In this paper, our objective is to conduct comprehensive tests for competitive coevolution using an evolutionary multiobjective algorithm for 3 dimensional problems. This competitive coevolution will be implemented with k-random opponents strategy. A new algorithm which integrates competitive coevolution (CE) and the strength Pareto evolutionary algorithm 2 (SPEA2) is proposed to achieve this objective. The resulting algorithm is referred to as the strength Pareto evolutionary algorithm 2 with competitive coevolution (SPEA2-CE). The performance between SPEA2-CE is compared against SPEA2 to solve problems with each having three objectives using DTLZ suite of test problems. In general, the results show that the SPEA2-CE with k- random opponents performed well for the generational distance and coverage but performed less favorably for spacing.
{"title":"Competitive Coevolution with K-Random Opponents for Pareto Multiobjective Optimization","authors":"Tse Guan Tan, J. Teo, H. Lau","doi":"10.1109/ICNC.2007.309","DOIUrl":"https://doi.org/10.1109/ICNC.2007.309","url":null,"abstract":"In this paper, our objective is to conduct comprehensive tests for competitive coevolution using an evolutionary multiobjective algorithm for 3 dimensional problems. This competitive coevolution will be implemented with k-random opponents strategy. A new algorithm which integrates competitive coevolution (CE) and the strength Pareto evolutionary algorithm 2 (SPEA2) is proposed to achieve this objective. The resulting algorithm is referred to as the strength Pareto evolutionary algorithm 2 with competitive coevolution (SPEA2-CE). The performance between SPEA2-CE is compared against SPEA2 to solve problems with each having three objectives using DTLZ suite of test problems. In general, the results show that the SPEA2-CE with k- random opponents performed well for the generational distance and coverage but performed less favorably for spacing.","PeriodicalId":250881,"journal":{"name":"Third International Conference on Natural Computation (ICNC 2007)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124091947","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 constrained optimization problems, evolutionary algorithms often utilize a penalty function to deal with constraints, which is, however, difficult to control the penalty parameters. This paper therefore presents a new constraint handling scheme. It adaptively defines an extended-feasible region that includes not only all feasible solutions, but some infeasible solutions near the boundary of the feasible region. Furthermore, we construct a new fitness function based on stochastic ranking, and meanwhile propose a new crossover operator that can produce more good individuals in general. Accordingly, a new evolutionary algorithm for constrained optimization problems is proposed. The simulations show the efficiency of the proposed algorithm on four benchmark problems.
{"title":"A Ranking-Based Evolutionary Algorithm for Constrained Optimization Problems","authors":"Yibo Hu, Yiu-ming Cheung, Yuping Wang","doi":"10.1109/ICNC.2007.129","DOIUrl":"https://doi.org/10.1109/ICNC.2007.129","url":null,"abstract":"In constrained optimization problems, evolutionary algorithms often utilize a penalty function to deal with constraints, which is, however, difficult to control the penalty parameters. This paper therefore presents a new constraint handling scheme. It adaptively defines an extended-feasible region that includes not only all feasible solutions, but some infeasible solutions near the boundary of the feasible region. Furthermore, we construct a new fitness function based on stochastic ranking, and meanwhile propose a new crossover operator that can produce more good individuals in general. Accordingly, a new evolutionary algorithm for constrained optimization problems is proposed. The simulations show the efficiency of the proposed algorithm on four benchmark problems.","PeriodicalId":250881,"journal":{"name":"Third International Conference on Natural Computation (ICNC 2007)","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124146284","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}
Dynamic multi-objective optimization problems are very common in real-world applications. The researches on applying evolutionary algorithm into such problems are attracting more and more researchers. In this paper, a new dynamic multi-objective optimization evolutionary algorithm which utilizes hyper-mutation operator to deal with dynamics and geometrical Pareto selection to deal with multi-objective is introduced. The experimental results show that the performance is satisfactory.
{"title":"A New Dynamic Multi-objective Optimization Evolutionary Algorithm","authors":"Bojin Zheng","doi":"10.1109/ICNC.2007.91","DOIUrl":"https://doi.org/10.1109/ICNC.2007.91","url":null,"abstract":"Dynamic multi-objective optimization problems are very common in real-world applications. The researches on applying evolutionary algorithm into such problems are attracting more and more researchers. In this paper, a new dynamic multi-objective optimization evolutionary algorithm which utilizes hyper-mutation operator to deal with dynamics and geometrical Pareto selection to deal with multi-objective is introduced. The experimental results show that the performance is satisfactory.","PeriodicalId":250881,"journal":{"name":"Third International Conference on Natural Computation (ICNC 2007)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127711921","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}
A self-organizing particle swarm optimization algorithm is developed for solving premature convergence of particle swarm optimization. According to adaptively adjusting acceleration coefficients and inertia weight, the particles are organized to track the domain of attraction of local optimum and the domain of attraction global optimum respectively during the search. Meanwhile the corresponding strategies with mutation are adopted in different stages of this algorithm to further enhance diversity of population. Experimental results for complex function optimization and nonlinear system identification show that this algorithm improves the global convergence ability and efficiently prevents the algorithm from the local optimization and early maturation.
{"title":"A Self-Organizing Particle Swarm Optimization Algorithm and Application","authors":"Yuanxia Shen, Chuanhua Zeng","doi":"10.1109/ICNC.2007.137","DOIUrl":"https://doi.org/10.1109/ICNC.2007.137","url":null,"abstract":"A self-organizing particle swarm optimization algorithm is developed for solving premature convergence of particle swarm optimization. According to adaptively adjusting acceleration coefficients and inertia weight, the particles are organized to track the domain of attraction of local optimum and the domain of attraction global optimum respectively during the search. Meanwhile the corresponding strategies with mutation are adopted in different stages of this algorithm to further enhance diversity of population. Experimental results for complex function optimization and nonlinear system identification show that this algorithm improves the global convergence ability and efficiently prevents the algorithm from the local optimization and early maturation.","PeriodicalId":250881,"journal":{"name":"Third International Conference on Natural Computation (ICNC 2007)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126210490","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}
Ball mill coal pulverizing system of pelletizing plant is a complex nonlinear multivariable process with strongly coupling and time-delay, whose operations often varies violently. The automatic control of such systems is a research focus in the process control area. A new multivariable PID decoupling controller is proposed in this paper, which consists of diagonally matrix method-based decomposition compensatory unit, PID controller and fuzzy self-tuning components unit with scaling facto. Particle swarm optimization algorithm is also adopted to optimize parameters of PID controller. Simulation results show the validity of the model obtained and the control method proposed in this paper, the new method can overcome nonlinear and strong coupling features of the system in a wide range, and it has strong robustness and adaptability.
{"title":"Self-Tuning Multivariable PID Decoupling Controller of Ball Mill Pulverizing System","authors":"Jie-sheng Wang","doi":"10.1109/ICNC.2007.655","DOIUrl":"https://doi.org/10.1109/ICNC.2007.655","url":null,"abstract":"Ball mill coal pulverizing system of pelletizing plant is a complex nonlinear multivariable process with strongly coupling and time-delay, whose operations often varies violently. The automatic control of such systems is a research focus in the process control area. A new multivariable PID decoupling controller is proposed in this paper, which consists of diagonally matrix method-based decomposition compensatory unit, PID controller and fuzzy self-tuning components unit with scaling facto. Particle swarm optimization algorithm is also adopted to optimize parameters of PID controller. Simulation results show the validity of the model obtained and the control method proposed in this paper, the new method can overcome nonlinear and strong coupling features of the system in a wide range, and it has strong robustness and adaptability.","PeriodicalId":250881,"journal":{"name":"Third International Conference on Natural Computation (ICNC 2007)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127998077","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, firstly, the existing problems of the solution of weight vector of triangular fuzzy number complementary judgment matrix, which are proposed by Xu (2004) and Gu (2006), are discussed. Secondly, on the basis of the consistency definition for triangular fuzzy number complementary judgment matrix (TFNCJM) proposed by Gu (2006), a consistency sufficient condition of TFNCJM is proposed, and a linear goal programming of TFNCJM is established. Then the weight vector of TFNCJM is obtained by solving the model. Thirdly, the paper gives a new priority formula for triangular fuzzy number, and the priority of alternatives are obtained by using the formula. Finally, a numerical example is given to show their feasibility and effectiveness.
{"title":"A New Priority Method for Triangular Fuzzy Number Complementary Judgment Matrix","authors":"Xue-lan Zeng, F. Meng, Meihua Chen","doi":"10.1109/ICNC.2007.102","DOIUrl":"https://doi.org/10.1109/ICNC.2007.102","url":null,"abstract":"In this paper, firstly, the existing problems of the solution of weight vector of triangular fuzzy number complementary judgment matrix, which are proposed by Xu (2004) and Gu (2006), are discussed. Secondly, on the basis of the consistency definition for triangular fuzzy number complementary judgment matrix (TFNCJM) proposed by Gu (2006), a consistency sufficient condition of TFNCJM is proposed, and a linear goal programming of TFNCJM is established. Then the weight vector of TFNCJM is obtained by solving the model. Thirdly, the paper gives a new priority formula for triangular fuzzy number, and the priority of alternatives are obtained by using the formula. Finally, a numerical example is given to show their feasibility and effectiveness.","PeriodicalId":250881,"journal":{"name":"Third International Conference on Natural Computation (ICNC 2007)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128114612","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, we will apply genetic programming (GP) technique to develop two strategies: the ghost (attacker) and players (survivors) in the Traffic Light Game (a popular game among children). These two strategies are competing for each other. By applying GP, each one strategy is used as an "imaginary enemy" to evolve (train) another strategy. Based on this co-evolution process, the final developed strategies: the ghost can effectively capture the players, and the players can also escape from the ghost, rescue partners and detour the obstacles. Part of developed strategies had achieved success beyond our wildest dreams. The results encourage us to develop more complex strategies or cooperative models such as human learning models, the cooperative models of robot, and self learning of virtual agents.
{"title":"Strategy Development by Genetic Programming","authors":"Koun-Tem Sun, Yi-Chun Lin, Cheng-Yen Wu, Yueh-Min Huang","doi":"10.1109/ICNC.2007.683","DOIUrl":"https://doi.org/10.1109/ICNC.2007.683","url":null,"abstract":"In this paper, we will apply genetic programming (GP) technique to develop two strategies: the ghost (attacker) and players (survivors) in the Traffic Light Game (a popular game among children). These two strategies are competing for each other. By applying GP, each one strategy is used as an \"imaginary enemy\" to evolve (train) another strategy. Based on this co-evolution process, the final developed strategies: the ghost can effectively capture the players, and the players can also escape from the ghost, rescue partners and detour the obstacles. Part of developed strategies had achieved success beyond our wildest dreams. The results encourage us to develop more complex strategies or cooperative models such as human learning models, the cooperative models of robot, and self learning of virtual agents.","PeriodicalId":250881,"journal":{"name":"Third International Conference on Natural Computation (ICNC 2007)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128171541","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}
Sheng Lu, Xiao-Li Cao, Zhong-Jian Cai, Gaorong Zeng, Tan Liu
Based on the theory of optical-mechanical-electrical automatic ranging system of vehicles, paper has a discussion and research of the implementation and design of auto ranging system with risk estimation and decision. The hardware is based on MPC5200. And paper includes the design of hardware architecture, software architecture and key techniques, of hardware development, etc. The system adopts the laser-lidar ranging method to get a high precision. Paper focused on the signal processing of laser-lidar and waveforms selection of the detection system.
{"title":"Implementation and Design of Auto Ranging System with Risk Estimation for Vehicles","authors":"Sheng Lu, Xiao-Li Cao, Zhong-Jian Cai, Gaorong Zeng, Tan Liu","doi":"10.1109/ICNC.2007.435","DOIUrl":"https://doi.org/10.1109/ICNC.2007.435","url":null,"abstract":"Based on the theory of optical-mechanical-electrical automatic ranging system of vehicles, paper has a discussion and research of the implementation and design of auto ranging system with risk estimation and decision. The hardware is based on MPC5200. And paper includes the design of hardware architecture, software architecture and key techniques, of hardware development, etc. The system adopts the laser-lidar ranging method to get a high precision. Paper focused on the signal processing of laser-lidar and waveforms selection of the detection system.","PeriodicalId":250881,"journal":{"name":"Third International Conference on Natural Computation (ICNC 2007)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125461353","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}
A novel model of the electric wave signal of the plant is established for the first time, there is x (n) =1.9591 times (n - 1) - 1.4927 times (n - 2) + 0.7205 times (n - 3) - 0.80219 times (n - 4) + 0.44582 times (n-5)- 0.30807 times (n - 6) + 0.19658 times (n - 7) - 0.34506 times (n - 8) + 0.52419 times (n - 9) - 0.339 times (n - 10) + 0.16681 times (n - 11) - 0.09664 times (n - 12) + 0.3625 times (n - 17) - 0.02005 times (n - 18); the fitting variance is 0.315951 and the standard deviation is 0.562095 in Aloe vera var. chinensis. It has a well effect that the fitting variance and standard deviation of models are the minimum. It is very well in the prediction effect of the AR model to the forecast 10 values of the plant electric wave signals respectively is well, and proves that the coefficient of AR model can represent main characters of plant electric wave signals. It is very importance that the function of plant electric wave signals are used to understand some regulations on the growth relationship between plants and environments.
{"title":"A Prediction on Electric Signals Processing of Aloe Vera Var. Chinensis","authors":"Lanzhou Wang, Haixia Li, Dongsheng Li, Jiayin Zhao","doi":"10.1109/ICNC.2007.127","DOIUrl":"https://doi.org/10.1109/ICNC.2007.127","url":null,"abstract":"A novel model of the electric wave signal of the plant is established for the first time, there is x (n) =1.9591 times (n - 1) - 1.4927 times (n - 2) + 0.7205 times (n - 3) - 0.80219 times (n - 4) + 0.44582 times (n-5)- 0.30807 times (n - 6) + 0.19658 times (n - 7) - 0.34506 times (n - 8) + 0.52419 times (n - 9) - 0.339 times (n - 10) + 0.16681 times (n - 11) - 0.09664 times (n - 12) + 0.3625 times (n - 17) - 0.02005 times (n - 18); the fitting variance is 0.315951 and the standard deviation is 0.562095 in Aloe vera var. chinensis. It has a well effect that the fitting variance and standard deviation of models are the minimum. It is very well in the prediction effect of the AR model to the forecast 10 values of the plant electric wave signals respectively is well, and proves that the coefficient of AR model can represent main characters of plant electric wave signals. It is very importance that the function of plant electric wave signals are used to understand some regulations on the growth relationship between plants and environments.","PeriodicalId":250881,"journal":{"name":"Third International Conference on Natural Computation (ICNC 2007)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125733597","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}
Considering the unreasonable currency structure of Chinese foreign reserve, this paper analyzed the optional asset sorts according to currency structure of trade and investment, as well as current status of global international reserves. The author took the hypothesis of interest rate parity to figure the dynamic return of different assets and its expected depreciation, and constructed a quadratic programming constrained model to analyze quantitatively how to adjust foreign reserve structure dynamically. Empirical results show that China needs not only to decrease dollar reserve to increase the reserve of Euro, Yen and Pound, but also to switch part of foreign reserve into gold reserve.
{"title":"Theoretical and Empirical Research on Dynamic Optimization Model of Structural Adjustment of International Reserves","authors":"Jie Ma, Fang Shu","doi":"10.1109/ICNC.2007.756","DOIUrl":"https://doi.org/10.1109/ICNC.2007.756","url":null,"abstract":"Considering the unreasonable currency structure of Chinese foreign reserve, this paper analyzed the optional asset sorts according to currency structure of trade and investment, as well as current status of global international reserves. The author took the hypothesis of interest rate parity to figure the dynamic return of different assets and its expected depreciation, and constructed a quadratic programming constrained model to analyze quantitatively how to adjust foreign reserve structure dynamically. Empirical results show that China needs not only to decrease dollar reserve to increase the reserve of Euro, Yen and Pound, but also to switch part of foreign reserve into gold reserve.","PeriodicalId":250881,"journal":{"name":"Third International Conference on Natural Computation (ICNC 2007)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121730052","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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