOIUrl":"https://doi.org/10.1109/CEC.2012.6256148","url":null,"abstract":"The short-term unit commitment problem is traditionally solved as a single-objective optimization problem with system operation cost as the only objective. This paper presents multi-objectivization of the short-term unit commitment problem in uncertain environment by considering reliability as an additional objective along with the economic objective. The uncertainties occurring due to unit outage and load forecast error are incorporated using loss of load probability (LOLP) and expected unserved energy (EUE) reliability indices. The multi-objectivized unit commitment problem in uncertain environment is solved using our earlier proposed multi-objective evolutionary algorithm [1]. Simulations are performed on a test system of 26 thermal generating units and the results obtained are benchmarked against the study [2] where the unit commitment problem was solved as a reliability-constrained single-objective optimization problem. The simulation results demonstrate that the proposed multi-objectivized approach can find solutions with considerably lower cost than those obtained in the benchmark. Further, the efficiency and consistency of the proposed algorithm for multi-objectivized unit commitment problem is demonstrated by quantitative performance assessment using hypervolume indicator.","PeriodicalId":376837,"journal":{"name":"2012 IEEE Congress on Evolutionary Computation","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128758185","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}

引用次数: 10

On the use of Population Based Incremental Learning to do Reverse Engineering on Gene Regulatory Networks 基于种群的增量学习在基因调控网络逆向工程中的应用

2012 IEEE Congress on Evolutionary Computation Pub Date : 2012-06-10 DOI: 10.1109/CEC.2012.6256580

Leon F Palafox, H. Iba

引用次数: 7

Cooperative Coevolution with global search for large scale global optimization 大规模全局优化的协同进化与全局搜索

2012 IEEE Congress on Evolutionary Computation Pub Date : 2012-06-10 DOI: 10.1109/CEC.2012.6252936

Kai Zhang, Bin Li

引用次数: 18

A new objective function to build seismic networks using differential evolution 差分演化建立地震台网的新目标函数

2012 IEEE Congress on Evolutionary Computation Pub Date : 2012-06-10 DOI: 10.1109/CEC.2012.6252913

Josafath Israel Espinosa Ramos, R. Vázquez

{"title":"A new objective function to build seismic networks using differential evolution","authors":"Josafath Israel Espinosa Ramos, R. Vázquez","doi":"10.1109/CEC.2012.6252913","DOIUrl":"https://doi.org/10.1109/CEC.2012.6252913","url":null,"abstract":"Natural phenomena such as earthquakes have caused devastating effects in different cities around the word. To prevent a great disaster, it is necessary to construct seismic stations at strategical locations to warn population. Many Disaster Alert Systems (DAS), such as the Seismic Alert System of Mexico City (SAS) [4] or the Deep-ocean Assessment and Reporting of Tsunamis (DART II) [11], were located not based in earthquake or tsunami data, but simply by spacing the sensors more or less evenly around the contour of the Pacific Ocean. The objective of a DAS is simple: to emit an alert as fast as possible, in order to warn the population as early as possible. According to a new location of its seismic stations, the SAS could issue a longer warning time. This research focuses on designing the locations of seismic sensing stations maximizing the “warning time”; that is, the gap between the time when an earthquake is detected and the alert is launched, and the arrival time of the disaster. Since locating these stations is basically a numerical problem, in this research, the authors propose a new objective function to maximize the warning time using a differential evolution algorithm. In order to perform the experiments and validate the efficiency of the algorithm, it was considered the epicenters of recorded earthquakes located in the State of Guerrero, México. This data is used in the objective function to set the fitness value of a candidate solution. The main disasters targeted in this paper are earthquakes, but this research can be extended easily to tsunamis or volcanic eruptions alert systems, locating telecommunications antennas, etc.","PeriodicalId":376837,"journal":{"name":"2012 IEEE Congress on Evolutionary Computation","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129179372","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}

引用次数: 3

Autonomous flock brush for non-photorealistic rendering 用于非真实感渲染的自主群刷

2012 IEEE Congress on Evolutionary Computation Pub Date : 2012-06-10 DOI: 10.1109/CEC.2012.6256601

Hsueh En Huang, Y. Ong, Xianshun Chen

引用次数: 5

Japanese international air travel: The relationship between flight ticket price and geodesic distance 日本国际航空旅行:机票价格与测地线距离的关系

2012 IEEE Congress on Evolutionary Computation Pub Date : 2012-06-10 DOI: 10.1109/CEC.2012.6252908

A. Sato

引用次数: 1

Evolution of cellular automata using instruction-based approach 基于指令方法的元胞自动机进化

2012 IEEE Congress on Evolutionary Computation Pub Date : 2012-06-10 DOI: 10.1109/CEC.2012.6256475

Michal Bidlo, Z. Vašíček

引用次数: 17

Comparison of the criteria for updating Kriging response surface models in multi-objective optimization 多目标优化中Kriging响应面模型更新准则的比较

2012 IEEE Congress on Evolutionary Computation Pub Date : 2012-06-10 DOI: 10.1109/CEC.2012.6256492

K. Shimoyama, Koma Sato, S. Jeong, S. Obayashi

{"title":"Comparison of the criteria for updating Kriging response surface models in multi-objective optimization","authors":"K. Shimoyama, Koma Sato, S. Jeong, S. Obayashi","doi":"10.1109/CEC.2012.6256492","DOIUrl":"https://doi.org/10.1109/CEC.2012.6256492","url":null,"abstract":"This paper compares the criteria for updating the Kriging response surface models in multi-objective optimization: expected improvement (EI), expected hypervolume improvement (EHVI), estimation (EST), and those combination (EHVI+EST). EI has been conventionally used as the criterion considering the stochastic improvement of each objective function value individually, while EHVI has been recently proposed as the criterion considering the stochastic improvement of the front of non-dominated solutions in multi-objective optimization. EST is the value of each objective function, which is estimated non-stochastically by the Kriging model without considering its uncertainties. Numerical experiments were implemented in the welded beam design problem, and empirically showed that, in a non-constrained case, EHVI keeps a balance between accurate and wide search for non-dominated solutions on the Kriging models in multi-objective optimization. In addition, the present experiments suggested future investigation into the techniques for handling uncertain constraints to enhance the capability of EHVI in a constrained case.","PeriodicalId":376837,"journal":{"name":"2012 IEEE Congress on Evolutionary Computation","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131088016","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}

引用次数: 24

Differential evolution with a mix of Constraint Consenus methods for solving a real-world Optimization Problem 混合约束共识方法的差分进化求解现实世界的优化问题

2012 IEEE Congress on Evolutionary Computation Pub Date : 2012-06-10 DOI: 10.1109/CEC.2012.6252904

Noha M. Hamza, R. Sarker, D. Essam

引用次数: 7

A repair mechanism for active inequality constraint handling 主动不等式约束处理的修复机制

2012 IEEE Congress on Evolutionary Computation Pub Date : 2012-06-10 DOI: 10.1109/CEC.2012.6256498

Amit Saha, T. Ray

引用次数: 4