Abstract - We propose a new smoothing function in this paper by smoothing the symmetric perturbed Fischer-Burmeister function. Based on this new function, we present a new noninterior continuation method for solving the second-order cone programming. We adopt a variant merit function. Our algorithm needs to solve only one system of linear equations and to perform only one line search at each iteration. It can start from an arbitrary point and does not require the iteration points to be in the set of strictly feasible solutions. We prove the global and local quadratic convergence of the algorithm under suitable assumptions. Numerical results indicate that our algorithm performs well.
{"title":"A new non-interior continuation method for second-order cone programming","authors":"Jingyong Tang, G. He, Liang Fang","doi":"10.1515/jnum-2013-0012","DOIUrl":"https://doi.org/10.1515/jnum-2013-0012","url":null,"abstract":"Abstract - We propose a new smoothing function in this paper by smoothing the symmetric perturbed Fischer-Burmeister function. Based on this new function, we present a new noninterior continuation method for solving the second-order cone programming. We adopt a variant merit function. Our algorithm needs to solve only one system of linear equations and to perform only one line search at each iteration. It can start from an arbitrary point and does not require the iteration points to be in the set of strictly feasible solutions. We prove the global and local quadratic convergence of the algorithm under suitable assumptions. Numerical results indicate that our algorithm performs well.","PeriodicalId":183428,"journal":{"name":"International Joint Conference on Computational Sciences and Optimization","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133153136","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}
We propose general disruption management models for a production and inventory control system. The models are developed in a multi-sourcing supply chain network, where these supply channels are susceptible to disruption risks. Properties of the object function are considered and closed-form solutions for the model is obtained. The effects of the parameters on the optimal policy are discussed analytically and through numerical experiments.
{"title":"Multi-source Supply Chains with Disruption Risk","authors":"Qi-feng Wang, Xiao-Shen Li, Wei Huang","doi":"10.1109/CSO.2012.100","DOIUrl":"https://doi.org/10.1109/CSO.2012.100","url":null,"abstract":"We propose general disruption management models for a production and inventory control system. The models are developed in a multi-sourcing supply chain network, where these supply channels are susceptible to disruption risks. Properties of the object function are considered and closed-form solutions for the model is obtained. The effects of the parameters on the optimal policy are discussed analytically and through numerical experiments.","PeriodicalId":183428,"journal":{"name":"International Joint Conference on Computational Sciences and Optimization","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122092662","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 the Smart grid, network security is the important part. In this paper, we will introduce a new method detection based on Support Vector Machines to detect Masquerade attack, and test it and other methods on the dataset from keyboard commands on a UNIX platform. The presence of shared tuples would cause many attacks in this dataset to be difficultly detected, just as other researchers shown. In order to eliminate their negative influence on masquerade detection, we take some preprocessing for the dataset before detecting masquerade attacks. Our results show that after removing the shared tuples, the classifiers based on support vector machines outperforms the original approaches presented.
{"title":"Masquerade Detection Using Support Vector Machines in the Smart Grid","authors":"Xiang Zhao, Guangyu Hu, Z. Wu","doi":"10.1109/CSO.2014.15","DOIUrl":"https://doi.org/10.1109/CSO.2014.15","url":null,"abstract":"In the Smart grid, network security is the important part. In this paper, we will introduce a new method detection based on Support Vector Machines to detect Masquerade attack, and test it and other methods on the dataset from keyboard commands on a UNIX platform. The presence of shared tuples would cause many attacks in this dataset to be difficultly detected, just as other researchers shown. In order to eliminate their negative influence on masquerade detection, we take some preprocessing for the dataset before detecting masquerade attacks. Our results show that after removing the shared tuples, the classifiers based on support vector machines outperforms the original approaches presented.","PeriodicalId":183428,"journal":{"name":"International Joint Conference on Computational Sciences and Optimization","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124459635","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}
The injection mold optimization problems always require huge computer resources, so the grid is a good choice for solving these problems. But for the heterogeneous, distributed and dynamic characters of the grid resources, it is difficult to finish the complex problems efficiently in collaborative way by grid. Based on the Globus Toolkits 4, a four-layer Mold Design Grid (MDG) platform was constructed to meet resource sharing for the complex injection mold optimization. By using multi-population genetic strategy and information-entropy based searching technique, a grid algorithm was presented to optimize the gate location of injection mold on MDG. It deals with the massive high coupling task-blocks in collaborative way and reduces the times of the iteration efficiently. Examples have been conducted successfully by using the proposed grid algorithm on MDG, and results indicate that the proposed grid algorithm performs high speedup and efficiency.
{"title":"A Grid Algorithm for Injection Gate Location Optimization Based on MDG","authors":"Zhendong Cui, Xicheng Wang, Jianke Zhang, Shenming Gu","doi":"10.1109/CSO.2009.280","DOIUrl":"https://doi.org/10.1109/CSO.2009.280","url":null,"abstract":"The injection mold optimization problems always require huge computer resources, so the grid is a good choice for solving these problems. But for the heterogeneous, distributed and dynamic characters of the grid resources, it is difficult to finish the complex problems efficiently in collaborative way by grid. Based on the Globus Toolkits 4, a four-layer Mold Design Grid (MDG) platform was constructed to meet resource sharing for the complex injection mold optimization. By using multi-population genetic strategy and information-entropy based searching technique, a grid algorithm was presented to optimize the gate location of injection mold on MDG. It deals with the massive high coupling task-blocks in collaborative way and reduces the times of the iteration efficiently. Examples have been conducted successfully by using the proposed grid algorithm on MDG, and results indicate that the proposed grid algorithm performs high speedup and efficiency.","PeriodicalId":183428,"journal":{"name":"International Joint Conference on Computational Sciences and Optimization","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130156533","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}
Image processing is an important aspect of microarray experiments. Spots segmentation, which is to distinguish the spot signals from background pixels, is a critical step in microarray image processing. After analyzing other means of microarray segmentation, a new method based on Expectation Maximization (EM) algorithm, mathematical morphological filtering and morphological processing is presented. And its corresponding theory and realizable steps are introduced in this paper. Simulations show that the new method for spot image segmentation has better performance than most common ways, such as the ScanAlizeTM method and GenePixTM method. The results of experiments, which are computationally attractive, have excellent performance and can preserve structural information while efficiently suppressing noise in DNA microarray data.
{"title":"Microarray Image Processing Using Expectation Maximization Algorithm and Mathematical Morphology","authors":"G. Weng, Jian Su","doi":"10.1109/CSO.2009.91","DOIUrl":"https://doi.org/10.1109/CSO.2009.91","url":null,"abstract":"Image processing is an important aspect of microarray experiments. Spots segmentation, which is to distinguish the spot signals from background pixels, is a critical step in microarray image processing. After analyzing other means of microarray segmentation, a new method based on Expectation Maximization (EM) algorithm, mathematical morphological filtering and morphological processing is presented. And its corresponding theory and realizable steps are introduced in this paper. Simulations show that the new method for spot image segmentation has better performance than most common ways, such as the ScanAlizeTM method and GenePixTM method. The results of experiments, which are computationally attractive, have excellent performance and can preserve structural information while efficiently suppressing noise in DNA microarray data.","PeriodicalId":183428,"journal":{"name":"International Joint Conference on Computational Sciences and Optimization","volume":"12 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113965168","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}
The premature problem of Particle Swarm Optimization(PSO) leads the missing of the global optima and the failure of searching process. To solve this problem, the chaotic PSO based on sub-energy tunneling is proposed. This algorithm introduces the concept of sub-energy tunneling of TRUST algorithm to transform the objective function in optimization problem. And it uses the Logistic series to replace the random number in PSO. With maintaining the optimization properties of the original objective function, the speed of particles searching the optimization is accelerated. The difference and relationship between the sub-energy tunneling and traditional transform are analyzed. In the numerical experiment, the proposed algorithm and some PSOs based on function transform are compared. The results show that the PSO based on sub-energy tunneling has a higher convergence speed and it can improve the searching efficiency. So the chaotic PSO based on sub-energy tunneling is valid and effective.
{"title":"The Chaotic Particle Swarm Optimization Based on Sub-Energy Tunneling","authors":"Yuemei Yang","doi":"10.1109/CSO.2012.40","DOIUrl":"https://doi.org/10.1109/CSO.2012.40","url":null,"abstract":"The premature problem of Particle Swarm Optimization(PSO) leads the missing of the global optima and the failure of searching process. To solve this problem, the chaotic PSO based on sub-energy tunneling is proposed. This algorithm introduces the concept of sub-energy tunneling of TRUST algorithm to transform the objective function in optimization problem. And it uses the Logistic series to replace the random number in PSO. With maintaining the optimization properties of the original objective function, the speed of particles searching the optimization is accelerated. The difference and relationship between the sub-energy tunneling and traditional transform are analyzed. In the numerical experiment, the proposed algorithm and some PSOs based on function transform are compared. The results show that the PSO based on sub-energy tunneling has a higher convergence speed and it can improve the searching efficiency. So the chaotic PSO based on sub-energy tunneling is valid and effective.","PeriodicalId":183428,"journal":{"name":"International Joint Conference on Computational Sciences and Optimization","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122140265","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}
This paper gives a concept of filled function which is different from the that of traditional filled functions, and a class of generalized filled functions satisfying the new concept are presented. furthermore, the filled functions properties were discussed and point out the filled function in paper [6] is the special form of this generalized filled functions.
{"title":"Generalized Filled Function for Global Continuous Optimization Problems","authors":"Yanxia Niu, Hengjun Zhao","doi":"10.1109/CSO.2012.87","DOIUrl":"https://doi.org/10.1109/CSO.2012.87","url":null,"abstract":"This paper gives a concept of filled function which is different from the that of traditional filled functions, and a class of generalized filled functions satisfying the new concept are presented. furthermore, the filled functions properties were discussed and point out the filled function in paper [6] is the special form of this generalized filled functions.","PeriodicalId":183428,"journal":{"name":"International Joint Conference on Computational Sciences and Optimization","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126730958","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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