This paper aims at minimizing the total completion time for a single batch processing machine with non-identical job sizes. For this problem, each job has a corresponding processing time and size. The machine can process the jobs in batches as long as the total size of all the jobs in a batch does not exceed the machine capacity. The processing time of a batch is equal to the longest processing time among all the jobs in that batch. This problem is NP-hard and hence a chaotic ant colony optimization algorithm based on batch sequence (BCACO) is proposed. Random instances were used to test the effectiveness of the proposed approach. Computational results show that BCACO significantly outperforms other algorithms addressed in the literature.
{"title":"A Hybrid Ant Colony Optimization to Minimize the Total Completion Time on a Single Batch Processing Machine with Non-identical Job Sizes","authors":"Rui Xu, Hua-ping Chen, Jun-Hong Zhu, Hao Shao","doi":"10.1109/ICNC.2008.384","DOIUrl":"https://doi.org/10.1109/ICNC.2008.384","url":null,"abstract":"This paper aims at minimizing the total completion time for a single batch processing machine with non-identical job sizes. For this problem, each job has a corresponding processing time and size. The machine can process the jobs in batches as long as the total size of all the jobs in a batch does not exceed the machine capacity. The processing time of a batch is equal to the longest processing time among all the jobs in that batch. This problem is NP-hard and hence a chaotic ant colony optimization algorithm based on batch sequence (BCACO) is proposed. Random instances were used to test the effectiveness of the proposed approach. Computational results show that BCACO significantly outperforms other algorithms addressed in the literature.","PeriodicalId":6404,"journal":{"name":"2008 Fourth International Conference on Natural Computation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90872352","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}
Combining bottom-up and top-down attention influences, a novel region extraction model which based on object-accumulated visual attention mechanism is proposed in this paper. Compared with early research, the new approach brings in prior information at the proper time, updates scan path dynamically, needs less computational resources and reduces the probability to direct the attention to a less-meaning area. The application to search an airport target in remote sensing image was provided, through which the novel mechanism that how visual attention chose the area was described. Compared with another two region extraction models, experimental results confirm the effectiveness of the approach proposed in this paper.
{"title":"The Application of A Novel Target Region Extraction Model Based on Object-Accumulated Visual Attention Mechanism","authors":"Jie Xiao, C. Cai, Mingyue Ding, Chengping Zhou","doi":"10.1109/ICNC.2008.524","DOIUrl":"https://doi.org/10.1109/ICNC.2008.524","url":null,"abstract":"Combining bottom-up and top-down attention influences, a novel region extraction model which based on object-accumulated visual attention mechanism is proposed in this paper. Compared with early research, the new approach brings in prior information at the proper time, updates scan path dynamically, needs less computational resources and reduces the probability to direct the attention to a less-meaning area. The application to search an airport target in remote sensing image was provided, through which the novel mechanism that how visual attention chose the area was described. Compared with another two region extraction models, experimental results confirm the effectiveness of the approach proposed in this paper.","PeriodicalId":6404,"journal":{"name":"2008 Fourth International Conference on Natural Computation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90873329","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}
Many processes are involved in managing the supply chain to expedite the flow of information and materials. The Supply Chain Council developed a Supply Chain Operations Reference Model (SCOR) as a cross-industry reference model for supply chain management, which identifies five major supply chain process: plan, source, make, deliver, and return. One of the subprocesses in the source process is identifying suppliers. In modern management, a company tries to establish a long-term relationship with its supplier to ensure its stable source and therefore evaluating supplier has become even more critical than ever in gaining strategic advantage in supply chain management. In this paper, we going to propose a supplier evaluation model based on grey relational analysis and TOPSIS which have been extensively applied in various fields including decision making.
{"title":"Supplier Selection Problem: Integrating Grey Relational Analysis and TOPSIS","authors":"Hsuan-Shih Lee","doi":"10.1109/ICNC.2008.855","DOIUrl":"https://doi.org/10.1109/ICNC.2008.855","url":null,"abstract":"Many processes are involved in managing the supply chain to expedite the flow of information and materials. The Supply Chain Council developed a Supply Chain Operations Reference Model (SCOR) as a cross-industry reference model for supply chain management, which identifies five major supply chain process: plan, source, make, deliver, and return. One of the subprocesses in the source process is identifying suppliers. In modern management, a company tries to establish a long-term relationship with its supplier to ensure its stable source and therefore evaluating supplier has become even more critical than ever in gaining strategic advantage in supply chain management. In this paper, we going to propose a supplier evaluation model based on grey relational analysis and TOPSIS which have been extensively applied in various fields including decision making.","PeriodicalId":6404,"journal":{"name":"2008 Fourth International Conference on Natural Computation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89602711","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}
Jianrong Wang, Haifeng Zhao, Jianwei Du, Tianbiao Yu, Wanshan Wang
On analysis of the workshop management characteristics of discrete enterprises in networked manufacturing environment, an instruction scheduling management system was designed and developed based on the discrete Hopfield network model. While changing weight factors or thresholds of neural network under associative memory mode, a suitable model for job scheduling was designed, which will bring advantages of neural network into play. The scheduling results were analyzed with multi-objective optimization computing method. Then this paper presented the comparison of simulation results and actual scheduling data,which shown that neural network scheduling model tends to consider evaluation indicators comprehensively, and all indicators of the corresponding scheduling solution keep balance.
{"title":"Neural Network Model Based Job Scheduling and Its Implementation in Networked Manufacturing","authors":"Jianrong Wang, Haifeng Zhao, Jianwei Du, Tianbiao Yu, Wanshan Wang","doi":"10.1109/ICNC.2008.795","DOIUrl":"https://doi.org/10.1109/ICNC.2008.795","url":null,"abstract":"On analysis of the workshop management characteristics of discrete enterprises in networked manufacturing environment, an instruction scheduling management system was designed and developed based on the discrete Hopfield network model. While changing weight factors or thresholds of neural network under associative memory mode, a suitable model for job scheduling was designed, which will bring advantages of neural network into play. The scheduling results were analyzed with multi-objective optimization computing method. Then this paper presented the comparison of simulation results and actual scheduling data,which shown that neural network scheduling model tends to consider evaluation indicators comprehensively, and all indicators of the corresponding scheduling solution keep balance.","PeriodicalId":6404,"journal":{"name":"2008 Fourth International Conference on Natural Computation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89727687","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}
Z. Xiong, Yang Yang, Fu Chen, Xuemin Zhang, Ming Zeng
The grid technology enables large-scale sharing and collaboration use of networked resource. Using P2P technology, grid system can have better scalability and dynamic. OGSA (open grid service architecture) provides a framework for integrating P2P technology into grid system. However, grid resource aggregation is a key issue for P2P grid. In this paper, ant-based resource aggregation algorithm is proposed to aggregate grid resource in P2P grid environment. Theoretical analysis and simulations prove that ant-based resource aggregation algorithm in P2P grid can improve the performance of resource aggregation.
{"title":"Ant-Based Resource Aggregation in a P2P Grid","authors":"Z. Xiong, Yang Yang, Fu Chen, Xuemin Zhang, Ming Zeng","doi":"10.1109/ICNC.2008.691","DOIUrl":"https://doi.org/10.1109/ICNC.2008.691","url":null,"abstract":"The grid technology enables large-scale sharing and collaboration use of networked resource. Using P2P technology, grid system can have better scalability and dynamic. OGSA (open grid service architecture) provides a framework for integrating P2P technology into grid system. However, grid resource aggregation is a key issue for P2P grid. In this paper, ant-based resource aggregation algorithm is proposed to aggregate grid resource in P2P grid environment. Theoretical analysis and simulations prove that ant-based resource aggregation algorithm in P2P grid can improve the performance of resource aggregation.","PeriodicalId":6404,"journal":{"name":"2008 Fourth International Conference on Natural Computation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90286500","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 efficiently to obtain an approximate solution of the traveling salesman problem (TSP), extended changing crossover operators (ECXOs) which can substitute any crossover operator of genetic algorithms (GAs) and ant colony optimization (ACO) for another crossover operator at any time is proposed. In our study ECXO uses both of EX (or ACO) and EXX (edge exchange crossover) in early generations to create local optimum sub-paths, and it uses EAX (edge assembly crossover) to create a global optimum solution after generations. With EX or ACO any individual or any ant determines the next city he visits based on lengths of edges or tours' lengths deposited on edges as pheromone, and he generates local optimum paths. With EXX the generated path converges to a provisional optimal path. With EAX a parent exchanges his edges with another parent's ones reciprocally to create sub-cyclic paths, before restructuring a cyclic path by combining the sub-cyclic paths with making distances between them minimum. In this paper validity of ECXO is verified by C experiments using medium-sized problems such as pcb442, etc. in TSPLIB. From our C experiments, we can see that the above ECXO (EX (or ACO) (rarrEXX)rarrEAX) can find the best solution earlier than EAX, where EX, ACO and EXX deliver their offspring to EAX.
{"title":"A Methodology of Extended Changing Crossover Operators to Solve the Traveling Salesman Problem","authors":"R. Takahashi","doi":"10.1109/ICNC.2008.826","DOIUrl":"https://doi.org/10.1109/ICNC.2008.826","url":null,"abstract":"In order efficiently to obtain an approximate solution of the traveling salesman problem (TSP), extended changing crossover operators (ECXOs) which can substitute any crossover operator of genetic algorithms (GAs) and ant colony optimization (ACO) for another crossover operator at any time is proposed. In our study ECXO uses both of EX (or ACO) and EXX (edge exchange crossover) in early generations to create local optimum sub-paths, and it uses EAX (edge assembly crossover) to create a global optimum solution after generations. With EX or ACO any individual or any ant determines the next city he visits based on lengths of edges or tours' lengths deposited on edges as pheromone, and he generates local optimum paths. With EXX the generated path converges to a provisional optimal path. With EAX a parent exchanges his edges with another parent's ones reciprocally to create sub-cyclic paths, before restructuring a cyclic path by combining the sub-cyclic paths with making distances between them minimum. In this paper validity of ECXO is verified by C experiments using medium-sized problems such as pcb442, etc. in TSPLIB. From our C experiments, we can see that the above ECXO (EX (or ACO) (rarrEXX)rarrEAX) can find the best solution earlier than EAX, where EX, ACO and EXX deliver their offspring to EAX.","PeriodicalId":6404,"journal":{"name":"2008 Fourth International Conference on Natural Computation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90392633","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}
According to the diffusion approximation, we present a more biologically plausible so-called spike-rate perceptron based on IF model with renewal process inputs, which employs both first and second statistical representation, i.e. the means, variances and correlations of the synaptic input. We first identify the input-output relationship of the spike-rate model and apply an error minimization technique to train the model. We then show that it is possible to train these networks with a mathematically derived learning rule. We show through various examples that such perceptron, even a single neuron, is able to perform various complex non-linear tasks like the XOR problem. Here our perceptrons offer a significant advantage over classical models, in that they include both the mean and the variance of the input signal. Our ultimate purpose is to open up the possibility of carrying out a random computation in neuronal networks, by introducing second order statistics in computations.
{"title":"Spike-Rate Perceptrons","authors":"Xuyan Xiang, Yingchun Deng, Xiangqun Yang","doi":"10.1109/ICNC.2008.556","DOIUrl":"https://doi.org/10.1109/ICNC.2008.556","url":null,"abstract":"According to the diffusion approximation, we present a more biologically plausible so-called spike-rate perceptron based on IF model with renewal process inputs, which employs both first and second statistical representation, i.e. the means, variances and correlations of the synaptic input. We first identify the input-output relationship of the spike-rate model and apply an error minimization technique to train the model. We then show that it is possible to train these networks with a mathematically derived learning rule. We show through various examples that such perceptron, even a single neuron, is able to perform various complex non-linear tasks like the XOR problem. Here our perceptrons offer a significant advantage over classical models, in that they include both the mean and the variance of the input signal. Our ultimate purpose is to open up the possibility of carrying out a random computation in neuronal networks, by introducing second order statistics in computations.","PeriodicalId":6404,"journal":{"name":"2008 Fourth International Conference on Natural Computation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73537895","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 describes a genetic algorithm based approach to detect and predict high-impact events. While, these events occur infrequently, they are quite costly, meaning that they have a high-impact on the system key performance indicators. This approach is based on mining for these events and subsequences that are predictive of these high-impact events from historical data and then classifying these predictive patterns. The resulting mined patterns are subsequently used to make future prediction of occurrences. The approach uses a genetic algorithm for estimating the parameters for the mining process and for the prediction. This makes our approach robust as the parameters are optimized for best accuracy in classification. This approach was tested on high-impact events that occur in automotive manufacturing lines and it was found to be robust, highly accurate and with low probability of false alarms for prediction of future occurrences of such events.
{"title":"High-Impact Event Prediction by Temporal Data Mining through Genetic Algorithms","authors":"N. Srinivasa, Q. Jiang, L. Barajas","doi":"10.1109/ICNC.2008.761","DOIUrl":"https://doi.org/10.1109/ICNC.2008.761","url":null,"abstract":"This paper describes a genetic algorithm based approach to detect and predict high-impact events. While, these events occur infrequently, they are quite costly, meaning that they have a high-impact on the system key performance indicators. This approach is based on mining for these events and subsequences that are predictive of these high-impact events from historical data and then classifying these predictive patterns. The resulting mined patterns are subsequently used to make future prediction of occurrences. The approach uses a genetic algorithm for estimating the parameters for the mining process and for the prediction. This makes our approach robust as the parameters are optimized for best accuracy in classification. This approach was tested on high-impact events that occur in automotive manufacturing lines and it was found to be robust, highly accurate and with low probability of false alarms for prediction of future occurrences of such events.","PeriodicalId":6404,"journal":{"name":"2008 Fourth International Conference on Natural Computation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76556477","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}
Facial expression is an important communication method. Facial expression recognition has been studied in many application domains. In this paper, we study hidden Markov model (HMM) and K nearest neighbor (KNN) classifiers, and put forward a combined approach for facial expression recognition. The basic idea of this approach is to employ the HMM and KNN classifiers in a sequential way. First, the HMM classifier is used to calculate the probabilities of six expressions. From two most possible results of classification by HMM, the KNN classifier is used to make a final decision while the difference between the maximum probability and the second is less than the threshold obtained from HMM and training samples. The experiments show that the performance of this method exceeds that of solely HMM-based or KNN-based method.
{"title":"A Mixed Classifier Based on Combination of HMM and KNN","authors":"Qingmiao Wang, Shiguang Ju","doi":"10.1109/ICNC.2008.680","DOIUrl":"https://doi.org/10.1109/ICNC.2008.680","url":null,"abstract":"Facial expression is an important communication method. Facial expression recognition has been studied in many application domains. In this paper, we study hidden Markov model (HMM) and K nearest neighbor (KNN) classifiers, and put forward a combined approach for facial expression recognition. The basic idea of this approach is to employ the HMM and KNN classifiers in a sequential way. First, the HMM classifier is used to calculate the probabilities of six expressions. From two most possible results of classification by HMM, the KNN classifier is used to make a final decision while the difference between the maximum probability and the second is less than the threshold obtained from HMM and training samples. The experiments show that the performance of this method exceeds that of solely HMM-based or KNN-based method.","PeriodicalId":6404,"journal":{"name":"2008 Fourth International Conference on Natural Computation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76864272","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}
To the time-constrained workflow scheduling in grids, this paper proposes a new scheduling algorithm in terms of the finite-state continuous-time Markov process through selecting a resource combination scheme which has the lowest expenditure under the certain credit level of the resource reliability on the critical path in the DAG-based workflow. The simulation shows the validity of theory analysis.
{"title":"Grid Workflow Scheduling Based on the Resource Combination Reliability","authors":"Guozhong Tian, Jiong Yu","doi":"10.1109/ICNC.2008.234","DOIUrl":"https://doi.org/10.1109/ICNC.2008.234","url":null,"abstract":"To the time-constrained workflow scheduling in grids, this paper proposes a new scheduling algorithm in terms of the finite-state continuous-time Markov process through selecting a resource combination scheme which has the lowest expenditure under the certain credit level of the resource reliability on the critical path in the DAG-based workflow. The simulation shows the validity of theory analysis.","PeriodicalId":6404,"journal":{"name":"2008 Fourth International Conference on Natural Computation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78159049","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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