To improve the global search ability of particle swarm optimization （PSO）, a multi-population PSO based on pyramid model （PPSO） is presented. Then, it is applied to solve the layout optimization problems against t...To improve the global search ability of particle swarm optimization （PSO）, a multi-population PSO based on pyramid model （PPSO） is presented. Then, it is applied to solve the layout optimization problems against the background of an international commercial communication satellite （INTELSAT-Ⅲ） module. Three improvements are developed, including multi-population search based on pyramid model, adaptive collision avoidance among particles, and mutation of degraded particles. In the numerical examples of the layout design of this simplified satellite module, the performance of PPSO is compared to global version PSO and local version PSO （ring and Neumann PSO）. The results show that PPSO has higher computational accuracy, efficiency and success ratio.展开更多
The layout optimization design of a natural gas gathering pipeline network is a multi-objective optimization problem because the extant theories are unable to meet the different decision preferences in scheme design,w...The layout optimization design of a natural gas gathering pipeline network is a multi-objective optimization problem because the extant theories are unable to meet the different decision preferences in scheme design,which restricts the intelligentization of gas gathering pipeline layout optimization.Currently,there are no generic design studies on the loop-star pipeline network.Therefore,this paper proposes a generic layout optimization model containing a large number of discrete and continuous variables,such as pipe connection relationships,pipe sizes,pipe length,and pipe specifications.In the solution section,drawing inspiration from the hormone regulation mechanism and local foraging rule in bionics,an improved particle swarm optimization algorithm based on hormone regulation(HRPSO)is proposed,and it obtains the favorable parameters range of the HRPSO algorithm.The results illustrate that the HRPSO algorithm exhibits convergence to the global optimum with a probability of 1.In comparison to manual design,the comprehensive costs of the optimized scheme are saved by 22.71%with the HRPSO algorithm.Compared to the four PSO variants in the paper,it can save costs by 5.38%,4.95%,4.09%,and 3.65%,respectively.展开更多
Thisworkpresentsahighlyefficientapproachforbroadbandmodelingofmillimeter-waveCMOSFETs with gate width scalability by using pre-modeled cells. Only a few devices with varied gate width are required to be measured and m...Thisworkpresentsahighlyefficientapproachforbroadbandmodelingofmillimeter-waveCMOSFETs with gate width scalability by using pre-modeled cells. Only a few devices with varied gate width are required to be measured and modeled with fixed models, and later used as pre-modeled cells. Then a target device with the desired gate width is constructed by choosing appropriate cells and connecting them with a wiring network. The corresponding scalable model is constructed by incorporating the fixed models of the cells used in the target device and the scalable model of the connection wires. The proposed approach is validated by experiments on 65-nm CMOS process up to 40 GHz and across a wide range of gate widths.展开更多
基金This project is supported by National Natural Science Foundation of China (No.50275019, No.50335040, No.50575031).
文摘To improve the global search ability of particle swarm optimization （PSO）, a multi-population PSO based on pyramid model （PPSO） is presented. Then, it is applied to solve the layout optimization problems against the background of an international commercial communication satellite （INTELSAT-Ⅲ） module. Three improvements are developed, including multi-population search based on pyramid model, adaptive collision avoidance among particles, and mutation of degraded particles. In the numerical examples of the layout design of this simplified satellite module, the performance of PPSO is compared to global version PSO and local version PSO （ring and Neumann PSO）. The results show that PPSO has higher computational accuracy, efficiency and success ratio.
基金funding provided by the National Natural Science Foundation of China,China(Grant No.52104065,52074090)the Heilongjiang Provincial Natural Science Foundation of China,China(Grant No.LH2021E019)+3 种基金the China Postdoctoral Science Foundation,China(Grant Nos.2022T150089 and 2020M681064)the Heilongjiang Postdoctoral Foundation,China(Grant No.LBH-Z20101)the Scientific Research Personnel Training Foundation of Northeast Petroleum University,China(Grant No.XNYXLY202103)Northeast Petroleum University Scientific Research Foundation,China(Grant No.2019KQ54).
文摘The layout optimization design of a natural gas gathering pipeline network is a multi-objective optimization problem because the extant theories are unable to meet the different decision preferences in scheme design,which restricts the intelligentization of gas gathering pipeline layout optimization.Currently,there are no generic design studies on the loop-star pipeline network.Therefore,this paper proposes a generic layout optimization model containing a large number of discrete and continuous variables,such as pipe connection relationships,pipe sizes,pipe length,and pipe specifications.In the solution section,drawing inspiration from the hormone regulation mechanism and local foraging rule in bionics,an improved particle swarm optimization algorithm based on hormone regulation(HRPSO)is proposed,and it obtains the favorable parameters range of the HRPSO algorithm.The results illustrate that the HRPSO algorithm exhibits convergence to the global optimum with a probability of 1.In comparison to manual design,the comprehensive costs of the optimized scheme are saved by 22.71%with the HRPSO algorithm.Compared to the four PSO variants in the paper,it can save costs by 5.38%,4.95%,4.09%,and 3.65%,respectively.
基金Project supported by the Major State Basic Research Development Program of China(No.2010CB327403)
文摘Thisworkpresentsahighlyefficientapproachforbroadbandmodelingofmillimeter-waveCMOSFETs with gate width scalability by using pre-modeled cells. Only a few devices with varied gate width are required to be measured and modeled with fixed models, and later used as pre-modeled cells. Then a target device with the desired gate width is constructed by choosing appropriate cells and connecting them with a wiring network. The corresponding scalable model is constructed by incorporating the fixed models of the cells used in the target device and the scalable model of the connection wires. The proposed approach is validated by experiments on 65-nm CMOS process up to 40 GHz and across a wide range of gate widths.
