In order to achieve dynamical optimization of mobility load balancing,we analyze the conflict between mobility load balancing and mobility robustness optimization caused by the improper operation of handover parameter...In order to achieve dynamical optimization of mobility load balancing,we analyze the conflict between mobility load balancing and mobility robustness optimization caused by the improper operation of handover parameters.To this end,a method of Handover Parameters Adjustment for Conflict Avoidance(HPACA)is proposed.Considering the movement of users,HPCAC can dynamically adjust handover range to optimize the mobility load balancing.The movement of users is an important factor of handover,which has a dramatic impact on system performance.The numerical evaluation results show the proposed approach outperforms the existing method in terms of throughput,call blocking ratio,load balancing index,radio link failure ratio,ping-pong handover ratio and call dropping ratio.展开更多
A modified harmony search algorithm with co-evolutional control parameters(DEHS), applied through differential evolution optimization, is proposed. In DEHS, two control parameters, i.e., harmony memory considering rat...A modified harmony search algorithm with co-evolutional control parameters(DEHS), applied through differential evolution optimization, is proposed. In DEHS, two control parameters, i.e., harmony memory considering rate and pitch adjusting rate, are encoded as a symbiotic individual of an original individual(i.e., harmony vector). Harmony search operators are applied to evolving the original population. DE is applied to co-evolving the symbiotic population based on feedback information from the original population. Thus, with the evolution of the original population in DEHS, the symbiotic population is dynamically and self-adaptively adjusted, and real-time optimum control parameters are obtained. The proposed DEHS algorithm has been applied to various benchmark functions and two typical dynamic optimization problems. The experimental results show that the performance of the proposed algorithm is better than that of other HS variants. Satisfactory results are obtained in the application.展开更多
基金supported by the National Natural Science Foundation of China under Grant No.61071118the National Basic Research Program of China(973 Program)under Grant No.2012CB316004+1 种基金Special Fund of Chongqing Key Laboratory(CSTC)Chongqing Municipal Education Commission’s Science and Technology Research Project under Grant No.KJ111506
文摘In order to achieve dynamical optimization of mobility load balancing,we analyze the conflict between mobility load balancing and mobility robustness optimization caused by the improper operation of handover parameters.To this end,a method of Handover Parameters Adjustment for Conflict Avoidance(HPACA)is proposed.Considering the movement of users,HPCAC can dynamically adjust handover range to optimize the mobility load balancing.The movement of users is an important factor of handover,which has a dramatic impact on system performance.The numerical evaluation results show the proposed approach outperforms the existing method in terms of throughput,call blocking ratio,load balancing index,radio link failure ratio,ping-pong handover ratio and call dropping ratio.
基金Project(2013CB733605)supported by the National Basic Research Program of ChinaProject(21176073)supported by the National Natural Science Foundation of China
文摘A modified harmony search algorithm with co-evolutional control parameters(DEHS), applied through differential evolution optimization, is proposed. In DEHS, two control parameters, i.e., harmony memory considering rate and pitch adjusting rate, are encoded as a symbiotic individual of an original individual(i.e., harmony vector). Harmony search operators are applied to evolving the original population. DE is applied to co-evolving the symbiotic population based on feedback information from the original population. Thus, with the evolution of the original population in DEHS, the symbiotic population is dynamically and self-adaptively adjusted, and real-time optimum control parameters are obtained. The proposed DEHS algorithm has been applied to various benchmark functions and two typical dynamic optimization problems. The experimental results show that the performance of the proposed algorithm is better than that of other HS variants. Satisfactory results are obtained in the application.
文摘针对深部采选充一体化矿井内采煤-充填空间协调布局问题,采用德尔菲-层次分析法确定了影响采、充空间布局各因素的相对权重,推导得到了采、充空间布置参数与工艺参数的动态调整方程,模拟研究了适用于“控、防、留”3类工程需求的采-充空间布局策略,构建了采-充空间优化布局决策模型.结果表明:选用采-充空间集中布置、局部密实充填方案时,地表沉陷控制与冲击地压防治效果最好;基于“以采定充”、采充空间分散布置的限定条件,新巨龙煤矿井下需同时布置1303N-1,1304N两个充填面以满足伴生矸石就地消化需求,且整体充实率不应低于55%,同时,为确保留巷围岩稳定,巷旁加强充填带的充实率需达80%以上、宽度不得小于10 m.
