2015 IEEE Congress on Evolutionary Computation (CEC)最新文献_第10页

A sensor tagging approach for reusing building blocks of knowledge in learning classifier systems 在学习分类器系统中重用知识构建块的传感器标记方法

2015 IEEE Congress on Evolutionary Computation (CEC) Pub Date : 2015-05-25 DOI: 10.1109/CEC.2015.7257256

Liang-yu Chen, Po-Ming Lee, T. Hsiao

{"title":"A sensor tagging approach for reusing building blocks of knowledge in learning classifier systems","authors":"Liang-yu Chen, Po-Ming Lee, T. Hsiao","doi":"10.1109/CEC.2015.7257256","DOIUrl":"https://doi.org/10.1109/CEC.2015.7257256","url":null,"abstract":"During the last decade, the extraction and reuse of building blocks of knowledge for the learning process of Extended Classifier System (XCS) in Multiplexer (MUX) problem domain have been demonstrate feasible by using Code Fragment (CF) (i.e. a tree-based structure ordinarily used in the field of Genetic Programming (GP)) as the representation of classifier conditions (the resulting system was called XCSCFC). However, the use of the tree-based structure may lead to the bloating problem and increase in time complexity when the tree grows deep. Therefore, we proposed a novel representation of classifier conditions for the XCS, named Sensory Tag (ST). The XCS with the ST as the input representation is called XCSSTC. The experiments of the proposed method were conducted in the MUX problem domain. The results indicate that the XCSSTC is capable of reusing building blocks of knowledge in the MUX problems. The current study also discussed about two different aspects of reusing of building blocks of knowledge. Specifically, we proposed the “attribution selection” part and the “logical relation between the attributes” part.","PeriodicalId":403666,"journal":{"name":"2015 IEEE Congress on Evolutionary Computation (CEC)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127772556","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: 4

Can OneMax help optimizing LeadingOnes using the EA+RL method? OneMax可以使用EA+RL方法帮助优化LeadingOnes吗?

2015 IEEE Congress on Evolutionary Computation (CEC) Pub Date : 2015-05-25 DOI: 10.1109/CEC.2015.7257100

M. Buzdalov, Arina Buzdalova

引用次数: 8

An evolutionary approach to the identification of Cellular Automata based on partial observations 基于局部观测的元胞自动机识别的进化方法

2015 IEEE Congress on Evolutionary Computation (CEC) Pub Date : 2015-05-25 DOI: 10.1109/CEC.2015.7257258

W. Bołt, J. Baetens, B. Baets

引用次数: 4

Algorithm structure optimization by choosing operators in multiobjective genetic local search 基于算子选择的多目标遗传局部搜索算法结构优化

2015 IEEE Congress on Evolutionary Computation (CEC) Pub Date : 2015-05-25 DOI: 10.1109/CEC.2015.7256980

Yuki Tanigaki, Hiroyuki Masuda, Yu Setoguchi, Y. Nojima, H. Ishibuchi

{"title":"Algorithm structure optimization by choosing operators in multiobjective genetic local search","authors":"Yuki Tanigaki, Hiroyuki Masuda, Yu Setoguchi, Y. Nojima, H. Ishibuchi","doi":"10.1109/CEC.2015.7256980","DOIUrl":"https://doi.org/10.1109/CEC.2015.7256980","url":null,"abstract":"An important implementation issue in the design of hybrid evolutionary multiobjective optimization algorithms such as multiobjective genetic local search (MOGLS) is how to combine local search with evolutionary algorithms. It has been demonstrated that the performance of MOGLS strongly depends on the order of global search and local search. A balance between local search and global search also affects its search ability. We can use three ideas for designing high-performance MOGLS algorithms. One idea is to choose one of two options: local search after global search or global search after local search. In general, their appropriate order depends on the problem. Another idea is to use tuned parameter values to appropriately specify their balance. The other idea is to change both their order and the parameter values during the execution of MOGLS. This idea can be implemented by dividing the whole search period into some sub-periods (i.e., dividing all generations into some intervals of generations). The appropriate order and parameter values are assigned to each sub-period. In this paper, we propose off-line algorithm structure optimization for MOGLS. The effectiveness of the proposed idea is examined by computational experiments on a two-objective knapsack problem and a two-objective flowshop scheduling problem. Based on experimental results, we discuss the importance of structure optimization of MOGLS.","PeriodicalId":403666,"journal":{"name":"2015 IEEE Congress on Evolutionary Computation (CEC)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133537108","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: 2

Multi-objective optimization of auto-tap-changer pole transformer considering optimum placement in distribution systems 考虑配电系统中最优配置的自分接开关极变多目标优化

2015 IEEE Congress on Evolutionary Computation (CEC) Pub Date : 2015-05-25 DOI: 10.1109/CEC.2015.7256989

Ryuto Shigenobu, M. Palmer

{"title":"Multi-objective optimization of auto-tap-changer pole transformer considering optimum placement in distribution systems","authors":"Ryuto Shigenobu, M. Palmer","doi":"10.1109/CEC.2015.7256989","DOIUrl":"https://doi.org/10.1109/CEC.2015.7256989","url":null,"abstract":"This paper proposes the application of multi-objective optimization to tap changing transformers in a distribution system. Conventional electrical power systems do not consider reverse power flow, in which the power flows toward the power system in distribution systems. When large quantities of distributed generators (DGs) are introduced into a distribution system they can cause voltage deviations beyond the statutory range, and can reverse flow toward the substation transformer. Consequently, this cause faults in electricity devices and even lead to a massive blackout. This is an important issue within the distribution system. To resolve voltage deviation problems it is necessary to consider some trade-offs. However, there is not much research adapting multi-objective optimization for use in the distribution system. Therefore this paper provides a method of multi-objective optimization in order to minimize voltage deviation while simultaneously minimizing the number of introduced voltage control devices and finding an optimum placement of those voltage control devices. Moreover, an optimum scheduling of the distribution system is adopted.","PeriodicalId":403666,"journal":{"name":"2015 IEEE Congress on Evolutionary Computation (CEC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134230359","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: 2

Analysis of chaotic maps applied to self-organizing maps for the Traveling Salesman Problem 混沌映射在旅行商问题自组织映射中的应用分析

2015 IEEE Congress on Evolutionary Computation (CEC) Pub Date : 2015-05-25 DOI: 10.1109/CEC.2015.7257094

Remo Ryter, Michael Stauffer, T. Hanne, Rolf Dornberger

引用次数: 5

A 2.45GHz microstrip patch antenna evolved for WiFi application 为WiFi应用开发了2.45GHz微带贴片天线

2015 IEEE Congress on Evolutionary Computation (CEC) Pub Date : 2015-05-25 DOI: 10.1109/CEC.2015.7257024

Zongchao Weng, Dayue Guo, Yong Wu, Meng Li, Jun Hu, Weizhen Zeng, Xi Li, Sanyou Zeng

引用次数: 10

GDE-MOEA: A new MOEA based on the generational distance indicator and ε-dominance GDE-MOEA:基于代距指标和ε-优势度的一种新的MOEA

2015 IEEE Congress on Evolutionary Computation (CEC) Pub Date : 2015-05-25 DOI: 10.1109/CEC.2015.7256992

A. Menchaca-Méndez, C. Coello

{"title":"GDE-MOEA: A new MOEA based on the generational distance indicator and ε-dominance","authors":"A. Menchaca-Méndez, C. Coello","doi":"10.1109/CEC.2015.7256992","DOIUrl":"https://doi.org/10.1109/CEC.2015.7256992","url":null,"abstract":"In this paper, we propose a new selection mechanism based on ε-dominance which is called “ε-selection”. An interesting feature of this selection scheme is that it does not require to set the value of o ahead of time. Our ε-selection is incorporated into the GD-MOEA algorithm, giving rise to the so-called “Generational Distance & ε-dominance Multi-Objective Evolutionary Algorithm (GDE-MOEA)”. Our proposed GDE-MOEA is validated using standard test functions taken from the specialized literature, having three to six objective functions. GDE-MOEA is compared with respect to the original GD-MOEA, which is based on the generational distance indicator and a technique based on Euclidean distances to improve the diversity in the population. Additionally, our proposed approach is compared with respect to MOEA/D using Penalty Boundary Intersection (PBI), which is based on decomposition, and SMS-EMOA-HYPE (a version of SMS-EMOA that uses a fitness assignment scheme based on the use of an approximation of the hypervolume indicator). Our preliminary results indicate that our proposed GDE-MOEA is a good alternative to solve multi-objective optimization problems having both low dimensionality and high dimensionality in objective function space because it obtains better results than GD-MOEA and MOEA/D in most cases and it is competitive with respect to SMS-EMOA-HYPE but at a much lower computational cost.","PeriodicalId":403666,"journal":{"name":"2015 IEEE Congress on Evolutionary Computation (CEC)","volume":"397 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113998381","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: 23

An ancestor based extension to Differential Evolution (AncDE) for Single-Objective Computationally Expensive Numerical Optimization 基于祖先的差分进化(AncDE)在单目标昂贵计算数值优化中的扩展

2015 IEEE Congress on Evolutionary Computation (CEC) Pub Date : 2015-05-25 DOI: 10.1109/CEC.2015.7257293

Rushikesh Sawant, D. Hatton, D. O'Donoghue

{"title":"An ancestor based extension to Differential Evolution (AncDE) for Single-Objective Computationally Expensive Numerical Optimization","authors":"Rushikesh Sawant, D. Hatton, D. O'Donoghue","doi":"10.1109/CEC.2015.7257293","DOIUrl":"https://doi.org/10.1109/CEC.2015.7257293","url":null,"abstract":"This paper presents the Ancestral Differential Evolution (AncDE) algorithm, which extends the standard Differential Evolution (DE) algorithm by adding an archive of recently discarded ancestors. AncDE adds the ability to occasionally compute difference vectors between current and archived solutions, using these inter-generational difference vectors in place of traditional difference vectors. Results for AncDE are presented for the CEC2015 Bound Constrained Single-Objective Computationally Expensive Numerical Optimization Problems using AncDE/best/1/bin. Summary results are included for standard DE for comparison purposes and these show that AncDE generally outperforms standard DE. These results suggest that the inter-generational difference vectors can help overcome some local optima, leading to faster convergence towards the global optimum. AncDE involves the very small overhead of storing and updating the ancestral cache. This paper introduces two empirically determined stochastic rates; one for updating the ancestral cache and the other for using an ancestral difference vector in place of the normal difference vector.","PeriodicalId":403666,"journal":{"name":"2015 IEEE Congress on Evolutionary Computation (CEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115711924","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: 5

Multi-population inflationary differential evolution algorithm with Adaptive Local Restart 具有自适应局部重启的多种群膨胀差分进化算法

2015 IEEE Congress on Evolutionary Computation (CEC) Pub Date : 2015-05-25 DOI: 10.1109/CEC.2015.7256950

M. D. Carlo, M. Vasile, E. Minisci

引用次数: 27