The hydro unit economic load dispatch （ELD） is of great importance in energy conservation and emission reduction. Dynamic programming （DP） and genetic algorithm （GA） are two representative algorithms for solving...The hydro unit economic load dispatch （ELD） is of great importance in energy conservation and emission reduction. Dynamic programming （DP） and genetic algorithm （GA） are two representative algorithms for solving ELD problems. The goal of this study was to examine the performance of DP and GA while they were applied to ELD. We established numerical experiments to conduct performance comparisons between DP and GA with two given schemes. The schemes included comparing the CPU time of the algorithms when they had the same solution quality, and comparing the solution quality when they had the same CPU time. The numerical experiments were applied to the Three Gorges Reservoir in China, which is equipped with 26 hydro generation units. We found the relation between the performance of algorithms and the number of units through experiments. Results show that GA is adept at searching for optimal solutions in low-dimensional cases. In some cases, such as with a number of units of less than 10, GA＇s performance is superior to that of a coarse-grid DP. However, GA loses its superiority in high-dimensional cases. DP is powerful in obtaining stable and high-quality solutions. Its performance can be maintained even while searching over a large solution space. Nevertheless, due to its exhaustive enumerating nature, it costs excess time in low-dimensional cases.展开更多
Two classes of mixed-integer nonlinear bilevel programming problems are discussed. One is that the follower＇s functions are separable with respect to the follower＇s variables, and the other is that the follower＇s f...Two classes of mixed-integer nonlinear bilevel programming problems are discussed. One is that the follower＇s functions are separable with respect to the follower＇s variables, and the other is that the follower＇s functions are convex if the follower＇s variables are not restricted to integers. A genetic algorithm based on an exponential distribution is proposed for the aforementioned problems. First, for each fixed leader＇s variable x, it is proved that the optimal solution y of the follower＇s mixed-integer programming can be obtained by solving associated relaxed problems, and according to the convexity of the functions involved, a simplified branch and bound approach is given to solve the follower＇s programming for the second class of problems. Furthermore, based on an exponential distribution with a parameter λ, a new crossover operator is designed in which the best individuals are used to generate better offspring of crossover. The simulation results illustrate that the proposed algorithm is efficient and robust.展开更多
Load distribution is the foundation of shape control and gauge control, in which it is necessary to take into account the shape control ability of TCM （tandem cold mill） for strip shape and gauge quality. First, the...Load distribution is the foundation of shape control and gauge control, in which it is necessary to take into account the shape control ability of TCM （tandem cold mill） for strip shape and gauge quality. First, the objective function of generalized shape and gauge decoupling load distribution optimization was established, which considered the rolling force characteristics of the first and last stands in TCM, the relative power, and the TCM shape control ability. Then, IGA （immune genetic algorithm） was used to accomplish this multi-objective load distribution optimization for TCM. After simulation and comparison with the practical load distribution strategy in one tandem cold mill, general- ized shape and gauge decoupling load distribution optimization on the basis of IGA approved good ability of optimizing shape control and gauge control simultaneously.展开更多
This paper presents a powerful approach to find the optimal size and location of distributed generation units in a distribution system using GA(Genetic Optimization algorithm).It is proved that GA method is fast and e...This paper presents a powerful approach to find the optimal size and location of distributed generation units in a distribution system using GA(Genetic Optimization algorithm).It is proved that GA method is fast and easy tool to enable the planners to select accurate and the optimum size of generators to improve the system voltage profile in addition to reduce the active and reactive power loss.GA fitness function is introduced including the active power losses,reactive power losses and the cumulative voltage deviation variables with selecting weight of each variable.GA fitness function is subjected to voltage constraints,active and reactive power losses constraints and DG size constraint.展开更多
The optimization of the control strategy of a plug-in hybrid electric bus(PHEB) for the repeatedly driven bus route is a key technique to improve the fuel economy. The widely used rule-based(RB) control strategy is la...The optimization of the control strategy of a plug-in hybrid electric bus(PHEB) for the repeatedly driven bus route is a key technique to improve the fuel economy. The widely used rule-based(RB) control strategy is lacking in the global optimization property, while the global optimization algorithms have an unacceptable computation complexity for real-time application. Therefore, a novel hybrid dynamic programming-rule based(DPRB) algorithm is brought forward to solve the global energy optimization problem in a real-time controller of PHEB. Firstly, a control grid is built up for a given typical city bus route, according to the station locations and discrete levels of battery state of charge(SOC). Moreover, the decision variables for the energy optimization at each point of the control grid might be deduced from an off-line dynamic programming(DP) with the historical running information of the driving cycle. Meanwhile, the genetic algorithm(GA) is adopted to replace the quantization process of DP permissible control set to reduce the computation burden. Secondly, with the optimized decision variables as control parameters according to the position and battery SOC of a PHEB, a RB control is used as an implementable controller for the energy management. Simulation results demonstrate that the proposed DPRB might distribute electric energy more reasonably throughout the bus route, compared with the optimized RB. The proposed hybrid algorithm might give a practicable solution, which is a tradeoff between the applicability of RB and the global optimization property of DP.展开更多
This paper addresses a dynamic vehicle routing problem with stochastic requests in a dual-channel distribution center that utilizes shared vehicle resources to serve two types of customers:offline corporate clients(CC...This paper addresses a dynamic vehicle routing problem with stochastic requests in a dual-channel distribution center that utilizes shared vehicle resources to serve two types of customers:offline corporate clients(CCs)with fixed and stochastic batch demands,and online individual customers(ICs)with single-unit demands.To manage stochastic batch demands from CCs,this paper proposes three recourse policies under a differentiated resource-sharing scheme:the waiting-tour-based(WTB)policy,the advance-tour-based(ATB)policy,and the advance-customer-based(ACB)policy.These policies differ in their response priorities to random requests and the scope of route reoptimization.The problem is formulated as a two-stage stochastic recourse programming model,where the first stage establishes routes for fixed demands.In the second stage,we construct three stochastic recourse programming models corresponding to the proposed recourse policies.To solve these models,this paper develop rolling horizon algorithms integrated with mathematical programming models or metaheuristic algorithms.Extensive numerical experiments validate the effectiveness of the proposed algorithms and policies.The results indicate that both the ATB and ACB policies lead to cost savings compared to the WTB policy,especially when stochastic demands are urgent and delivery resources are quite limited.Specifically,when the number of ICs is small,the expected total cost savings can exceed 12%,and in some scenarios,savings of over 20%can be achieved.When the number of ICs is large,some scenarios can achieve cost savings exceeding 7%.Furthermore,the ACB policy yields lower costs,fewer worsened ICs,fewer trips,and less vehicle time than the ATB policy.展开更多
Optimization of cylindrical roller bearings(CRBs)has been performed using a robust design.It ensures that the changes in the objective function,even in the case of variations in design variables during manufacturing,h...Optimization of cylindrical roller bearings(CRBs)has been performed using a robust design.It ensures that the changes in the objective function,even in the case of variations in design variables during manufacturing,have a minimum possible value and do not exceed the upper limit of a desired range of percentage variation.Also,it checks the feasibility of design outcome in presence of manufacturing tolerances in design variables.For any rolling element bearing,a long life indicates a satisfactory performance.In the present study,the dynamic load carrying capacity C,which relates to fatigue life,has been optimized using the robust design.In roller bearings,boundary dimensions(i.e.,bearing outer diameter,bore diameter and width)are standard.Hence,the performance is mainly affected by the internal dimensions and not the bearing boundary dimensions mentioned formerly.In spite of this,besides internal dimensions and their tolerances,the tolerances in boundary dimensions have also been taken into consideration for the robust optimization.The problem has been solved with the elitist non-dominating sorting genetic algorithm(NSGA-II).Finally,for the visualization and to ensure manufacturability of CRB using obtained values,radial dimensions drawing of one of the optimized CRB has been made.To check the robustness of obtained design after optimization,a sensitivity analysis has also been carried out to find out how much the variation in the objective function will be in case of variation in optimized value of design variables.Optimized bearings have been found to have improved life as compared with standard ones.展开更多
This research develops a comprehensive method to solve a combinatorial problem consisting of distribution system reconfiguration, capacitor allocation, and renewable energy resources sizing and siting simultaneously a...This research develops a comprehensive method to solve a combinatorial problem consisting of distribution system reconfiguration, capacitor allocation, and renewable energy resources sizing and siting simultaneously and to improve power system's accountability and system performance parameters. Due to finding solution which is closer to realistic characteristics, load forecasting, market price errors and the uncertainties related to the variable output power of wind based DG units are put in consideration. This work employs NSGA-II accompanied by the fuzzy set theory to solve the aforementioned multi-objective problem. The proposed scheme finally leads to a solution with a minimum voltage deviation, a maximum voltage stability, lower amount of pollutant and lower cost. The cost includes the installation costs of new equipment, reconfiguration costs, power loss cost, reliability cost, cost of energy purchased from power market, upgrade costs of lines and operation and maintenance costs of DGs. Therefore, the proposed methodology improves power quality, reliability and security in lower costs besides its preserve, with the operational indices of power distribution networks in acceptable level. To validate the proposed methodology's usefulness, it was applied on the IEEE 33-bus distribution system then the outcomes were compared with initial configuration.展开更多
This paper presents an efficient numerical tool for the prediction of railway dynamic response.A behavior calibration of the infinite Euler-Bernoulli beam resting on continuous viscoelastic foundation is proposed.Cons...This paper presents an efficient numerical tool for the prediction of railway dynamic response.A behavior calibration of the infinite Euler-Bernoulli beam resting on continuous viscoelastic foundation is proposed.Constitutive laws of the discrete elements are determined for a rectilinear ballasted track.A three-dimensional model coupled with an adaptive meshing scheme is employed to calibrate the beam model impedances by finding the similarity between the output signals using the genetic algorithm.The model shows an important performance with significant reduction in computational effort.This study emphasizes the major impact of the excitation characteristics on the parameters of the discrete models.展开更多
应急物资调度是灾后应急响应的关键环节,其调度效率直接影响救援效果。突发自然灾害经常伴随着道路损毁,严重制约着应急物资的运输。在应急物资调度中,卡车载重量大、行驶距离长;无人机运输不依赖于地面路况但受到电池和载重约束,二者...应急物资调度是灾后应急响应的关键环节,其调度效率直接影响救援效果。突发自然灾害经常伴随着道路损毁,严重制约着应急物资的运输。在应急物资调度中,卡车载重量大、行驶距离长;无人机运输不依赖于地面路况但受到电池和载重约束,二者协同能够实现优势互补。为提升应急物资的调度效率,本文研究了卡车-无人机协同的灾后应急物资调度策略。以卡车和无人机完成所有物资运输并回到配送中心的时间最短为目标,考虑卡车和无人机的载重和里程约束、道路损毁和道路拥堵限制,建立了混合整数规划模型。针对所提出的模型属于NP难问题,融合遗传算法和动态规划算法的优点,提出了新的混合算法(hybrid method based on genetic algorithm and dynamic programming, HGADP)。本文针对提出的管理问题场景,设计了小、中、大三种不同规模的算例,通过将本文提出的算法与Gurobi求解器和前人提出的算法对比,验证了本文提出算法的有效性。通过算例结果分析,发现相比于传统车辆运输模型,本文提出的卡车-无人机协同运输模型可大幅地节省物资运输时间。最后,本文对无人机载重和续航里程进行灵敏性分析,分析了参数变化对应急物资调度效率的影响。本研究拓展了应急物资调度策略,为应急管理部门的应急物资调度决策提供了决策依据。展开更多
基金supported by the National Basic Research Program of China(973 Program,Grant No.2013CB036406)the National Natural Science Foundation of China(Grant No.51179044)the Research Innovation Program for College Graduates in Jiangsu Province of China(Grant No.CXZZ12-0242)
文摘The hydro unit economic load dispatch （ELD） is of great importance in energy conservation and emission reduction. Dynamic programming （DP） and genetic algorithm （GA） are two representative algorithms for solving ELD problems. The goal of this study was to examine the performance of DP and GA while they were applied to ELD. We established numerical experiments to conduct performance comparisons between DP and GA with two given schemes. The schemes included comparing the CPU time of the algorithms when they had the same solution quality, and comparing the solution quality when they had the same CPU time. The numerical experiments were applied to the Three Gorges Reservoir in China, which is equipped with 26 hydro generation units. We found the relation between the performance of algorithms and the number of units through experiments. Results show that GA is adept at searching for optimal solutions in low-dimensional cases. In some cases, such as with a number of units of less than 10, GA＇s performance is superior to that of a coarse-grid DP. However, GA loses its superiority in high-dimensional cases. DP is powerful in obtaining stable and high-quality solutions. Its performance can be maintained even while searching over a large solution space. Nevertheless, due to its exhaustive enumerating nature, it costs excess time in low-dimensional cases.
基金supported by the National Natural Science Fundation of China (60374063)
文摘Two classes of mixed-integer nonlinear bilevel programming problems are discussed. One is that the follower＇s functions are separable with respect to the follower＇s variables, and the other is that the follower＇s functions are convex if the follower＇s variables are not restricted to integers. A genetic algorithm based on an exponential distribution is proposed for the aforementioned problems. First, for each fixed leader＇s variable x, it is proved that the optimal solution y of the follower＇s mixed-integer programming can be obtained by solving associated relaxed problems, and according to the convexity of the functions involved, a simplified branch and bound approach is given to solve the follower＇s programming for the second class of problems. Furthermore, based on an exponential distribution with a parameter λ, a new crossover operator is designed in which the best individuals are used to generate better offspring of crossover. The simulation results illustrate that the proposed algorithm is efficient and robust.
基金Item Sponsored by National Significant Technology and Equipment Research Project of China (ZZ02-13B-03)
文摘Load distribution is the foundation of shape control and gauge control, in which it is necessary to take into account the shape control ability of TCM （tandem cold mill） for strip shape and gauge quality. First, the objective function of generalized shape and gauge decoupling load distribution optimization was established, which considered the rolling force characteristics of the first and last stands in TCM, the relative power, and the TCM shape control ability. Then, IGA （immune genetic algorithm） was used to accomplish this multi-objective load distribution optimization for TCM. After simulation and comparison with the practical load distribution strategy in one tandem cold mill, general- ized shape and gauge decoupling load distribution optimization on the basis of IGA approved good ability of optimizing shape control and gauge control simultaneously.
文摘This paper presents a powerful approach to find the optimal size and location of distributed generation units in a distribution system using GA(Genetic Optimization algorithm).It is proved that GA method is fast and easy tool to enable the planners to select accurate and the optimum size of generators to improve the system voltage profile in addition to reduce the active and reactive power loss.GA fitness function is introduced including the active power losses,reactive power losses and the cumulative voltage deviation variables with selecting weight of each variable.GA fitness function is subjected to voltage constraints,active and reactive power losses constraints and DG size constraint.
基金supported by the National Natural Science Foundation of China(Grant No.51275557,5142505)the National Science-Technology Support Plan Projects of China(Grant No.2013BAG14B01)
文摘The optimization of the control strategy of a plug-in hybrid electric bus(PHEB) for the repeatedly driven bus route is a key technique to improve the fuel economy. The widely used rule-based(RB) control strategy is lacking in the global optimization property, while the global optimization algorithms have an unacceptable computation complexity for real-time application. Therefore, a novel hybrid dynamic programming-rule based(DPRB) algorithm is brought forward to solve the global energy optimization problem in a real-time controller of PHEB. Firstly, a control grid is built up for a given typical city bus route, according to the station locations and discrete levels of battery state of charge(SOC). Moreover, the decision variables for the energy optimization at each point of the control grid might be deduced from an off-line dynamic programming(DP) with the historical running information of the driving cycle. Meanwhile, the genetic algorithm(GA) is adopted to replace the quantization process of DP permissible control set to reduce the computation burden. Secondly, with the optimized decision variables as control parameters according to the position and battery SOC of a PHEB, a RB control is used as an implementable controller for the energy management. Simulation results demonstrate that the proposed DPRB might distribute electric energy more reasonably throughout the bus route, compared with the optimized RB. The proposed hybrid algorithm might give a practicable solution, which is a tradeoff between the applicability of RB and the global optimization property of DP.
基金supported by the National Natural Science Foundation of China(71991464/71991460,72301261,72001066)2024 Anhui Province High-end Talent Introduction and Cultivation Project.
文摘This paper addresses a dynamic vehicle routing problem with stochastic requests in a dual-channel distribution center that utilizes shared vehicle resources to serve two types of customers:offline corporate clients(CCs)with fixed and stochastic batch demands,and online individual customers(ICs)with single-unit demands.To manage stochastic batch demands from CCs,this paper proposes three recourse policies under a differentiated resource-sharing scheme:the waiting-tour-based(WTB)policy,the advance-tour-based(ATB)policy,and the advance-customer-based(ACB)policy.These policies differ in their response priorities to random requests and the scope of route reoptimization.The problem is formulated as a two-stage stochastic recourse programming model,where the first stage establishes routes for fixed demands.In the second stage,we construct three stochastic recourse programming models corresponding to the proposed recourse policies.To solve these models,this paper develop rolling horizon algorithms integrated with mathematical programming models or metaheuristic algorithms.Extensive numerical experiments validate the effectiveness of the proposed algorithms and policies.The results indicate that both the ATB and ACB policies lead to cost savings compared to the WTB policy,especially when stochastic demands are urgent and delivery resources are quite limited.Specifically,when the number of ICs is small,the expected total cost savings can exceed 12%,and in some scenarios,savings of over 20%can be achieved.When the number of ICs is large,some scenarios can achieve cost savings exceeding 7%.Furthermore,the ACB policy yields lower costs,fewer worsened ICs,fewer trips,and less vehicle time than the ATB policy.
文摘Optimization of cylindrical roller bearings(CRBs)has been performed using a robust design.It ensures that the changes in the objective function,even in the case of variations in design variables during manufacturing,have a minimum possible value and do not exceed the upper limit of a desired range of percentage variation.Also,it checks the feasibility of design outcome in presence of manufacturing tolerances in design variables.For any rolling element bearing,a long life indicates a satisfactory performance.In the present study,the dynamic load carrying capacity C,which relates to fatigue life,has been optimized using the robust design.In roller bearings,boundary dimensions(i.e.,bearing outer diameter,bore diameter and width)are standard.Hence,the performance is mainly affected by the internal dimensions and not the bearing boundary dimensions mentioned formerly.In spite of this,besides internal dimensions and their tolerances,the tolerances in boundary dimensions have also been taken into consideration for the robust optimization.The problem has been solved with the elitist non-dominating sorting genetic algorithm(NSGA-II).Finally,for the visualization and to ensure manufacturability of CRB using obtained values,radial dimensions drawing of one of the optimized CRB has been made.To check the robustness of obtained design after optimization,a sensitivity analysis has also been carried out to find out how much the variation in the objective function will be in case of variation in optimized value of design variables.Optimized bearings have been found to have improved life as compared with standard ones.
文摘This research develops a comprehensive method to solve a combinatorial problem consisting of distribution system reconfiguration, capacitor allocation, and renewable energy resources sizing and siting simultaneously and to improve power system's accountability and system performance parameters. Due to finding solution which is closer to realistic characteristics, load forecasting, market price errors and the uncertainties related to the variable output power of wind based DG units are put in consideration. This work employs NSGA-II accompanied by the fuzzy set theory to solve the aforementioned multi-objective problem. The proposed scheme finally leads to a solution with a minimum voltage deviation, a maximum voltage stability, lower amount of pollutant and lower cost. The cost includes the installation costs of new equipment, reconfiguration costs, power loss cost, reliability cost, cost of energy purchased from power market, upgrade costs of lines and operation and maintenance costs of DGs. Therefore, the proposed methodology improves power quality, reliability and security in lower costs besides its preserve, with the operational indices of power distribution networks in acceptable level. To validate the proposed methodology's usefulness, it was applied on the IEEE 33-bus distribution system then the outcomes were compared with initial configuration.
文摘This paper presents an efficient numerical tool for the prediction of railway dynamic response.A behavior calibration of the infinite Euler-Bernoulli beam resting on continuous viscoelastic foundation is proposed.Constitutive laws of the discrete elements are determined for a rectilinear ballasted track.A three-dimensional model coupled with an adaptive meshing scheme is employed to calibrate the beam model impedances by finding the similarity between the output signals using the genetic algorithm.The model shows an important performance with significant reduction in computational effort.This study emphasizes the major impact of the excitation characteristics on the parameters of the discrete models.
文摘应急物资调度是灾后应急响应的关键环节,其调度效率直接影响救援效果。突发自然灾害经常伴随着道路损毁,严重制约着应急物资的运输。在应急物资调度中,卡车载重量大、行驶距离长;无人机运输不依赖于地面路况但受到电池和载重约束,二者协同能够实现优势互补。为提升应急物资的调度效率,本文研究了卡车-无人机协同的灾后应急物资调度策略。以卡车和无人机完成所有物资运输并回到配送中心的时间最短为目标,考虑卡车和无人机的载重和里程约束、道路损毁和道路拥堵限制,建立了混合整数规划模型。针对所提出的模型属于NP难问题,融合遗传算法和动态规划算法的优点,提出了新的混合算法(hybrid method based on genetic algorithm and dynamic programming, HGADP)。本文针对提出的管理问题场景,设计了小、中、大三种不同规模的算例,通过将本文提出的算法与Gurobi求解器和前人提出的算法对比,验证了本文提出算法的有效性。通过算例结果分析,发现相比于传统车辆运输模型,本文提出的卡车-无人机协同运输模型可大幅地节省物资运输时间。最后,本文对无人机载重和续航里程进行灵敏性分析,分析了参数变化对应急物资调度效率的影响。本研究拓展了应急物资调度策略,为应急管理部门的应急物资调度决策提供了决策依据。
