具有硬时间窗口约束下同时收发的车辆路径问题(vehicle routing problem with simultaneous pick-up and delivery with hard time windows,VRPSPD with Hard TW)是将产品配送和废物回收统一进行优化的问题。本文研究了一个中心仓库,多...具有硬时间窗口约束下同时收发的车辆路径问题(vehicle routing problem with simultaneous pick-up and delivery with hard time windows,VRPSPD with Hard TW)是将产品配送和废物回收统一进行优化的问题。本文研究了一个中心仓库,多台车辆向具有配送需求和回收需求的客户提供服务,客户存在硬时间窗口要求的车辆运输问题。该问题中,客户的配送需求和回收需求必须同时获得满足,即客户仅允许被访问一次,且需求不可分割,只能由一台车辆提供服务。且客户的硬时间窗口要求必须获得满足。首先将修正后的旅程分割方法应用于硬时间窗口约束下的VRPSPD问题初始解的获得,并利用响应性禁忌搜索算法框架,结合基于多种领域的可变式搜索方法,给出一启发式算法。计算机实验结果表明,该启发式算法在求解VRPSPD with hard TW上是有效的。展开更多
The locally optimal block preconditioned 4-d conjugate gradient method(LOBP4dC G) for the linear response eigenvalue problem was proposed by Bai and Li(2013) and later was extended to the generalized linear response e...The locally optimal block preconditioned 4-d conjugate gradient method(LOBP4dC G) for the linear response eigenvalue problem was proposed by Bai and Li(2013) and later was extended to the generalized linear response eigenvalue problem by Bai and Li(2014). We put forward two improvements to the method: A shifting deflation technique and an idea of extending the search subspace. The deflation technique is able to deflate away converged eigenpairs from future computation, and the idea of extending the search subspace increases convergence rate per iterative step. The resulting algorithm is called the extended LOBP4 dC G(ELOBP4dC G).Numerical results of the ELOBP4 dC G strongly demonstrate the capability of deflation technique and effectiveness the search space extension for solving linear response eigenvalue problems arising from linear response analysis of two molecule systems.展开更多
文摘较低的网络服务响应时间对提升用户体验至关重要.以搜索引擎这一典型的网络服务场景为例,服务提供商应确保网络服务(搜索)响应时间在1 s以内.在实践中,服务响应时间会受到用户浏览器、运营商、页面加载方式等诸多服务属性的影响.为了进行针对性的优化,服务提供商需要找出使服务响应时间过长的规则,即一些属性的组合.然而现有研究工作遇到了3方面挑战:1)搜索日志数据量大;2)搜索日志数据分布不平衡;3)要求泛化度高的规则.因此设计了Miner(multi-dimensional extraction of rules),一种新型服务响应时间异常诊断框架.Miner使用自步采样机制应对第1个挑战和第2个挑战.针对第3个挑战,Miner使用Corels算法挖掘出泛化率高且召回率高的规则.使用2家国内顶级搜索引擎服务提供商的响应时间日志数据评估了Miner性能,结果显示Miner的泛化率和召回率均高于现有方法,并证明了Miner挖掘出的规则可被运维人员采纳并做针对性的优化.
文摘具有硬时间窗口约束下同时收发的车辆路径问题(vehicle routing problem with simultaneous pick-up and delivery with hard time windows,VRPSPD with Hard TW)是将产品配送和废物回收统一进行优化的问题。本文研究了一个中心仓库,多台车辆向具有配送需求和回收需求的客户提供服务,客户存在硬时间窗口要求的车辆运输问题。该问题中,客户的配送需求和回收需求必须同时获得满足,即客户仅允许被访问一次,且需求不可分割,只能由一台车辆提供服务。且客户的硬时间窗口要求必须获得满足。首先将修正后的旅程分割方法应用于硬时间窗口约束下的VRPSPD问题初始解的获得,并利用响应性禁忌搜索算法框架,结合基于多种领域的可变式搜索方法,给出一启发式算法。计算机实验结果表明,该启发式算法在求解VRPSPD with hard TW上是有效的。
基金supported by National Science Foundation of USA(Grant Nos.DMS1522697,CCF-1527091,DMS-1317330 and CCF-1527091)National Natural Science Foundation of China(Grant No.11428104)
文摘The locally optimal block preconditioned 4-d conjugate gradient method(LOBP4dC G) for the linear response eigenvalue problem was proposed by Bai and Li(2013) and later was extended to the generalized linear response eigenvalue problem by Bai and Li(2014). We put forward two improvements to the method: A shifting deflation technique and an idea of extending the search subspace. The deflation technique is able to deflate away converged eigenpairs from future computation, and the idea of extending the search subspace increases convergence rate per iterative step. The resulting algorithm is called the extended LOBP4 dC G(ELOBP4dC G).Numerical results of the ELOBP4 dC G strongly demonstrate the capability of deflation technique and effectiveness the search space extension for solving linear response eigenvalue problems arising from linear response analysis of two molecule systems.