This paper reviews existing approaches to the airport gate assignment problem （AGAP） and presents an optimization model for the problem considering operational safety constraints. The main objective is to minimize t...This paper reviews existing approaches to the airport gate assignment problem （AGAP） and presents an optimization model for the problem considering operational safety constraints. The main objective is to minimize the dispersion of gate idle time periods （to get robust optimization） while ensuring appropriate matching between the size of each aircraft and its assigned gate type and avoiding the potential hazard caused by gate apron operational conflict. Genetic algorithm is adopted to solve the problem, An illustrative example is given to show the effectiveness and efficiency of the algorithm. The algorithm performance is further demonstrated using data of a terminal from Beijing Capital International Airport （PEK）.展开更多
Traditional deconvolution methods based on single-channel inversion do not consider the spatial structural relation between channels,and hence,they yield high-resolution results with the existing transverse inconsiste...Traditional deconvolution methods based on single-channel inversion do not consider the spatial structural relation between channels,and hence,they yield high-resolution results with the existing transverse inconsistency or discontinuity.Therefore,in this study,the local dip angle was used to obtain the structural information and construct the spatial structurally constraint operator.This operator is then introduced into multichannel deconvolution as a regularization operator to improve the resolution and maintain the transverse continuity of seismic data.Model tests and actual seismic data processing have demonstrated the effectiveness and practicability of this method.展开更多
Enhancing the efficiency of Rankine cycles is crucial for improving the performance of thermal power plants,as it directly impacts operational costs and emissions in light of energy transition goals.This study sets it...Enhancing the efficiency of Rankine cycles is crucial for improving the performance of thermal power plants,as it directly impacts operational costs and emissions in light of energy transition goals.This study sets itself apart from existing research by applying a novel optimization technique to a basic ideal Rankine cycle,focusing on a specific power plant that has not been previously analyzed.Currently,this cycle operates at 41%efficiency and a steam quality of 76%,constrained by fixed operational parameters.The primary objectives are to increase thermal efficiency beyond 46%and raise steam quality above 85%,while adhering to operational limits:a boiler pressure not exceeding 15 MPa,condenser pressure not dropping below 10 kPa,and turbine temperature not surpassing 500℃.This study utilizes numerical simulations to model the effects of varying boiler pressure(Pb)and condenser pressure(Pc)within the ranges of 12MPa<Pb<15 MPa and 5 kPa<Pc<10 kPa.By systematically adjusting these parameters,the proposed aimto identify optimal conditions that maximize efficiency and performance within specified constraints.The findings will provide valuable insights for power plant operators seeking to optimize performance under real-world conditions,contributing to more efficient and sustainable power generation.展开更多
A first-order necessary condition for an infinite-dimensional nonlinear op-timization problem, which arises when the all-at-once method is employed to slove theoptimal control problems, is formulated and analyzed. Ope...A first-order necessary condition for an infinite-dimensional nonlinear op-timization problem, which arises when the all-at-once method is employed to slove theoptimal control problems, is formulated and analyzed. Operator constraint and simplebound on part of the variables are both considered. Based on this optimality condition,the trust-region subproblems are built, then the trust region method rnay be employedto deal with the optimizatiou problem in infinite-dimensional space.展开更多
The problem of D-pseudoconvex programming with operator con-straints is discussed in this paper.Some new optimality conditions are presentedand an error made by V.Barbu in [4] is pointed out.
文摘This paper reviews existing approaches to the airport gate assignment problem （AGAP） and presents an optimization model for the problem considering operational safety constraints. The main objective is to minimize the dispersion of gate idle time periods （to get robust optimization） while ensuring appropriate matching between the size of each aircraft and its assigned gate type and avoiding the potential hazard caused by gate apron operational conflict. Genetic algorithm is adopted to solve the problem, An illustrative example is given to show the effectiveness and efficiency of the algorithm. The algorithm performance is further demonstrated using data of a terminal from Beijing Capital International Airport （PEK）.
基金supported by the basic and forward-looking project(No.2023YQX302)。
文摘Traditional deconvolution methods based on single-channel inversion do not consider the spatial structural relation between channels,and hence,they yield high-resolution results with the existing transverse inconsistency or discontinuity.Therefore,in this study,the local dip angle was used to obtain the structural information and construct the spatial structurally constraint operator.This operator is then introduced into multichannel deconvolution as a regularization operator to improve the resolution and maintain the transverse continuity of seismic data.Model tests and actual seismic data processing have demonstrated the effectiveness and practicability of this method.
文摘Enhancing the efficiency of Rankine cycles is crucial for improving the performance of thermal power plants,as it directly impacts operational costs and emissions in light of energy transition goals.This study sets itself apart from existing research by applying a novel optimization technique to a basic ideal Rankine cycle,focusing on a specific power plant that has not been previously analyzed.Currently,this cycle operates at 41%efficiency and a steam quality of 76%,constrained by fixed operational parameters.The primary objectives are to increase thermal efficiency beyond 46%and raise steam quality above 85%,while adhering to operational limits:a boiler pressure not exceeding 15 MPa,condenser pressure not dropping below 10 kPa,and turbine temperature not surpassing 500℃.This study utilizes numerical simulations to model the effects of varying boiler pressure(Pb)and condenser pressure(Pc)within the ranges of 12MPa<Pb<15 MPa and 5 kPa<Pc<10 kPa.By systematically adjusting these parameters,the proposed aimto identify optimal conditions that maximize efficiency and performance within specified constraints.The findings will provide valuable insights for power plant operators seeking to optimize performance under real-world conditions,contributing to more efficient and sustainable power generation.
文摘A first-order necessary condition for an infinite-dimensional nonlinear op-timization problem, which arises when the all-at-once method is employed to slove theoptimal control problems, is formulated and analyzed. Operator constraint and simplebound on part of the variables are both considered. Based on this optimality condition,the trust-region subproblems are built, then the trust region method rnay be employedto deal with the optimizatiou problem in infinite-dimensional space.
基金supported by National Natural Science Foundation of China
文摘The problem of D-pseudoconvex programming with operator con-straints is discussed in this paper.Some new optimality conditions are presentedand an error made by V.Barbu in [4] is pointed out.
