Public sector decision-making typically involves complex problems that are riddled with competing performance objecttives and possess design requirements which are difficult to capture at the time that supporting deci...Public sector decision-making typically involves complex problems that are riddled with competing performance objecttives and possess design requirements which are difficult to capture at the time that supporting decision models are constructed. Environmental policy formulation can prove additionally complicated because the various system components often contain considerable stochastic uncertainty and frequently numerous stakeholders exist that hold completely incompatible perspectives. Consequently, there are invariably unmodelled performance design issues, not apparent at the time of the problem formulation, which can greatly impact the acceptability of any proposed solutions. While a mathematically optimal solution might provide the best solution to a modelled problem, normally this will not be the best solution to the underlying real problem. Therefore, in public environmental policy formulation, it is generally preferable to be able to create several quantifiably good alternatives that provide very different approaches and perspectives to the problem. This study shows how a computationally efficient simulation-driven optimization approach that com- bines evolutionary optimization with simulation can be used to generate multiple policy alternatives that satisfy required system criteria and are maximally different in decision space. The efficacy of this modelling-to-generate-alternatives method is specifically demonstrated on a municipal solid waste management facility expansion case.展开更多
The optimization method of a mathematical model and connected-pipe experimental technique for a test in altitude test facility (ATF) of a liquid fuel ramjet engine was researched.The optimization of the simple mathema...The optimization method of a mathematical model and connected-pipe experimental technique for a test in altitude test facility (ATF) of a liquid fuel ramjet engine was researched.The optimization of the simple mathematical model was divided into two steps.Firstly,using the test engine's geometry configuration size data,a preliminary adjustment was done.Secondly,using experimental test data,the components' experiential coefficients were modified appropriately.Emphasis was laid on the simulation technique of flight condition and parameters measurement method.The experimental technique was applied to a ramjet ATF test successfully.The comparison results show that the optimized-model has higher precision and the nozzle gross thrust difference drops from 12% to about 4%.展开更多
The methodology for optimization-oriented computer simulation and animationis proposed. The paper considere how to implement optimization-orientedsimulation throush the simulation activities in an attempt to intesrate...The methodology for optimization-oriented computer simulation and animationis proposed. The paper considere how to implement optimization-orientedsimulation throush the simulation activities in an attempt to intesrate animatedsimulation with optimization idea. It also deals with the application of multiple-objective optimisation in simulation study. Furthermore, the principles forevaluating and obtaining the optimum design and factor level combination of asimulated system are presented with respect to the underlying rationale.Inaddition,the approach for optimication objectives driven simulation analysis isexamined .展开更多
This paper investigates the dynamic design methodology of mountain bikes with rear suspension. Firstly, a multi-rigid body dynamic model of rider and mountain bike coupled system is constructed. The rider model includ...This paper investigates the dynamic design methodology of mountain bikes with rear suspension. Firstly, a multi-rigid body dynamic model of rider and mountain bike coupled system is constructed. The rider model includes 19 skeletons, 18 joints and 118 main muscles. Secondly, to validate the feasibility of the model, an experiment test is designed to reflect the real cycling status. Finally, aiming at enhancing the performance of the rider vibration comfort, the scale parameters of rear suspension are optimized with computer simulation and uniform design. The mathematical model in the vibration performance and the design variables is constructed with regression analysis. The result shows that when the length of side link is 90 mm, the length of connected rod is 336.115 1 mm and the included angle between absorber and side link is 60°, the mountain bike has better vibration comfort. This study and relevant conclusions are of practical importance to the design of the mountain bike＇s rear suspension system.展开更多
With market competition becoming fiercer,enterprises must update their products by constantly assimilating new big data knowledge and private knowledge to maintain their market shares at different time points in the b...With market competition becoming fiercer,enterprises must update their products by constantly assimilating new big data knowledge and private knowledge to maintain their market shares at different time points in the big data environment.Typically,there is mutual influence between each knowledge transfer if the time interval is not too long.It is necessary to study the problem of continuous knowledge transfer in the big data environment.Based on research on one-time knowledge transfer,a model of continuous knowledge transfer is presented,which can consider the interaction between knowledge transfer and determine the optimal knowledge transfer time at different time points in the big data environment.Simulation experiments were performed by adjusting several parameters.The experimental results verified the model’s validity and facilitated conclusions regarding their practical application values.The experimental results can provide more effective decisions for enterprises that must carry out continuous knowledge transfer in the big data environment.展开更多
文摘Public sector decision-making typically involves complex problems that are riddled with competing performance objecttives and possess design requirements which are difficult to capture at the time that supporting decision models are constructed. Environmental policy formulation can prove additionally complicated because the various system components often contain considerable stochastic uncertainty and frequently numerous stakeholders exist that hold completely incompatible perspectives. Consequently, there are invariably unmodelled performance design issues, not apparent at the time of the problem formulation, which can greatly impact the acceptability of any proposed solutions. While a mathematically optimal solution might provide the best solution to a modelled problem, normally this will not be the best solution to the underlying real problem. Therefore, in public environmental policy formulation, it is generally preferable to be able to create several quantifiably good alternatives that provide very different approaches and perspectives to the problem. This study shows how a computationally efficient simulation-driven optimization approach that com- bines evolutionary optimization with simulation can be used to generate multiple policy alternatives that satisfy required system criteria and are maximally different in decision space. The efficacy of this modelling-to-generate-alternatives method is specifically demonstrated on a municipal solid waste management facility expansion case.
文摘The optimization method of a mathematical model and connected-pipe experimental technique for a test in altitude test facility (ATF) of a liquid fuel ramjet engine was researched.The optimization of the simple mathematical model was divided into two steps.Firstly,using the test engine's geometry configuration size data,a preliminary adjustment was done.Secondly,using experimental test data,the components' experiential coefficients were modified appropriately.Emphasis was laid on the simulation technique of flight condition and parameters measurement method.The experimental technique was applied to a ramjet ATF test successfully.The comparison results show that the optimized-model has higher precision and the nozzle gross thrust difference drops from 12% to about 4%.
文摘The methodology for optimization-oriented computer simulation and animationis proposed. The paper considere how to implement optimization-orientedsimulation throush the simulation activities in an attempt to intesrate animatedsimulation with optimization idea. It also deals with the application of multiple-objective optimisation in simulation study. Furthermore, the principles forevaluating and obtaining the optimum design and factor level combination of asimulated system are presented with respect to the underlying rationale.Inaddition,the approach for optimication objectives driven simulation analysis isexamined .
基金supported by Tianjin Municipal Science and Technology Development Project of China (Grant No. 043186211)Tianjin Municipal Key Laboratory of Advanced Manufacturing Technology and Equipment of Tianjin University of China
文摘This paper investigates the dynamic design methodology of mountain bikes with rear suspension. Firstly, a multi-rigid body dynamic model of rider and mountain bike coupled system is constructed. The rider model includes 19 skeletons, 18 joints and 118 main muscles. Secondly, to validate the feasibility of the model, an experiment test is designed to reflect the real cycling status. Finally, aiming at enhancing the performance of the rider vibration comfort, the scale parameters of rear suspension are optimized with computer simulation and uniform design. The mathematical model in the vibration performance and the design variables is constructed with regression analysis. The result shows that when the length of side link is 90 mm, the length of connected rod is 336.115 1 mm and the included angle between absorber and side link is 60°, the mountain bike has better vibration comfort. This study and relevant conclusions are of practical importance to the design of the mountain bike＇s rear suspension system.
基金supported by the National Natural Science Foundation of China(Grant No.71704016,71331008)the Natural Science Foundation of Hunan Province(Grant No.2017JJ2267)+1 种基金Key Projects of Chinese Ministry of Education(17JZD022)the Project of China Scholarship Council for Overseas Studies(201208430233,201508430121),which are acknowledged.
文摘With market competition becoming fiercer,enterprises must update their products by constantly assimilating new big data knowledge and private knowledge to maintain their market shares at different time points in the big data environment.Typically,there is mutual influence between each knowledge transfer if the time interval is not too long.It is necessary to study the problem of continuous knowledge transfer in the big data environment.Based on research on one-time knowledge transfer,a model of continuous knowledge transfer is presented,which can consider the interaction between knowledge transfer and determine the optimal knowledge transfer time at different time points in the big data environment.Simulation experiments were performed by adjusting several parameters.The experimental results verified the model’s validity and facilitated conclusions regarding their practical application values.The experimental results can provide more effective decisions for enterprises that must carry out continuous knowledge transfer in the big data environment.
