Considering that the vehicle routing problem （VRP） with many extended features is widely used in actual life, such as multi-depot, heterogeneous types of vehicles, customer service priority and time windows etc., a ...Considering that the vehicle routing problem （VRP） with many extended features is widely used in actual life, such as multi-depot, heterogeneous types of vehicles, customer service priority and time windows etc., a mathematical model for multi-depot heterogeneous vehicle routing problem with soft time windows （MDHVRPSTW） is established. An improved ant colony optimization （IACO） is proposed for solving this model. First, MDHVRPSTW is transferred into different groups according to the nearest principle, and then the initial route is constructed by the scanning algorithm （SA）. Secondly, genetic operators are introduced, and crossover probability and mutation probability are adaptively adjusted in order to improve the global search ability of the algorithm. Moreover, the smooth mechanism is used to improve the performance of the ant colony optimization （ACO）. Finally, the 3-opt strategy is used to improve the local search ability. The proposed IACO was tested on three new instances that were generated randomly. The experimental results show that IACO is superior to the other three existing algorithms in terms of convergence speed and solution quality. Thus, the proposed method is effective and feasible, and the proposed model is meaningful.展开更多
A hybrid approach using MLD (mixed logical dynamical) framework to handle infeasibility and constraint prioritization issues in MPC (model predictive control) based on input-output model is introduced. By expressing c...A hybrid approach using MLD (mixed logical dynamical) framework to handle infeasibility and constraint prioritization issues in MPC (model predictive control) based on input-output model is introduced. By expressing constraint priorities as propositional logics and by transforming the propositional logics into inequalities,the infeasibility and constraint prioritization issues are solved in the MPC. Constraints with higher priorities are met first, and then these with lower priorities are satisfied as much as possible. This new approach is illustrated in the control of a heavy oil fractionator-Shell column. The overall control performance has been significantly improved through the infeasibility and control priorities handling.展开更多
Since the complex impeller structure and the difficult remanufacturing process may easily cause advance remanufacturing or excessive use,an optimized design method of impeller and service mapping model was presented f...Since the complex impeller structure and the difficult remanufacturing process may easily cause advance remanufacturing or excessive use,an optimized design method of impeller and service mapping model was presented for its proactive remanufacturing with setting up to explore the best remanufacturing time point in this work.Considering a certain model of long distance pipeline compressor impeller with the Basquin equation and the design method of impeller,the mathematical relationship between the changes of structure and life of the impeller was established.And the service mapping model between the structure and life was set up and simulated by ANSYS software.Thus,the service mapping model was applied to feedback the original design for proactive remanufacturing.In this work,the best proactive remanufacturing time point of impeller was analyzed with the service mapping model,and the structural parameter values could be optimized at this time point.Meanwhile,in the results of this simulation,it proves that the impeller under this optimization performance could satisfy the impeller operating demands.Therefore,comparing with the traditional optimization design method,the remanufacturing optimized design based on the service mapping model is feasible in proactive remanufacturing for sustainable development.展开更多
In the past two decades, software aging has been studied by both academic and industry communities. Many scholars focused on analytical methods or time series to model software aging process. While machine learning ha...In the past two decades, software aging has been studied by both academic and industry communities. Many scholars focused on analytical methods or time series to model software aging process. While machine learning has been shown as a very promising technique in application to forecast software state: normal or aging. In this paper, we proposed a method which can give practice guide to forecast software aging using machine learning algorithm. Firstly, we collected data from a running commercial web server and preprocessed these data. Secondly, feature selection algorithm was applied to find a subset of model parameters set. Thirdly, time series model was used to predict values of selected parameters in advance. Fourthly, some machine learning algorithms were used to model software aging process and to predict software aging. Fifthly, we used sensitivity analysis to analyze how heavily outcomes changed following input variables change. In the last, we applied our method to an IIS web server. Through analysis of the experiment results, we find that our proposed method can predict software aging in the early stage of system development life cycle.展开更多
基金The National Natural Science Foundation of China(No.61074147)the Natural Science Foundation of Guangdong Province(No.S2011010005059)+2 种基金the Foundation of Enterprise-University-Research Institute Cooperation from Guangdong Province and Ministry of Education of China(No.2012B091000171,2011B090400460)the Science and Technology Program of Guangdong Province(No.2012B050600028)the Science and Technology Program of Huadu District,Guangzhou(No.HD14ZD001)
文摘Considering that the vehicle routing problem （VRP） with many extended features is widely used in actual life, such as multi-depot, heterogeneous types of vehicles, customer service priority and time windows etc., a mathematical model for multi-depot heterogeneous vehicle routing problem with soft time windows （MDHVRPSTW） is established. An improved ant colony optimization （IACO） is proposed for solving this model. First, MDHVRPSTW is transferred into different groups according to the nearest principle, and then the initial route is constructed by the scanning algorithm （SA）. Secondly, genetic operators are introduced, and crossover probability and mutation probability are adaptively adjusted in order to improve the global search ability of the algorithm. Moreover, the smooth mechanism is used to improve the performance of the ant colony optimization （ACO）. Finally, the 3-opt strategy is used to improve the local search ability. The proposed IACO was tested on three new instances that were generated randomly. The experimental results show that IACO is superior to the other three existing algorithms in terms of convergence speed and solution quality. Thus, the proposed method is effective and feasible, and the proposed model is meaningful.
基金Supported by the 973 Program (No. 2002CB312200)National High Tech. Project of China (863/CIMS 2004AA412050).
文摘A hybrid approach using MLD (mixed logical dynamical) framework to handle infeasibility and constraint prioritization issues in MPC (model predictive control) based on input-output model is introduced. By expressing constraint priorities as propositional logics and by transforming the propositional logics into inequalities,the infeasibility and constraint prioritization issues are solved in the MPC. Constraints with higher priorities are met first, and then these with lower priorities are satisfied as much as possible. This new approach is illustrated in the control of a heavy oil fractionator-Shell column. The overall control performance has been significantly improved through the infeasibility and control priorities handling.
基金Project(2011CB013406)supported by National Basic Research Program of ChinaProjects(51305119,51375133)supported by National Natural Science Foundation of China
文摘Since the complex impeller structure and the difficult remanufacturing process may easily cause advance remanufacturing or excessive use,an optimized design method of impeller and service mapping model was presented for its proactive remanufacturing with setting up to explore the best remanufacturing time point in this work.Considering a certain model of long distance pipeline compressor impeller with the Basquin equation and the design method of impeller,the mathematical relationship between the changes of structure and life of the impeller was established.And the service mapping model between the structure and life was set up and simulated by ANSYS software.Thus,the service mapping model was applied to feedback the original design for proactive remanufacturing.In this work,the best proactive remanufacturing time point of impeller was analyzed with the service mapping model,and the structural parameter values could be optimized at this time point.Meanwhile,in the results of this simulation,it proves that the impeller under this optimization performance could satisfy the impeller operating demands.Therefore,comparing with the traditional optimization design method,the remanufacturing optimized design based on the service mapping model is feasible in proactive remanufacturing for sustainable development.
基金supported by the grants from Natural Science Foundation of China(Project No.61375045)the joint astronomic fund of the national natural science foundation of China and Chinese Academic Sinica(Project No.U1531242)Beijing Natural Science Foundation(4142030)
文摘In the past two decades, software aging has been studied by both academic and industry communities. Many scholars focused on analytical methods or time series to model software aging process. While machine learning has been shown as a very promising technique in application to forecast software state: normal or aging. In this paper, we proposed a method which can give practice guide to forecast software aging using machine learning algorithm. Firstly, we collected data from a running commercial web server and preprocessed these data. Secondly, feature selection algorithm was applied to find a subset of model parameters set. Thirdly, time series model was used to predict values of selected parameters in advance. Fourthly, some machine learning algorithms were used to model software aging process and to predict software aging. Fifthly, we used sensitivity analysis to analyze how heavily outcomes changed following input variables change. In the last, we applied our method to an IIS web server. Through analysis of the experiment results, we find that our proposed method can predict software aging in the early stage of system development life cycle.
