A hybrid carrier(HC) scheme based on weighted-type fractional Fourier transform(WFRFT) has been proposed recently.While most of the works focus on HC scheme's inherent characteristics, little attention is paid to...A hybrid carrier(HC) scheme based on weighted-type fractional Fourier transform(WFRFT) has been proposed recently.While most of the works focus on HC scheme's inherent characteristics, little attention is paid to the WFRFT modulation recognition.In this paper, a new theory is provided to recognize the WFRFT modulation based on higher order cumulants(HOC). First, it is deduced that the optimal WFRFT received order can be obtained through the minimization of 4 th-order cumulants, C_(42). Then, a combinatorial searching algorithm is designed to minimize C_(42).Finally, simulation results show that the designed scheme has a high recognition rate and the combinatorial searching algorithm is effective and reliable.展开更多
The idle time which is part of the order fulfillment time is decided by the number of items in the zone; therefore the item assignment method affects the picking efficiency. Whereas previous studies only focus on the ...The idle time which is part of the order fulfillment time is decided by the number of items in the zone; therefore the item assignment method affects the picking efficiency. Whereas previous studies only focus on the balance of number of kinds of items between different zones but not the number of items and the idle time in each zone. In this paper, an idle factor is proposed to measure the idle time exactly. The idle factor is proven to obey the same vary trend with the idle time, so the object of this problem can be simplified from minimizing idle time to minimizing idle factor. Based on this, the model of item assignment problem in synchronized zone automated order picking system is built. The model is a form of relaxation of parallel machine scheduling problem which had been proven to be NP-complete. To solve the model, a taboo search algorithm is proposed. The main idea of the algorithm is minimizing the greatest idle factor of zones with the 2-exchange algorithm. Finally, the simulation which applies the data collected from a tobacco distribution center is conducted to evaluate the performance of the algorithm. The result verifies the model and shows the algorithm can do a steady work to reduce idle time and the idle time can be reduced by 45.63% on average. This research proposed an approach to measure the idle time in synchronized zone automated order picking system. The approach can improve the picking efficiency significantly and can be seen as theoretical basis when optimizing the synchronized automated order picking systems.展开更多
Ordering based search methods have advantages over graph based search methods for structure learning of Bayesian networks in terms on the efficiency. With the aim of further increasing the accuracy of ordering based s...Ordering based search methods have advantages over graph based search methods for structure learning of Bayesian networks in terms on the efficiency. With the aim of further increasing the accuracy of ordering based search methods, we first propose to increase the search space, which can facilitate escaping from the local optima. We present our search operators with majorizations, which are easy to implement. Experiments show that the proposed algorithm can obtain significantly more accurate results. With regard to the problem of the decrease on efficiency due to the increase of the search space, we then propose to add path priors as constraints into the swap process. We analyze the coefficient which may influence the performance of the proposed algorithm, the experiments show that the constraints can enhance the efficiency greatly, while has little effect on the accuracy. The final experiments show that, compared to other competitive methods, the proposed algorithm can find better solutions while holding high efficiency at the same time on both synthetic and real data sets.展开更多
In this paper, we present a nonmonotone smoothing Newton algorithm for solving the circular cone programming(CCP) problem in which a linear function is minimized or maximized over the intersection of an affine space w...In this paper, we present a nonmonotone smoothing Newton algorithm for solving the circular cone programming(CCP) problem in which a linear function is minimized or maximized over the intersection of an affine space with the circular cone. Based on the relationship between the circular cone and the second-order cone(SOC), we reformulate the CCP problem as the second-order cone problem(SOCP). By extending the nonmonotone line search for unconstrained optimization to the CCP, a nonmonotone smoothing Newton method is proposed for solving the CCP. Under suitable assumptions, the proposed algorithm is shown to be globally and locally quadratically convergent. Some preliminary numerical results indicate the effectiveness of the proposed algorithm for solving the CCP.展开更多
The new method is presented for computing engineering structure reliability by direct searching the next checking point and accelerating convergence based on the analysis of errors in the center point method and borro...The new method is presented for computing engineering structure reliability by direct searching the next checking point and accelerating convergence based on the analysis of errors in the center point method and borrowing ideas form the merits of the other First-Order Second Moment (FOSM) methods. The idea of the direct searching method is constructing a new explicit searching formula to make the new checking point being more closed to the failure surface based on the results of the center point method. The new checking point has steepest descent character because the searching path is the gradient of the approximate surface. An example shows that the method presented in this article has well precision. Although the direct searching formula may not reach the globally optimal point, the error can be controlled owing to the locally optimal plan at each searching step.展开更多
The concepts of ordered code-book and the priority of code-vector are proposedin this paper.The statistical properties of a signal are investigated through its coded sequence.Experimental results are presented which p...The concepts of ordered code-book and the priority of code-vector are proposedin this paper.The statistical properties of a signal are investigated through its coded sequence.Experimental results are presented which provide some insight into the statistical properties ofvector quantized sequences.Based on the given concepts and experimental results,a fast searchmethod for the vector quantization of correlated information sources,such as Gauss-Markovsources,is proposed and has shown its efficiency in simulation results.展开更多
随着电子商务的蓬勃发展,海量客户需求和高频率、多品种、小批量的订单特性为订单拣选业务带来巨大挑战。在物流智能化的趋势下,大量电商企业采用移动机器人拣货系统(Robotic Mobile Fulfillment System,RMFS)进行订单拣选。订单分配和...随着电子商务的蓬勃发展,海量客户需求和高频率、多品种、小批量的订单特性为订单拣选业务带来巨大挑战。在物流智能化的趋势下,大量电商企业采用移动机器人拣货系统(Robotic Mobile Fulfillment System,RMFS)进行订单拣选。订单分配和拣选路径规划是影响仓库订单拣选效率的关键决策。为了提高电商RMFS系统拣选效率,降低仓库运营成本,基于电商企业多订单、多货架、多拣选站下的拣选业务场景,以最小化机器人负载距离为目标,构建订单分配与路径规划联合优化模型,设计两阶段的A*算法和自适应大领域搜索算法(Adaptive Large Neighborhood Search,ALNS),在ALNS算法原有框架的基础上提出新的移除和修复算子以适应订单分配问题,并针对30个不同规模算例进行计算分析。计算结果表明,所提出的优化方法收敛快、性能稳定,能够有效缩短机器人行走距离,相比先到先拣选策略最大可缩短47.6%的机器人负载距离。同时,也可在更短时间内获得与CPLEX求解质量相近的解。尤其是当订单数量增长时,相比CPLEX具有突出时间优势,可以实现电商仓储资源的合理调度和配置,从而为电商企业仓储智能化提供有效决策指导。展开更多
新零售带动传统企业转型,加速了以实体门店作为前置仓的线上订单履行模式的发展。针对订单需求不确定导致的就近门店无法满足订单需求的情况,提出多门店协同下的订单拆分与配送的联合优化问题。通过引入拆单数量限制,缩减问题求解空间,...新零售带动传统企业转型,加速了以实体门店作为前置仓的线上订单履行模式的发展。针对订单需求不确定导致的就近门店无法满足订单需求的情况,提出多门店协同下的订单拆分与配送的联合优化问题。通过引入拆单数量限制,缩减问题求解空间,同时为了减少单独配送导致的路径重叠,采用协同配送的模式整合路径,并通过订单拆分与配送之间的调整优化降低订单履行成本。集成广度优先搜索和局部搜索算法,构造TNILS(top-N&improved local search)混合启发式算法求解问题。在合成数据集的基础上,通过协同配送与单独配送的结果对比,证明了协同配送的有效性及提出算法的可行性。通过与其他算法的实验结果对比,验证TNILS算法的有效性和稳定性。展开更多
针对分数阶PID(fractional order PID,FOPID)控制器的设计问题,提出一种基于自适应布谷鸟搜索算法的分数阶PID控制器参数整定算法。为改进经典布谷鸟算法的收敛速度与计算精度,并充分发挥全局搜索和局部挖掘两者各自的优势,采用了基于...针对分数阶PID(fractional order PID,FOPID)控制器的设计问题,提出一种基于自适应布谷鸟搜索算法的分数阶PID控制器参数整定算法。为改进经典布谷鸟算法的收敛速度与计算精度,并充分发挥全局搜索和局部挖掘两者各自的优势,采用了基于系统误差的自适应步长策略。为保证布谷鸟搜索算法初始化种群的均匀性,采用佳点集法初始化种群替代经典算法中的随机初始化种群。最后对2类系统进行仿真实验,并将实验结果与现有结果进行对比,验证了基于自适应布谷鸟搜索算法的分数阶PID控制器的设计和参数整定方法的有效性和优良性。展开更多
在全球零售额和当天交货量不断增长的时代,实现订单的快速交付和优质分批是影响移动机器人履行系统(Robotic Mobile Fulfillment Systems,RMFS)拣选效率的关键因素.为构造高质量订单分配批次、提升RMFS系统拣选效率,提出融合大邻域搜索...在全球零售额和当天交货量不断增长的时代,实现订单的快速交付和优质分批是影响移动机器人履行系统(Robotic Mobile Fulfillment Systems,RMFS)拣选效率的关键因素.为构造高质量订单分配批次、提升RMFS系统拣选效率,提出融合大邻域搜索的改进差分进化算法(LNS_DE),引入大邻域搜索的破坏与修复思想及一批基于随机、基于最大代价贡献和基于集中批次的移除算子以及新的插入算子组件,以最小化订单总延迟时间为目标建立订单分批优化模型,并针对不同订单规模算例进行实验仿真.仿真结果表明,所提出的订单分批优化算法较差分进化算法(DE)相比求解质量更优,性能更稳定、收敛速度更快,尤其当订单数量增大时,LNS_DE算法解的平均值优化比例不断扩大,这为提高RMFS系统拣选效率,实现订单快速响应提供有效决策指导.展开更多
基金supported by the National Natural Science Foundation of China(6127125061571460)
文摘A hybrid carrier(HC) scheme based on weighted-type fractional Fourier transform(WFRFT) has been proposed recently.While most of the works focus on HC scheme's inherent characteristics, little attention is paid to the WFRFT modulation recognition.In this paper, a new theory is provided to recognize the WFRFT modulation based on higher order cumulants(HOC). First, it is deduced that the optimal WFRFT received order can be obtained through the minimization of 4 th-order cumulants, C_(42). Then, a combinatorial searching algorithm is designed to minimize C_(42).Finally, simulation results show that the designed scheme has a high recognition rate and the combinatorial searching algorithm is effective and reliable.
基金Supported by Independent Innovation Foundation of Shandong University of China(Grant No.2013GN007)
文摘The idle time which is part of the order fulfillment time is decided by the number of items in the zone; therefore the item assignment method affects the picking efficiency. Whereas previous studies only focus on the balance of number of kinds of items between different zones but not the number of items and the idle time in each zone. In this paper, an idle factor is proposed to measure the idle time exactly. The idle factor is proven to obey the same vary trend with the idle time, so the object of this problem can be simplified from minimizing idle time to minimizing idle factor. Based on this, the model of item assignment problem in synchronized zone automated order picking system is built. The model is a form of relaxation of parallel machine scheduling problem which had been proven to be NP-complete. To solve the model, a taboo search algorithm is proposed. The main idea of the algorithm is minimizing the greatest idle factor of zones with the 2-exchange algorithm. Finally, the simulation which applies the data collected from a tobacco distribution center is conducted to evaluate the performance of the algorithm. The result verifies the model and shows the algorithm can do a steady work to reduce idle time and the idle time can be reduced by 45.63% on average. This research proposed an approach to measure the idle time in synchronized zone automated order picking system. The approach can improve the picking efficiency significantly and can be seen as theoretical basis when optimizing the synchronized automated order picking systems.
基金supported by the National Natural Science Fundation of China(61573285)the Doctoral Fundation of China(2013ZC53037)
文摘Ordering based search methods have advantages over graph based search methods for structure learning of Bayesian networks in terms on the efficiency. With the aim of further increasing the accuracy of ordering based search methods, we first propose to increase the search space, which can facilitate escaping from the local optima. We present our search operators with majorizations, which are easy to implement. Experiments show that the proposed algorithm can obtain significantly more accurate results. With regard to the problem of the decrease on efficiency due to the increase of the search space, we then propose to add path priors as constraints into the swap process. We analyze the coefficient which may influence the performance of the proposed algorithm, the experiments show that the constraints can enhance the efficiency greatly, while has little effect on the accuracy. The final experiments show that, compared to other competitive methods, the proposed algorithm can find better solutions while holding high efficiency at the same time on both synthetic and real data sets.
基金supported by the National Natural Science Foundation of China(11401126,71471140 and 11361018)Guangxi Natural Science Foundation(2016GXNSFBA380102 and 2014GXNSFFA118001)+2 种基金Guangxi Key Laboratory of Cryptography and Information Security(GCIS201618)Guangxi Key Laboratory of Automatic Detecting Technology and Instruments(YQ15112 and YQ16112)China
文摘In this paper, we present a nonmonotone smoothing Newton algorithm for solving the circular cone programming(CCP) problem in which a linear function is minimized or maximized over the intersection of an affine space with the circular cone. Based on the relationship between the circular cone and the second-order cone(SOC), we reformulate the CCP problem as the second-order cone problem(SOCP). By extending the nonmonotone line search for unconstrained optimization to the CCP, a nonmonotone smoothing Newton method is proposed for solving the CCP. Under suitable assumptions, the proposed algorithm is shown to be globally and locally quadratically convergent. Some preliminary numerical results indicate the effectiveness of the proposed algorithm for solving the CCP.
文摘The new method is presented for computing engineering structure reliability by direct searching the next checking point and accelerating convergence based on the analysis of errors in the center point method and borrowing ideas form the merits of the other First-Order Second Moment (FOSM) methods. The idea of the direct searching method is constructing a new explicit searching formula to make the new checking point being more closed to the failure surface based on the results of the center point method. The new checking point has steepest descent character because the searching path is the gradient of the approximate surface. An example shows that the method presented in this article has well precision. Although the direct searching formula may not reach the globally optimal point, the error can be controlled owing to the locally optimal plan at each searching step.
文摘The concepts of ordered code-book and the priority of code-vector are proposedin this paper.The statistical properties of a signal are investigated through its coded sequence.Experimental results are presented which provide some insight into the statistical properties ofvector quantized sequences.Based on the given concepts and experimental results,a fast searchmethod for the vector quantization of correlated information sources,such as Gauss-Markovsources,is proposed and has shown its efficiency in simulation results.
文摘随着电子商务的蓬勃发展,海量客户需求和高频率、多品种、小批量的订单特性为订单拣选业务带来巨大挑战。在物流智能化的趋势下,大量电商企业采用移动机器人拣货系统(Robotic Mobile Fulfillment System,RMFS)进行订单拣选。订单分配和拣选路径规划是影响仓库订单拣选效率的关键决策。为了提高电商RMFS系统拣选效率,降低仓库运营成本,基于电商企业多订单、多货架、多拣选站下的拣选业务场景,以最小化机器人负载距离为目标,构建订单分配与路径规划联合优化模型,设计两阶段的A*算法和自适应大领域搜索算法(Adaptive Large Neighborhood Search,ALNS),在ALNS算法原有框架的基础上提出新的移除和修复算子以适应订单分配问题,并针对30个不同规模算例进行计算分析。计算结果表明,所提出的优化方法收敛快、性能稳定,能够有效缩短机器人行走距离,相比先到先拣选策略最大可缩短47.6%的机器人负载距离。同时,也可在更短时间内获得与CPLEX求解质量相近的解。尤其是当订单数量增长时,相比CPLEX具有突出时间优势,可以实现电商仓储资源的合理调度和配置,从而为电商企业仓储智能化提供有效决策指导。
文摘新零售带动传统企业转型,加速了以实体门店作为前置仓的线上订单履行模式的发展。针对订单需求不确定导致的就近门店无法满足订单需求的情况,提出多门店协同下的订单拆分与配送的联合优化问题。通过引入拆单数量限制,缩减问题求解空间,同时为了减少单独配送导致的路径重叠,采用协同配送的模式整合路径,并通过订单拆分与配送之间的调整优化降低订单履行成本。集成广度优先搜索和局部搜索算法,构造TNILS(top-N&improved local search)混合启发式算法求解问题。在合成数据集的基础上,通过协同配送与单独配送的结果对比,证明了协同配送的有效性及提出算法的可行性。通过与其他算法的实验结果对比,验证TNILS算法的有效性和稳定性。
文摘针对分数阶PID(fractional order PID,FOPID)控制器的设计问题,提出一种基于自适应布谷鸟搜索算法的分数阶PID控制器参数整定算法。为改进经典布谷鸟算法的收敛速度与计算精度,并充分发挥全局搜索和局部挖掘两者各自的优势,采用了基于系统误差的自适应步长策略。为保证布谷鸟搜索算法初始化种群的均匀性,采用佳点集法初始化种群替代经典算法中的随机初始化种群。最后对2类系统进行仿真实验,并将实验结果与现有结果进行对比,验证了基于自适应布谷鸟搜索算法的分数阶PID控制器的设计和参数整定方法的有效性和优良性。
文摘在全球零售额和当天交货量不断增长的时代,实现订单的快速交付和优质分批是影响移动机器人履行系统(Robotic Mobile Fulfillment Systems,RMFS)拣选效率的关键因素.为构造高质量订单分配批次、提升RMFS系统拣选效率,提出融合大邻域搜索的改进差分进化算法(LNS_DE),引入大邻域搜索的破坏与修复思想及一批基于随机、基于最大代价贡献和基于集中批次的移除算子以及新的插入算子组件,以最小化订单总延迟时间为目标建立订单分批优化模型,并针对不同订单规模算例进行实验仿真.仿真结果表明,所提出的订单分批优化算法较差分进化算法(DE)相比求解质量更优,性能更稳定、收敛速度更快,尤其当订单数量增大时,LNS_DE算法解的平均值优化比例不断扩大,这为提高RMFS系统拣选效率,实现订单快速响应提供有效决策指导.