The metaheuristic algorithms are widely used in solving the parameters of the optimization problem.The marine predators algorithm(MPA)is a novel population-based intelligent algorithm.Although MPA has shown a talented...The metaheuristic algorithms are widely used in solving the parameters of the optimization problem.The marine predators algorithm(MPA)is a novel population-based intelligent algorithm.Although MPA has shown a talented foraging strategy,it still needs a balance of exploration and exploitation.Therefore,a multi-stage improvement of marine predators algorithm(MSMPA)is proposed in this paper.The algorithm retains the advantage of multistage search and introduces a linear flight strategy in the middle stage to enhance the interaction between predators.Predators further away from the historical optimum are required to move,increasing the exploration capability of the algorithm.In the middle and late stages,the searchmechanism of particle swarmoptimization(PSO)is inserted,which enhances the exploitation capability of the algorithm.This means that the stochasticity is decreased,that is the optimal region where predators jumping out is effectively stifled.At the same time,self-adjusting weight is used to regulate the convergence speed of the algorithm,which can balance the exploration and exploitation capability of the algorithm.The algorithm is applied to different types of CEC2017 benchmark test functions and threemultidimensional nonlinear structure design optimization problems,compared with other recent algorithms.The results show that the convergence speed and accuracy of MSMPA are significantly better than that of the comparison algorithms.展开更多
E-commerce, as an emerging marketing mode, has attracted more and more attention and gradually changed the way of our life. However, the existing layout of distribution centers can＇t fulfill the storage and picking d...E-commerce, as an emerging marketing mode, has attracted more and more attention and gradually changed the way of our life. However, the existing layout of distribution centers can＇t fulfill the storage and picking demands of e-commerce sufficiently. In this paper, a modified miniload automated storage/retrieval system is designed to fit these new characteristics of e-commerce in logistics. Meanwhile, a matching problem, concerning with the improvement of picking efficiency in new system, is studied in this paper. The problem is how to reduce the travelling distance of totes between aisles and picking stations. A multi-stage heuristic algorithm is proposed based on statement and model of this problem. The main idea of this algorithm is, with some heuristic strategies based on similarity coefficients, minimizing the transportations of items which can not arrive in the destination picking stations just through direct conveyors. The experimental results based on the cases generated by computers show that the average reduced rate of indirect transport times can reach 14.36% with the application of multi-stage heuristic algorithm. For the cases from a real e-commerce distribution center, the order processing time can be reduced from 11.20 h to 10.06 h with the help of the modified system and the proposed algorithm. In summary, this research proposed a modified system and a multi-stage heuristic algorithm that can reduce the travelling distance of totes effectively and improve the whole performance of e-commerce distribution center.展开更多
A new hang-off system has been proposed to improve the security of risers in hang-off modes during typhoons.However,efficient anti-typhoon evacuation strategies have not been investigated.Optimiza-tion model and metho...A new hang-off system has been proposed to improve the security of risers in hang-off modes during typhoons.However,efficient anti-typhoon evacuation strategies have not been investigated.Optimiza-tion model and method for the anti-typhoon evacuation strategies should be researched.Therefore,multi-objective functions are proposed based on operation time,evacuation speed stability,and steering stability.An evacuation path model and a dynamic model of risers with the new hang-off system are developed for design variables and constraints.A multi-objective optimization model with high-dimensional variables and complex constraints is established.Finally,a three-stage optimization method based on genetic algorithm,least square method,and the penalty function method is proposed to solve the multi-objective optimization model.Optimization results show that the operation time can be reduced through operation parameter optimization,especially evacuation heading optimization.The optimal anti-typhoon strategy is evacuation with all risers suspended along a variable path when the direction angle is large,while evacuation with all risers suspended along a straight path at another di-rection angle.Besides,the influencing factors on anti-typhoon evacuation strategies indicate that the proposed optimization model and method have strong applicability to working conditions and remarkable optimization effects.展开更多
In this paper we proposed an AMH Supply Chain model to obtain optimal solutions for Two-, Three- and Four-Stage for deterministic models. Besides deriving its algebraic solutions, a simple searching method is successf...In this paper we proposed an AMH Supply Chain model to obtain optimal solutions for Two-, Three- and Four-Stage for deterministic models. Besides deriving its algebraic solutions, a simple searching method is successfully applied in obtaining optimal total costs and its integer multipliers. Our model has shown promising results in comparison to Equal Cycle Time and other existing ones. The tests focused on obtaining optimal total annual costs and other related details of Two-, Three- and Four-Stage for deterministic models. The results are run under Visual Basic Programming platform using Intel? CoreTM2 Duo T6500 Processor.展开更多
To decompose an unbalanced multi-stage logistic system to multipleindependent single-stage logistic systems, a new notion of parameterized interface distribution ispresented. For encoding the logistic pattern on each ...To decompose an unbalanced multi-stage logistic system to multipleindependent single-stage logistic systems, a new notion of parameterized interface distribution ispresented. For encoding the logistic pattern on each stage, the Pruefer number is used. With theimproved decoding procedure, any Pruefer number produced stochastically can be decoded to a feasiblelogistic pattern, which can match with the capacities of the nodes of the logistic system. Withthese two innovations, a new modeling method based on parameterized interface distribution and thePriifer number coding is put forward. The corresponding genetic algorithm, named as PIP-GA, can findbetter solutions and require less computational time than st-GA. Although requiring a little moreconsumption of memory, PIP-GA is still an efficient and robust method in the modeling andoptimization of unbalanced multi-stage logistic systems.展开更多
A novel rule-based model for multi-stage multi-product scheduling problem(MMSP)in batch plants with parallel units is proposed.The scheduling problem is decomposed into two sub-problems of order assignment and order s...A novel rule-based model for multi-stage multi-product scheduling problem(MMSP)in batch plants with parallel units is proposed.The scheduling problem is decomposed into two sub-problems of order assignment and order sequencing.Firstly,hierarchical scheduling strategy is presented for solving the former sub-problem,where the multi-stage multi-product batch process is divided into multiple sequentially connected single process stages,and then the production of orders are arranged in each single stage by using forward order assignment strategy and backward order assignment strategy respectively according to the feature of scheduling objective.Line-up competition algorithm(LCA)is presented to find out optimal order sequence and order assignment rule,which can minimize total flow time or maximize total weighted process time.Computational results show that the proposed approach can obtain better solutions than those of the literature for all scheduling problems with more than 10 orders.Moreover,with the problem size increasing,the solutions obtained by the proposed approach are improved remarkably.The proposed approach has the potential to solve large size MMSP.展开更多
Conventional multi-stage constant current charging strategies often use higher multiples of current to charge the battery in pursuit of shorter charging times.However,this leads to an increase in battery temperature,w...Conventional multi-stage constant current charging strategies often use higher multiples of current to charge the battery in pursuit of shorter charging times.However,this leads to an increase in battery temperature,while shortening the charging time.This in turn affects the safety of the charging process.Furthermore,the higher charging currents are not ideal for shortening the charging time in the later stages of charging.To solve the aforementioned problems,in this study,a multi-stage constant current charging strategy is presented.This strategy can shorten the battery charging time by using the increase in battery temperature during the charging process as a constraint,using a genetic algorithm to calculate the charging current value,and investigating the phased approach to charging.Finally,the charging strategy is experimentally validated at different ambient temperatures and different initial SOCs.The experimental results show that the charging strategy proposed in this paper not only reduces the amount of calculations,but also reduces the temperature rise by up to 46.4%and charging time by up to 4.2%under different operating conditions.展开更多
The potential to save energy in existing consumer electrical appliances is very high. One of the ways to achieve energy saving and improve energy use awareness is to recognize the energy consumption of individual elec...The potential to save energy in existing consumer electrical appliances is very high. One of the ways to achieve energy saving and improve energy use awareness is to recognize the energy consumption of individual electrical appliances. To recognize the energy consumption of consumer electrical appliances, the load disaggregation methodology is utilized. Non-intrusive appliance load monitoring (NIALM) is a load disaggrega-tion methodology that disaggregates the sum of power consumption in a single point into the power consumption of individual electrical appliances. In this study, load disaggregation is performed through voltage and current waveform, known as the V-I trajectory. The classification algorithm performs cropping and image pyramid reduction of the V-I trajectory plot template images before utilizing the principal component analysis (PCA) and the k-nearest neighbor (k-NN) algorithm. The novelty of this paper is to establish a systematic approach of load disaggregation through V-I trajectory-based load signature images by utilizing a multi-stage classification algorithm methodol-ogy. The contribution of this paper is in utilizing the “k- value,” the number of closest data points to the nearest neighbor, in the k-NN algorithm to be effective in classification of electrical appliances. The results of the multi-stage classification algorithm implementation have been discussed and the idea on future work has also been proposed.展开更多
Throughflow design has the advantages of less time consumption and large optimization space,and thus is the corner stone of advanced design system of multi-stage axial-flow compressors.The majority of relevant studies...Throughflow design has the advantages of less time consumption and large optimization space,and thus is the corner stone of advanced design system of multi-stage axial-flow compressors.The majority of relevant studies were limited to the throughflow inverse designs,and quite few works have been till now devoted to the throughflow optimal designs.In this work,an automatic and rapid throughflow-based optimal design method is proposed for axial-flow compressors in which a throughflow inverse design solver is embedded in optimal genetic algorithm to improve the design efficiency of axial-flow compressor.Two types of design parameters in the throughflow inverse design of axial-flow compressors,i.e.,swirl and shroud curve,are simultaneously used to optimize both the blade shape and flow path.The proposed method is validated by the redesign optimization of the benchmark axial-flow compressor NASA Stage 35,and the CFD predictions show that the throughflow-based optimization leads to 1.18% efficiency benefit at design condition.The proposed method is then utilized to the two-dimensional throughflow optimal design of a large-scale 6.5-stage axial-flow industrial compressor.The optimal design results are confirmed by CFD predictions,indicating that the proposed method can effectively improve the design adiabatic efficiency of the compressors by 1.09% within a few minutes on desk-top computer.Two throughflow design implications are also obtained for advanced axial-flow industrial compressors.This work could enhance the capability of throughflow design method and has engineering application value to explore the throughflow optimization space of multi-stage axial-flow compressors.展开更多
As the observation data generated by Earth Observation Satellites(EOSs)increase,the joint scheduling of satellite imaging and data transmission has become a bottleneck in EOS resource applications.This study has propo...As the observation data generated by Earth Observation Satellites(EOSs)increase,the joint scheduling of satellite imaging and data transmission has become a bottleneck in EOS resource applications.This study has proposed a three-stage-based hybrid meta-heuristic scheduling algorithm for the Agile Satellite Joint Imaging and Data Transmission Scheduling(ASJIDTS)problem.The original complex problem is decomposed into three distinct phases:joint task allocation for imaging and data transmission,scheduling of imaging tasks,and scheduling data transmission tasks.During the initial phase of joint task allocation,both imaging and data transmission resources are preemptively allocated using a greedy-based strategy,which considers data transmission opportunities,the conflict degree,and the spatial distribution of different resources.Subsequently,the imaging task scheduling phase generates an optimized sequence for imaging tasks.Based on this sequence,a rule-based multi-insertion strategy for the data transmission scheduling phase has been designed,which ensures rapid responsiveness to data transmission tasks.Extensive experiments have been conducted to verify the proposed algorithm.For the scheduling scenarios with 200 tasks,The Hybrid Metaheuristic Algorithm based on Multi-Stage(HMA-MS)shows at least a 14.11%increase in scheduling profit compared to several excellent algorithms.The experimental results validate the superior capability of the proposed algorithm in handling large-scale scheduling problems.展开更多
利用杭州市公交线路站点GIS数据和车辆运行GPS数据进行分析,将公交车到站时间分为站点停靠时间和站间行程时间,得到公交车站点之间运行可能总时间的分布概率.通过实际的公交路网结构,定义扩展的公交网络有效路径.在考虑公交线路联合发...利用杭州市公交线路站点GIS数据和车辆运行GPS数据进行分析,将公交车到站时间分为站点停靠时间和站间行程时间,得到公交车站点之间运行可能总时间的分布概率.通过实际的公交路网结构,定义扩展的公交网络有效路径.在考虑公交线路联合发车频率和根据乘客路径选择的广义成本下,建立出行策略与行程时间不确定下的公交客流分配模型,并将公交线路发车时刻表引入用户均衡模型中,设计了基于扩展网络最短路的Method of Successive Average(MSA)算法求解,通过对两个交通小区间高峰小时的客流分配结果验证模型和算法的有效性.展开更多
基金supported in part byNationalNatural Science Foundation of China(No.62066001)Natural Science Foundation of Ningxia Province(No.2021AAC03230)Program of Graduate Innovation Research of North Minzu University(No.YCX22111).
文摘The metaheuristic algorithms are widely used in solving the parameters of the optimization problem.The marine predators algorithm(MPA)is a novel population-based intelligent algorithm.Although MPA has shown a talented foraging strategy,it still needs a balance of exploration and exploitation.Therefore,a multi-stage improvement of marine predators algorithm(MSMPA)is proposed in this paper.The algorithm retains the advantage of multistage search and introduces a linear flight strategy in the middle stage to enhance the interaction between predators.Predators further away from the historical optimum are required to move,increasing the exploration capability of the algorithm.In the middle and late stages,the searchmechanism of particle swarmoptimization(PSO)is inserted,which enhances the exploitation capability of the algorithm.This means that the stochasticity is decreased,that is the optimal region where predators jumping out is effectively stifled.At the same time,self-adjusting weight is used to regulate the convergence speed of the algorithm,which can balance the exploration and exploitation capability of the algorithm.The algorithm is applied to different types of CEC2017 benchmark test functions and threemultidimensional nonlinear structure design optimization problems,compared with other recent algorithms.The results show that the convergence speed and accuracy of MSMPA are significantly better than that of the comparison algorithms.
文摘E-commerce, as an emerging marketing mode, has attracted more and more attention and gradually changed the way of our life. However, the existing layout of distribution centers can＇t fulfill the storage and picking demands of e-commerce sufficiently. In this paper, a modified miniload automated storage/retrieval system is designed to fit these new characteristics of e-commerce in logistics. Meanwhile, a matching problem, concerning with the improvement of picking efficiency in new system, is studied in this paper. The problem is how to reduce the travelling distance of totes between aisles and picking stations. A multi-stage heuristic algorithm is proposed based on statement and model of this problem. The main idea of this algorithm is, with some heuristic strategies based on similarity coefficients, minimizing the transportations of items which can not arrive in the destination picking stations just through direct conveyors. The experimental results based on the cases generated by computers show that the average reduced rate of indirect transport times can reach 14.36% with the application of multi-stage heuristic algorithm. For the cases from a real e-commerce distribution center, the order processing time can be reduced from 11.20 h to 10.06 h with the help of the modified system and the proposed algorithm. In summary, this research proposed a modified system and a multi-stage heuristic algorithm that can reduce the travelling distance of totes effectively and improve the whole performance of e-commerce distribution center.
基金supported by the National Natural Science Foundation of China(Grant No:52271300,52071337)National Key Research and Development Program of China(2022YFC2806501)+1 种基金High-tech Ship Research Projects Sponsored by MIIT(CBG2N21-4-25)Program for Changjiang Scholars and Innovative Research Team in University(Grant No.IRT14R58).
文摘A new hang-off system has been proposed to improve the security of risers in hang-off modes during typhoons.However,efficient anti-typhoon evacuation strategies have not been investigated.Optimiza-tion model and method for the anti-typhoon evacuation strategies should be researched.Therefore,multi-objective functions are proposed based on operation time,evacuation speed stability,and steering stability.An evacuation path model and a dynamic model of risers with the new hang-off system are developed for design variables and constraints.A multi-objective optimization model with high-dimensional variables and complex constraints is established.Finally,a three-stage optimization method based on genetic algorithm,least square method,and the penalty function method is proposed to solve the multi-objective optimization model.Optimization results show that the operation time can be reduced through operation parameter optimization,especially evacuation heading optimization.The optimal anti-typhoon strategy is evacuation with all risers suspended along a variable path when the direction angle is large,while evacuation with all risers suspended along a straight path at another di-rection angle.Besides,the influencing factors on anti-typhoon evacuation strategies indicate that the proposed optimization model and method have strong applicability to working conditions and remarkable optimization effects.
文摘In this paper we proposed an AMH Supply Chain model to obtain optimal solutions for Two-, Three- and Four-Stage for deterministic models. Besides deriving its algebraic solutions, a simple searching method is successfully applied in obtaining optimal total costs and its integer multipliers. Our model has shown promising results in comparison to Equal Cycle Time and other existing ones. The tests focused on obtaining optimal total annual costs and other related details of Two-, Three- and Four-Stage for deterministic models. The results are run under Visual Basic Programming platform using Intel? CoreTM2 Duo T6500 Processor.
文摘To decompose an unbalanced multi-stage logistic system to multipleindependent single-stage logistic systems, a new notion of parameterized interface distribution ispresented. For encoding the logistic pattern on each stage, the Pruefer number is used. With theimproved decoding procedure, any Pruefer number produced stochastically can be decoded to a feasiblelogistic pattern, which can match with the capacities of the nodes of the logistic system. Withthese two innovations, a new modeling method based on parameterized interface distribution and thePriifer number coding is put forward. The corresponding genetic algorithm, named as PIP-GA, can findbetter solutions and require less computational time than st-GA. Although requiring a little moreconsumption of memory, PIP-GA is still an efficient and robust method in the modeling andoptimization of unbalanced multi-stage logistic systems.
基金Supported by the National Natural Science Foundation of China(21376185)
文摘A novel rule-based model for multi-stage multi-product scheduling problem(MMSP)in batch plants with parallel units is proposed.The scheduling problem is decomposed into two sub-problems of order assignment and order sequencing.Firstly,hierarchical scheduling strategy is presented for solving the former sub-problem,where the multi-stage multi-product batch process is divided into multiple sequentially connected single process stages,and then the production of orders are arranged in each single stage by using forward order assignment strategy and backward order assignment strategy respectively according to the feature of scheduling objective.Line-up competition algorithm(LCA)is presented to find out optimal order sequence and order assignment rule,which can minimize total flow time or maximize total weighted process time.Computational results show that the proposed approach can obtain better solutions than those of the literature for all scheduling problems with more than 10 orders.Moreover,with the problem size increasing,the solutions obtained by the proposed approach are improved remarkably.The proposed approach has the potential to solve large size MMSP.
基金supported by National Natural Science Foundation of China (Grant No. 51677058)
文摘Conventional multi-stage constant current charging strategies often use higher multiples of current to charge the battery in pursuit of shorter charging times.However,this leads to an increase in battery temperature,while shortening the charging time.This in turn affects the safety of the charging process.Furthermore,the higher charging currents are not ideal for shortening the charging time in the later stages of charging.To solve the aforementioned problems,in this study,a multi-stage constant current charging strategy is presented.This strategy can shorten the battery charging time by using the increase in battery temperature during the charging process as a constraint,using a genetic algorithm to calculate the charging current value,and investigating the phased approach to charging.Finally,the charging strategy is experimentally validated at different ambient temperatures and different initial SOCs.The experimental results show that the charging strategy proposed in this paper not only reduces the amount of calculations,but also reduces the temperature rise by up to 46.4%and charging time by up to 4.2%under different operating conditions.
文摘The potential to save energy in existing consumer electrical appliances is very high. One of the ways to achieve energy saving and improve energy use awareness is to recognize the energy consumption of individual electrical appliances. To recognize the energy consumption of consumer electrical appliances, the load disaggregation methodology is utilized. Non-intrusive appliance load monitoring (NIALM) is a load disaggrega-tion methodology that disaggregates the sum of power consumption in a single point into the power consumption of individual electrical appliances. In this study, load disaggregation is performed through voltage and current waveform, known as the V-I trajectory. The classification algorithm performs cropping and image pyramid reduction of the V-I trajectory plot template images before utilizing the principal component analysis (PCA) and the k-nearest neighbor (k-NN) algorithm. The novelty of this paper is to establish a systematic approach of load disaggregation through V-I trajectory-based load signature images by utilizing a multi-stage classification algorithm methodol-ogy. The contribution of this paper is in utilizing the “k- value,” the number of closest data points to the nearest neighbor, in the k-NN algorithm to be effective in classification of electrical appliances. The results of the multi-stage classification algorithm implementation have been discussed and the idea on future work has also been proposed.
基金financially supported by the National Science and Technology Major Project of China(Grant No.2017-Ⅱ-0006-0020)National Key Research and Development Project of China(Grant No.2016YFB0200901)+1 种基金National Natural Science Foundation of China(Grant No.51776154)Shaanxi Key Research and Development Project(Grant No.2018KWZ-01)。
文摘Throughflow design has the advantages of less time consumption and large optimization space,and thus is the corner stone of advanced design system of multi-stage axial-flow compressors.The majority of relevant studies were limited to the throughflow inverse designs,and quite few works have been till now devoted to the throughflow optimal designs.In this work,an automatic and rapid throughflow-based optimal design method is proposed for axial-flow compressors in which a throughflow inverse design solver is embedded in optimal genetic algorithm to improve the design efficiency of axial-flow compressor.Two types of design parameters in the throughflow inverse design of axial-flow compressors,i.e.,swirl and shroud curve,are simultaneously used to optimize both the blade shape and flow path.The proposed method is validated by the redesign optimization of the benchmark axial-flow compressor NASA Stage 35,and the CFD predictions show that the throughflow-based optimization leads to 1.18% efficiency benefit at design condition.The proposed method is then utilized to the two-dimensional throughflow optimal design of a large-scale 6.5-stage axial-flow industrial compressor.The optimal design results are confirmed by CFD predictions,indicating that the proposed method can effectively improve the design adiabatic efficiency of the compressors by 1.09% within a few minutes on desk-top computer.Two throughflow design implications are also obtained for advanced axial-flow industrial compressors.This work could enhance the capability of throughflow design method and has engineering application value to explore the throughflow optimization space of multi-stage axial-flow compressors.
基金supported by the National Natural Science Foundation of China(No.62373380).
文摘As the observation data generated by Earth Observation Satellites(EOSs)increase,the joint scheduling of satellite imaging and data transmission has become a bottleneck in EOS resource applications.This study has proposed a three-stage-based hybrid meta-heuristic scheduling algorithm for the Agile Satellite Joint Imaging and Data Transmission Scheduling(ASJIDTS)problem.The original complex problem is decomposed into three distinct phases:joint task allocation for imaging and data transmission,scheduling of imaging tasks,and scheduling data transmission tasks.During the initial phase of joint task allocation,both imaging and data transmission resources are preemptively allocated using a greedy-based strategy,which considers data transmission opportunities,the conflict degree,and the spatial distribution of different resources.Subsequently,the imaging task scheduling phase generates an optimized sequence for imaging tasks.Based on this sequence,a rule-based multi-insertion strategy for the data transmission scheduling phase has been designed,which ensures rapid responsiveness to data transmission tasks.Extensive experiments have been conducted to verify the proposed algorithm.For the scheduling scenarios with 200 tasks,The Hybrid Metaheuristic Algorithm based on Multi-Stage(HMA-MS)shows at least a 14.11%increase in scheduling profit compared to several excellent algorithms.The experimental results validate the superior capability of the proposed algorithm in handling large-scale scheduling problems.
文摘利用杭州市公交线路站点GIS数据和车辆运行GPS数据进行分析,将公交车到站时间分为站点停靠时间和站间行程时间,得到公交车站点之间运行可能总时间的分布概率.通过实际的公交路网结构,定义扩展的公交网络有效路径.在考虑公交线路联合发车频率和根据乘客路径选择的广义成本下,建立出行策略与行程时间不确定下的公交客流分配模型,并将公交线路发车时刻表引入用户均衡模型中,设计了基于扩展网络最短路的Method of Successive Average(MSA)算法求解,通过对两个交通小区间高峰小时的客流分配结果验证模型和算法的有效性.
