The constriction factor method (CFM) is a new variation of the basic particle swarm optimization (PSO), which has relatively better convergent nature. The effects of the major parameters on CFM were systematically inv...The constriction factor method (CFM) is a new variation of the basic particle swarm optimization (PSO), which has relatively better convergent nature. The effects of the major parameters on CFM were systematically investigated based on some benchmark functions. The constriction factor, velocity constraint, and population size all have significant impact on the per- formance of CFM for PSO. The constriction factor and velocity constraint have optimal values in practical application, and im- proper choice of these factors will lead to bad results. Increasing population size can improve the solution quality, although the computing time will be longer. The characteristics of CFM parameters are described and guidelines for determining parameter values are given in this paper.展开更多
This article presents a study on profit optimization of external cylindrical grinding. In the optimization problem, the influences of several grinding process parameters such as the initial grinding wheel diameter, th...This article presents a study on profit optimization of external cylindrical grinding. In the optimization problem, the influences of several grinding process parameters such as the initial grinding wheel diameter, the wheel life, the total dressing depth as well as the effect of many cost components were investigated. A model for determination of optimum exchanged grinding wheel diameter was proposed. With this optimum diameter, a new and effective way of using the grinding wheel was proposed.展开更多
基金Project (No. 20276063) supported by the National Natural Sci-ence Foundation of China
文摘The constriction factor method (CFM) is a new variation of the basic particle swarm optimization (PSO), which has relatively better convergent nature. The effects of the major parameters on CFM were systematically investigated based on some benchmark functions. The constriction factor, velocity constraint, and population size all have significant impact on the per- formance of CFM for PSO. The constriction factor and velocity constraint have optimal values in practical application, and im- proper choice of these factors will lead to bad results. Increasing population size can improve the solution quality, although the computing time will be longer. The characteristics of CFM parameters are described and guidelines for determining parameter values are given in this paper.
文摘This article presents a study on profit optimization of external cylindrical grinding. In the optimization problem, the influences of several grinding process parameters such as the initial grinding wheel diameter, the wheel life, the total dressing depth as well as the effect of many cost components were investigated. A model for determination of optimum exchanged grinding wheel diameter was proposed. With this optimum diameter, a new and effective way of using the grinding wheel was proposed.
