In order to solve the complex optimization problem dealing with uncertain phenomenon effectively, this paper presents a probability simulation optimization approach using orthogonal genetic algorithm. This approach sy...In order to solve the complex optimization problem dealing with uncertain phenomenon effectively, this paper presents a probability simulation optimization approach using orthogonal genetic algorithm. This approach synthesizes the computer simulation technology, orthogonal genetic algorithm and statistical test method faultlessly, which can solve complex optimization problem effectively. In this paper, the author gives the correlative conception of probability simulation optimization and describes the probability simulation optimization approach using orthogonal genetic algorithm in detail. Theoretically speaking, it has a strong rationality and maneuverability that can apply probability method in solving the complex optimization problems with uncertain phenomenon. In demonstration, the optimization performance of this method is better than other traditional methods. Simulation resuh suggests that the approach referred to this paper is feasible, correct and valid.展开更多
Optimizing train movement has a great significance for railway traffic. In this paper, based on the optimal velocity car-following model, we propose a new simulation model for optimizing train movement in railway traf...Optimizing train movement has a great significance for railway traffic. In this paper, based on the optimal velocity car-following model, we propose a new simulation model for optimizing train movement in railway traffic. Here a kind of single-track railway is considered. Our aim is to reduce the energy consumption of train movement and ensure the train being on time by controlling the velocity curve of train movement. The simulation results indicate that the proposed model is effective for optimizing train movement. In addition, some major characteristics of train movement can be well captured. This method provides a new way to optimize train movement in railway traffic.展开更多
Predictive control has recently received much attention from researchers. However a challenging problem to be solved is how to tune the parameters of the predictive controller. So far, only few guidelines related to t...Predictive control has recently received much attention from researchers. However a challenging problem to be solved is how to tune the parameters of the predictive controller. So far, only few guidelines related to tuning of the parameters of predictive controllers have been provided in literature. In practice, these parameters are generally off-line determined by the designers' experience. From the point of view of process control, it is difficult to find out the optimal parameters for the control system based on a single quadratic performance index, which is used in the standard predictive control algorithm. The fuzzy decision-making function is investigated in this paper. Firstly, M control actions are achieved by unconstrained predictive control algorithm, and fuzzy goals and fuzzy constraints are then calculated and the global satisfaction degree is obtained by fuzzy inference. Moreover, the weighting coefficient λ in the cost function is tuned using simulation optimization according to the fuzzy criteria.展开更多
As the take-off of China’s macro economy,as well as the rapid development of infrastructure construction,real estate industry,and highway logistics transportation industry,the demand for heavy vehicles is increasing ...As the take-off of China’s macro economy,as well as the rapid development of infrastructure construction,real estate industry,and highway logistics transportation industry,the demand for heavy vehicles is increasing rapidly,the competition is becoming increasingly fierce,and the digital transformation of the production line is imminent.As one of themost important components of heavy vehicles,the transmission front andmiddle case assembly lines have a high degree of automation,which can be used as a pilot for the digital transformation of production.To ensure the visualization of digital twins(DT),consistent control logic,and real-time data interaction,this paper proposes an experimental digital twin modeling method for the transmission front and middle case assembly line.Firstly,theDT-based systemarchitecture is designed,and theDT model is created by constructing the visualization model,logic model,and data model of the assembly line.Then,a simulation experiment is carried out in a virtual space to analyze the existing problems in the current assembly line.Eventually,some improvement strategies are proposed and the effectiveness is verified by a new simulation experiment.展开更多
This special issue focuses on simulation optimization(SO),which combines stochastic simulation with optimization techniques to address complex decisionmaking problems under uncertainty.SO has gained increasing importa...This special issue focuses on simulation optimization(SO),which combines stochastic simulation with optimization techniques to address complex decisionmaking problems under uncertainty.SO has gained increasing importance in areas such as transportation,supply chain and manufacturing,providing solutions where traditional analytical methods may fail.Recent advances in computing,data analytics,and artificial intelligence have significantly enhanced the efficiency and capability of SO methods,enabling the development of innovative techniques.This special issue aims to highlight recent theoretical and practical advancements in SO,showcasing its potential to solve real-world problems and inspiring further research and application in this dynamic field.展开更多
This study considers a problem of coordinating production,transportation and sales in a multi-echelon supply chain network.A simulation model is built to generate the random customer demands at different locations,whi...This study considers a problem of coordinating production,transportation and sales in a multi-echelon supply chain network.A simulation model is built to generate the random customer demands at different locations,which are affected by a marketing strategy.Customer demands need to be satisfied by the supply chain through production,transportation and distribution.The optimization problem for coordination of production,trans-portation and distribution is first formulated as a linear programming with demands as input parameters in the constraint.Our objective is to maximize the expectation of the optimal profit of the supply chain given random demands by selecting an optimal marketing strategy.A simulation optimization technique is proposed to con-trol the generation of random demands and solve the linear programming for efficiently learning the optimal marketing strategy.Numerical results show that our method can significantly improve the expected profit of the supply chain and reduce the computational burden of solving linear programming for achieving a given level of probability of correct selection of the optimal marketing strategy.Furthermore,we extend the optimization problem to a mixed integer programming and also demonstrate the computational efficiency of our proposed method.展开更多
Simulation optimization is a rapidly growing research field,fueled by advances in computational technology.These advances have made it possible to solve complex stochastic optimization problems through simulation.Whil...Simulation optimization is a rapidly growing research field,fueled by advances in computational technology.These advances have made it possible to solve complex stochastic optimization problems through simulation.While most published articles focus on single-objective optimization,multi-objective optimization is gaining prominence,allowing the approach of real-world problems that present multiple,conflicting objectives.In this context,the objective of this article was to conduct a systematic literature review to identify articles that present solution methods for Multi-Objective Simulation Optimization(MOSO)problems.The focus was on practical optimization applications in conjunction with Discrete Event Simulation(DES)models,aiming to identify the main aspects of the problems addressed,the methods used,and research opportunities,contributing to future projects.By exploring the characteristics of MOSO problems associated with DES and the applied solution methods,this article innovatively presents a guide to help professionals improve their decision-making processes and assist researchers in developing new research.展开更多
The inpatient bed allocation that allows beds shared among different departments is an important and challenging problem for a healthcare system. When the objective function(s) and (some) constraints need to be estima...The inpatient bed allocation that allows beds shared among different departments is an important and challenging problem for a healthcare system. When the objective function(s) and (some) constraints need to be estimated via expensive and noisy stochastic simulation, a simulation optimization algorithm is required to solve this problem. In literature, there is a heuristic algorithm highly customized for one specific inpatient bed allocation problem, and it performs quite well on that problem. However, its lack of theoretical convergence and high specialization may not give practitioners enough confidence to apply it on real inpatient bed allocation problems. To mitigate such issues, this paper proposes to use the empirical stochastic branch-and-bound (ESB&B) algorithm, which is theoretically convergent and suitable for relatively general problems. A modest improvement for the original ESB&B algorithm is made and how to adapt the ESB&B algorithm to inpatient bed allocation problems is presented. Numerical experiments reveal the generality and fairly satisfying performance of the ESB&B algorithm, and the superiority of the improved ESB&B algorithm over the original one.展开更多
Large-scale simulation optimization(SO)problems encompass both large-scale ranking-and-selection problems and high-dimensional discrete or continuous SO problems,presenting significant challenges to existing SO theori...Large-scale simulation optimization(SO)problems encompass both large-scale ranking-and-selection problems and high-dimensional discrete or continuous SO problems,presenting significant challenges to existing SO theories and algorithms.This paper begins by providing illustrative examples that highlight the differences between large-scale SO problems and those of a more moderate scale.Subsequently,it reviews several widely employed techniques for addressing large-scale SOproblems,such as divide-and-conquer,dimension reduction,and gradient-based algorithms.Additionally,the paper examines parallelization techniques leveraging widely accessible parallel computing environments to facilitate the resolution of large-scale SO problems.展开更多
In response to the deficiencies of commonly used optimization methods for assembly lines,a production demand-oriented optimization method for assembly lines is proposed.Taking a certain compressor assembly line as an ...In response to the deficiencies of commonly used optimization methods for assembly lines,a production demand-oriented optimization method for assembly lines is proposed.Taking a certain compressor assembly line as an example,the production rhythm and the number of workstations are calculated based on production requirements and working systems.With assembly rhythm and smoothing index as optimization goals,an improved particle swarm optimization algorithm is employed for process allocation.Subsequently,Flexsim simulation is used to analyze the assembly line.The final results show that after optimization using the improved particle swarm algorithm,the assembly line balance rate increased from 71.1%to 85.9%,and the assembly line smoothing index decreased from 47.4 to 29.8,significantly enhancing assembly efficiency.This demonstrates the effectiveness of the proposed optimization method for the assembly line and provides a reference for other products in the same industry.展开更多
We present a novel system productivity simulation and optimization modeling framework in which equipment availability is a variable in the expected productivity function of the system. The framework is used for alloca...We present a novel system productivity simulation and optimization modeling framework in which equipment availability is a variable in the expected productivity function of the system. The framework is used for allocating trucks by route according to their operating performances in a truck-shovel system of an open-pit mine, so as to maximize the overall productivity of the fleet. We implement the framework in an originally designed and specifically developed simulator-optimizer software tool. We make an application on a real open-pit mine case study taking into account the stochasticity of the equipment behavior and environment. The total system production values obtained with and without considering the equipment reliability, availability and maintainability (RAM) characteristics are compared. We show that by taking into account the truck and shovel RAM aspects, we can maximize the total production of the system and obtain specific information on the production availability and productivity of its components.展开更多
With the aim of visualizing the real-time simulation calculation of water delivery system (WDS), a structural drawing-oriented (SDO) simulation technique was presented, and applied to Zhangjiuhe Diversion Project, whi...With the aim of visualizing the real-time simulation calculation of water delivery system (WDS), a structural drawing-oriented (SDO) simulation technique was presented, and applied to Zhangjiuhe Diversion Project, which is a long-distance water delivery system constructed for draw- ing water from the Zhangjiuhe River to Kunming city. Taking SIMULINK software as simulating plat-form, the technique established a visual dynamic simulation model for the system. The simulation procedure of the system was simplified,and the efficiency of modeling was also enhanced according to the modularization and reutilization of the simulation program. Furthermore, a self-optimization model was presented. Based on the digital simulation models, the on line controlled optimization link was added, and the input data can be continually optimized according to the feedback information of simulating output. The system was thus optimized automatically. Built upon MATLAB software, simulation optimization of the Zhangjiuhe Diversion Project was achieved, which provides a new way for the research of optimal operation of WDS.展开更多
With the advance of new computational technology,stochastic systems simulation and optimization has become increasingly a popular subject in both academic research and industrial applications.This paper presents some ...With the advance of new computational technology,stochastic systems simulation and optimization has become increasingly a popular subject in both academic research and industrial applications.This paper presents some of recent developments about the problem of optimizing a performance function from a simulation model.We begin by classifying different types of problems and then provide an overview of the major approaches,followed by a more in-depth presentation of two specific areas:optimal computing budget allocation and the nested partitions method.展开更多
Boiling heat transfer and the controllability of the thermal load of the cylinder head were studied.The thermodynamic phase change characteristics of the cylinder head coolant were considered and the mass,momentumand ...Boiling heat transfer and the controllability of the thermal load of the cylinder head were studied.The thermodynamic phase change characteristics of the cylinder head coolant were considered and the mass,momentumand energy transfers between two phases were calculated with the interface transfer submodels by using the computational fluid dynamics software CFX. Results showed that compared with the single-phase flow without considering the boiling heat transfer,the sub-cooled boiling heat transfer of the cylinder head was greatly increased. According to the results of the numerical simulation,an optimized structure of the water jacket was proposed. Finally,temperature and velocity of coolant,diameter of flow passage and mean bubble diameter that influences sub-cooled boiling were studied using the orthogonal experiment method.展开更多
Network-based manufacturing is a kind of distributed system, which enables manufacturers to finish production tasks as well as to grasp the opportunities in the market, even if manufacturing resources are insufficient...Network-based manufacturing is a kind of distributed system, which enables manufacturers to finish production tasks as well as to grasp the opportunities in the market, even if manufacturing resources are insufficient. One of the main problems in network-based manufacturing is the allocation of resources and the assignment of tasks rationally, according to flexible resource distribution. The mapping rules and relations between production techniques and resources are proposed, followed by the definition of the resource unit. Ultimately, the genetic programming method for the optimization of the manufacturing system is put forward. A set of software for the optimization system of simulation process using genetic programming techniques has been developed, and the problems of manufacturing resource planning in network-based manufacturing are solved with the simulation of optimizing methods by genetic programming. The optimum proposal of hardware planning, selection of company and scheduling will be obtained in theory to help company managers in scientific decision-making.展开更多
As a major configuration of membrane elements,multi-channel porous inorganic membrane tubes were studied by means of theoretical analysis and simulation.Configuration optimization of a cylindrical 37-channel porous in...As a major configuration of membrane elements,multi-channel porous inorganic membrane tubes were studied by means of theoretical analysis and simulation.Configuration optimization of a cylindrical 37-channel porous inorganic membrane tube was studied by increasing membrane filtration area and increasing permeation efficiency of inner channels.An optimal ratio of the channel diameter to the inter-channel distance was proposed so as to increase the total membrane filtration area of the membrane tube.The three-dimensional computational fluid dynamics(CFD) simulation was conducted to study the cross-flow permeation flow of pure water in the 37-channel ceramic membrane tube.A model combining Navier–Stokes equation with Darcy's law and the porous jump boundary conditions was applied.The relationship between permeation efficiency and channel locations,and the method for increasing the permeation efficiency of inner channels were proposed.Some novel multichannel membrane configurations with more permeate side channels were put forward and evaluated.展开更多
A new vapor distributor based on the Coanda effect is added to the Dividing Wall column(DWC),and the multiphase flow simulation is performed using ANSYS Fluent by this model.The results show that with the addition of ...A new vapor distributor based on the Coanda effect is added to the Dividing Wall column(DWC),and the multiphase flow simulation is performed using ANSYS Fluent by this model.The results show that with the addition of the liquid phase,the new vapor distributor still follows the Coanda effect.Hereby,the vapor is ejected from the slits of the distributor to take away the surrounding vapor,and a negative pressure is formed under the distributor,so as to achieve the purpose of regulating Rv.Analogously to the working principle of vapor distributor,a certain amount of vapor is drawn out from a position of prefractionator,which is equivalent to the vapor ejected by the distributor.The same amount of vapor is fed into the main column,which corresponds to the gas phase at the inlet of the distributor.The Rv is adjusted by changing the speed of the input or output vapor.Simulation results show that adding this control mechanism on the basis of temperature or concentration control structure can better achieve the effect of vapor distribution.展开更多
In this paper, we propose an ordinal optimization based simulation optimization algorithm to determine a target distribution of bicycles for a bicycle sharing network to minimize an expected cost. The proposed algorit...In this paper, we propose an ordinal optimization based simulation optimization algorithm to determine a target distribution of bicycles for a bicycle sharing network to minimize an expected cost. The proposed algorithm consists of two stages. The first stage is using GA （genetic algorithm） assisted by a surrogate model to select an estimated good enough subset of solutions. The second stage is to identify the best solution among the solutions obtained from stage one using optimal computing budget allocation technique. We have tested the proposed algorithm on a bicycle sharing network and compared the test results with those obtained by the GA with exact model. The test results demonstrate that the proposed algorithm can obtain a good enough solution within reasonable computing time and outperforms the comparing method.展开更多
The research addresses the prevalence of gassy soil, containing methane (CH4), within the soil particles of southeast coastal areas of China, such as the Quaternary deposit in the Hangzhou Bay area. This soil exhibits...The research addresses the prevalence of gassy soil, containing methane (CH4), within the soil particles of southeast coastal areas of China, such as the Quaternary deposit in the Hangzhou Bay area. This soil exhibits spatial variability in the distribution of gas pressure, posing a potential threat of engineering disasters, including fire outbreaks and blasting, during the construction of underground projects. Consequently, it is crucial to assess the risk state of gas pressure, involving accurate identification and reduction of associated uncertainty, through site investigation. This is indispensable prior to the commencement of underground projects. However, during the site investigation stage, the random field parameters that quantify the spatial variability distribution of gas pressure (e.g., mean value, standard deviations, and scale of fluctuation) are unknown, introducing corresponding statistical uncertainty. Therefore, the most significant consideration for planning site investigation from an engineering perspective involves determining the risk state of gas pressure while considering the statistical uncertainty of these random field parameters. This consideration heavily relies on the engineering experience gained from current site investigation practices. To address this challenge, the study introduces a probabilistic site investigation optimization method designed for planning the site investigation scheme for gassy soils, including determining the number and locations of boreholes. The method is based on the expected state-identification probability, representing the probability of identifying the risk state of gas pressure, and takes into account the statistical uncertainty of random field parameters. The proposed method aims to determine an optimal investigation scheme before conducting the site investigation, leveraging prior knowledge. This optimal scheme is identified using Subset Simulation Optimization (SSO) in the space of candidate site investigations, maximizing the value of the expected state-identification probability at the minimal value point. Finally, the paper illustrates the proposed approach through a case study.展开更多
The current Whale Optimization Algorithm(WOA)has several drawbacks,such as slow convergence,low solution accuracy and easy to fall into the local optimal solution.To overcome these drawbacks,an improved Whale Optimiza...The current Whale Optimization Algorithm(WOA)has several drawbacks,such as slow convergence,low solution accuracy and easy to fall into the local optimal solution.To overcome these drawbacks,an improved Whale Optimization Algorithm(IWOA)is proposed in this study.IWOA can enhance the global search capability by two measures.First,the crossover and mutation operations in Differential Evolutionary algorithm(DE)are combined with the whale optimization algorithm.Second,the cloud adaptive inertia weight is introduced in the position update phase of WOA to divide the population into two subgroups,so as to balance the global search ability and local development ability.ANSYS and Matlab are used to establish the structure model.To demonstrate the application of the IWOA,truss structural optimizations on 52-bar plane truss and 25-bar space truss were performed,and the results were are compared with that obtained by other optimization algorithm.It is verified that,compared with WOA,the IWOA has higher efficiency,fast convergence speed,better solution accuracy and stability.So IWOA can be used in the optimization design of large truss structures.展开更多
基金Supported by the National Natural Science Foundation of China(70272002) .
文摘In order to solve the complex optimization problem dealing with uncertain phenomenon effectively, this paper presents a probability simulation optimization approach using orthogonal genetic algorithm. This approach synthesizes the computer simulation technology, orthogonal genetic algorithm and statistical test method faultlessly, which can solve complex optimization problem effectively. In this paper, the author gives the correlative conception of probability simulation optimization and describes the probability simulation optimization approach using orthogonal genetic algorithm in detail. Theoretically speaking, it has a strong rationality and maneuverability that can apply probability method in solving the complex optimization problems with uncertain phenomenon. In demonstration, the optimization performance of this method is better than other traditional methods. Simulation resuh suggests that the approach referred to this paper is feasible, correct and valid.
基金Project supported by the National High Technology Research and Development Program of China (Grant No. 2011AA110502)the National Natural Science Foundation of China (Grant No. 71271022)
文摘Optimizing train movement has a great significance for railway traffic. In this paper, based on the optimal velocity car-following model, we propose a new simulation model for optimizing train movement in railway traffic. Here a kind of single-track railway is considered. Our aim is to reduce the energy consumption of train movement and ensure the train being on time by controlling the velocity curve of train movement. The simulation results indicate that the proposed model is effective for optimizing train movement. In addition, some major characteristics of train movement can be well captured. This method provides a new way to optimize train movement in railway traffic.
文摘Predictive control has recently received much attention from researchers. However a challenging problem to be solved is how to tune the parameters of the predictive controller. So far, only few guidelines related to tuning of the parameters of predictive controllers have been provided in literature. In practice, these parameters are generally off-line determined by the designers' experience. From the point of view of process control, it is difficult to find out the optimal parameters for the control system based on a single quadratic performance index, which is used in the standard predictive control algorithm. The fuzzy decision-making function is investigated in this paper. Firstly, M control actions are achieved by unconstrained predictive control algorithm, and fuzzy goals and fuzzy constraints are then calculated and the global satisfaction degree is obtained by fuzzy inference. Moreover, the weighting coefficient λ in the cost function is tuned using simulation optimization according to the fuzzy criteria.
基金supported by China National Heavy Duty Truck Group Co.,Ltd.(Grant No.YF03221048P)the Shanghai Municipal Bureau of Market Supervision and Administration(Grant No.2022-35)New Young TeachersResearch Start-Up Foundation of Shanghai Jiao Tong University(Grant No.22X010503668).
文摘As the take-off of China’s macro economy,as well as the rapid development of infrastructure construction,real estate industry,and highway logistics transportation industry,the demand for heavy vehicles is increasing rapidly,the competition is becoming increasingly fierce,and the digital transformation of the production line is imminent.As one of themost important components of heavy vehicles,the transmission front andmiddle case assembly lines have a high degree of automation,which can be used as a pilot for the digital transformation of production.To ensure the visualization of digital twins(DT),consistent control logic,and real-time data interaction,this paper proposes an experimental digital twin modeling method for the transmission front and middle case assembly line.Firstly,theDT-based systemarchitecture is designed,and theDT model is created by constructing the visualization model,logic model,and data model of the assembly line.Then,a simulation experiment is carried out in a virtual space to analyze the existing problems in the current assembly line.Eventually,some improvement strategies are proposed and the effectiveness is verified by a new simulation experiment.
文摘This special issue focuses on simulation optimization(SO),which combines stochastic simulation with optimization techniques to address complex decisionmaking problems under uncertainty.SO has gained increasing importance in areas such as transportation,supply chain and manufacturing,providing solutions where traditional analytical methods may fail.Recent advances in computing,data analytics,and artificial intelligence have significantly enhanced the efficiency and capability of SO methods,enabling the development of innovative techniques.This special issue aims to highlight recent theoretical and practical advancements in SO,showcasing its potential to solve real-world problems and inspiring further research and application in this dynamic field.
基金supported in part by the National Natural Science Foundation of China(72250065,72022001,71901003).
文摘This study considers a problem of coordinating production,transportation and sales in a multi-echelon supply chain network.A simulation model is built to generate the random customer demands at different locations,which are affected by a marketing strategy.Customer demands need to be satisfied by the supply chain through production,transportation and distribution.The optimization problem for coordination of production,trans-portation and distribution is first formulated as a linear programming with demands as input parameters in the constraint.Our objective is to maximize the expectation of the optimal profit of the supply chain given random demands by selecting an optimal marketing strategy.A simulation optimization technique is proposed to con-trol the generation of random demands and solve the linear programming for efficiently learning the optimal marketing strategy.Numerical results show that our method can significantly improve the expected profit of the supply chain and reduce the computational burden of solving linear programming for achieving a given level of probability of correct selection of the optimal marketing strategy.Furthermore,we extend the optimization problem to a mixed integer programming and also demonstrate the computational efficiency of our proposed method.
文摘Simulation optimization is a rapidly growing research field,fueled by advances in computational technology.These advances have made it possible to solve complex stochastic optimization problems through simulation.While most published articles focus on single-objective optimization,multi-objective optimization is gaining prominence,allowing the approach of real-world problems that present multiple,conflicting objectives.In this context,the objective of this article was to conduct a systematic literature review to identify articles that present solution methods for Multi-Objective Simulation Optimization(MOSO)problems.The focus was on practical optimization applications in conjunction with Discrete Event Simulation(DES)models,aiming to identify the main aspects of the problems addressed,the methods used,and research opportunities,contributing to future projects.By exploring the characteristics of MOSO problems associated with DES and the applied solution methods,this article innovatively presents a guide to help professionals improve their decision-making processes and assist researchers in developing new research.
基金supported in part by the National Natural Science Foundation of China under Grant Nos.72031006,72031007,and 72394375.
文摘The inpatient bed allocation that allows beds shared among different departments is an important and challenging problem for a healthcare system. When the objective function(s) and (some) constraints need to be estimated via expensive and noisy stochastic simulation, a simulation optimization algorithm is required to solve this problem. In literature, there is a heuristic algorithm highly customized for one specific inpatient bed allocation problem, and it performs quite well on that problem. However, its lack of theoretical convergence and high specialization may not give practitioners enough confidence to apply it on real inpatient bed allocation problems. To mitigate such issues, this paper proposes to use the empirical stochastic branch-and-bound (ESB&B) algorithm, which is theoretically convergent and suitable for relatively general problems. A modest improvement for the original ESB&B algorithm is made and how to adapt the ESB&B algorithm to inpatient bed allocation problems is presented. Numerical experiments reveal the generality and fairly satisfying performance of the ESB&B algorithm, and the superiority of the improved ESB&B algorithm over the original one.
基金supported by the National Natural Science Foundation of China(Nos.72071146,72091211,72293562,and 72031006).
文摘Large-scale simulation optimization(SO)problems encompass both large-scale ranking-and-selection problems and high-dimensional discrete or continuous SO problems,presenting significant challenges to existing SO theories and algorithms.This paper begins by providing illustrative examples that highlight the differences between large-scale SO problems and those of a more moderate scale.Subsequently,it reviews several widely employed techniques for addressing large-scale SOproblems,such as divide-and-conquer,dimension reduction,and gradient-based algorithms.Additionally,the paper examines parallelization techniques leveraging widely accessible parallel computing environments to facilitate the resolution of large-scale SO problems.
文摘In response to the deficiencies of commonly used optimization methods for assembly lines,a production demand-oriented optimization method for assembly lines is proposed.Taking a certain compressor assembly line as an example,the production rhythm and the number of workstations are calculated based on production requirements and working systems.With assembly rhythm and smoothing index as optimization goals,an improved particle swarm optimization algorithm is employed for process allocation.Subsequently,Flexsim simulation is used to analyze the assembly line.The final results show that after optimization using the improved particle swarm algorithm,the assembly line balance rate increased from 71.1%to 85.9%,and the assembly line smoothing index decreased from 47.4 to 29.8,significantly enhancing assembly efficiency.This demonstrates the effectiveness of the proposed optimization method for the assembly line and provides a reference for other products in the same industry.
文摘We present a novel system productivity simulation and optimization modeling framework in which equipment availability is a variable in the expected productivity function of the system. The framework is used for allocating trucks by route according to their operating performances in a truck-shovel system of an open-pit mine, so as to maximize the overall productivity of the fleet. We implement the framework in an originally designed and specifically developed simulator-optimizer software tool. We make an application on a real open-pit mine case study taking into account the stochasticity of the equipment behavior and environment. The total system production values obtained with and without considering the equipment reliability, availability and maintainability (RAM) characteristics are compared. We show that by taking into account the truck and shovel RAM aspects, we can maximize the total production of the system and obtain specific information on the production availability and productivity of its components.
基金National Natural Science Foundation of China(No.50179032)Natural Science Foundation of Tianjin(No.000345)
文摘With the aim of visualizing the real-time simulation calculation of water delivery system (WDS), a structural drawing-oriented (SDO) simulation technique was presented, and applied to Zhangjiuhe Diversion Project, which is a long-distance water delivery system constructed for draw- ing water from the Zhangjiuhe River to Kunming city. Taking SIMULINK software as simulating plat-form, the technique established a visual dynamic simulation model for the system. The simulation procedure of the system was simplified,and the efficiency of modeling was also enhanced according to the modularization and reutilization of the simulation program. Furthermore, a self-optimization model was presented. Based on the digital simulation models, the on line controlled optimization link was added, and the input data can be continually optimized according to the feedback information of simulating output. The system was thus optimized automatically. Built upon MATLAB software, simulation optimization of the Zhangjiuhe Diversion Project was achieved, which provides a new way for the research of optimal operation of WDS.
基金Some of this material was presented at the 2008 INFORMS Annual Meeting and 2008 Winter Simulation Conference[56,57]This work was supported in part by Department of Energy under Award DE-SC0002223NIH under Grant 1R21DK088368-01.
文摘With the advance of new computational technology,stochastic systems simulation and optimization has become increasingly a popular subject in both academic research and industrial applications.This paper presents some of recent developments about the problem of optimizing a performance function from a simulation model.We begin by classifying different types of problems and then provide an overview of the major approaches,followed by a more in-depth presentation of two specific areas:optimal computing budget allocation and the nested partitions method.
基金Supported by the National Key Basic Research Program of China(1030021210710)
文摘Boiling heat transfer and the controllability of the thermal load of the cylinder head were studied.The thermodynamic phase change characteristics of the cylinder head coolant were considered and the mass,momentumand energy transfers between two phases were calculated with the interface transfer submodels by using the computational fluid dynamics software CFX. Results showed that compared with the single-phase flow without considering the boiling heat transfer,the sub-cooled boiling heat transfer of the cylinder head was greatly increased. According to the results of the numerical simulation,an optimized structure of the water jacket was proposed. Finally,temperature and velocity of coolant,diameter of flow passage and mean bubble diameter that influences sub-cooled boiling were studied using the orthogonal experiment method.
基金supported by National Hi-tech Research and Development Program of China (863 Program, Grant No. 2002AA411030)National Defense Foundation Scientific Research of China (Grant No. d2520061124)
文摘Network-based manufacturing is a kind of distributed system, which enables manufacturers to finish production tasks as well as to grasp the opportunities in the market, even if manufacturing resources are insufficient. One of the main problems in network-based manufacturing is the allocation of resources and the assignment of tasks rationally, according to flexible resource distribution. The mapping rules and relations between production techniques and resources are proposed, followed by the definition of the resource unit. Ultimately, the genetic programming method for the optimization of the manufacturing system is put forward. A set of software for the optimization system of simulation process using genetic programming techniques has been developed, and the problems of manufacturing resource planning in network-based manufacturing are solved with the simulation of optimizing methods by genetic programming. The optimum proposal of hardware planning, selection of company and scheduling will be obtained in theory to help company managers in scientific decision-making.
基金Supported by the National Basic Research Program of China(2012CB224806)the National Natural Science Foundation of China(21490584,21476236)the National High Technology Research and Development Program of China(2012AA03A606)
文摘As a major configuration of membrane elements,multi-channel porous inorganic membrane tubes were studied by means of theoretical analysis and simulation.Configuration optimization of a cylindrical 37-channel porous inorganic membrane tube was studied by increasing membrane filtration area and increasing permeation efficiency of inner channels.An optimal ratio of the channel diameter to the inter-channel distance was proposed so as to increase the total membrane filtration area of the membrane tube.The three-dimensional computational fluid dynamics(CFD) simulation was conducted to study the cross-flow permeation flow of pure water in the 37-channel ceramic membrane tube.A model combining Navier–Stokes equation with Darcy's law and the porous jump boundary conditions was applied.The relationship between permeation efficiency and channel locations,and the method for increasing the permeation efficiency of inner channels were proposed.Some novel multichannel membrane configurations with more permeate side channels were put forward and evaluated.
基金This work was supported by the National Natural Science Foundation of China(21878066).
文摘A new vapor distributor based on the Coanda effect is added to the Dividing Wall column(DWC),and the multiphase flow simulation is performed using ANSYS Fluent by this model.The results show that with the addition of the liquid phase,the new vapor distributor still follows the Coanda effect.Hereby,the vapor is ejected from the slits of the distributor to take away the surrounding vapor,and a negative pressure is formed under the distributor,so as to achieve the purpose of regulating Rv.Analogously to the working principle of vapor distributor,a certain amount of vapor is drawn out from a position of prefractionator,which is equivalent to the vapor ejected by the distributor.The same amount of vapor is fed into the main column,which corresponds to the gas phase at the inlet of the distributor.The Rv is adjusted by changing the speed of the input or output vapor.Simulation results show that adding this control mechanism on the basis of temperature or concentration control structure can better achieve the effect of vapor distribution.
文摘In this paper, we propose an ordinal optimization based simulation optimization algorithm to determine a target distribution of bicycles for a bicycle sharing network to minimize an expected cost. The proposed algorithm consists of two stages. The first stage is using GA （genetic algorithm） assisted by a surrogate model to select an estimated good enough subset of solutions. The second stage is to identify the best solution among the solutions obtained from stage one using optimal computing budget allocation technique. We have tested the proposed algorithm on a bicycle sharing network and compared the test results with those obtained by the GA with exact model. The test results demonstrate that the proposed algorithm can obtain a good enough solution within reasonable computing time and outperforms the comparing method.
文摘The research addresses the prevalence of gassy soil, containing methane (CH4), within the soil particles of southeast coastal areas of China, such as the Quaternary deposit in the Hangzhou Bay area. This soil exhibits spatial variability in the distribution of gas pressure, posing a potential threat of engineering disasters, including fire outbreaks and blasting, during the construction of underground projects. Consequently, it is crucial to assess the risk state of gas pressure, involving accurate identification and reduction of associated uncertainty, through site investigation. This is indispensable prior to the commencement of underground projects. However, during the site investigation stage, the random field parameters that quantify the spatial variability distribution of gas pressure (e.g., mean value, standard deviations, and scale of fluctuation) are unknown, introducing corresponding statistical uncertainty. Therefore, the most significant consideration for planning site investigation from an engineering perspective involves determining the risk state of gas pressure while considering the statistical uncertainty of these random field parameters. This consideration heavily relies on the engineering experience gained from current site investigation practices. To address this challenge, the study introduces a probabilistic site investigation optimization method designed for planning the site investigation scheme for gassy soils, including determining the number and locations of boreholes. The method is based on the expected state-identification probability, representing the probability of identifying the risk state of gas pressure, and takes into account the statistical uncertainty of random field parameters. The proposed method aims to determine an optimal investigation scheme before conducting the site investigation, leveraging prior knowledge. This optimal scheme is identified using Subset Simulation Optimization (SSO) in the space of candidate site investigations, maximizing the value of the expected state-identification probability at the minimal value point. Finally, the paper illustrates the proposed approach through a case study.
基金This work was supported by the National Natural Science Foundation of China(Grant No.11872157 and 11532013)the graduate innovative research project of Heilongjiang University of Science and Technology(Grant No.YJSCX2020-214HKD).
文摘The current Whale Optimization Algorithm(WOA)has several drawbacks,such as slow convergence,low solution accuracy and easy to fall into the local optimal solution.To overcome these drawbacks,an improved Whale Optimization Algorithm(IWOA)is proposed in this study.IWOA can enhance the global search capability by two measures.First,the crossover and mutation operations in Differential Evolutionary algorithm(DE)are combined with the whale optimization algorithm.Second,the cloud adaptive inertia weight is introduced in the position update phase of WOA to divide the population into two subgroups,so as to balance the global search ability and local development ability.ANSYS and Matlab are used to establish the structure model.To demonstrate the application of the IWOA,truss structural optimizations on 52-bar plane truss and 25-bar space truss were performed,and the results were are compared with that obtained by other optimization algorithm.It is verified that,compared with WOA,the IWOA has higher efficiency,fast convergence speed,better solution accuracy and stability.So IWOA can be used in the optimization design of large truss structures.
