This work proposes an improved multi-objective slime mould algorithm, called IBMSMA, for solving the multi-objective truss optimization problem. In IBMSMA, the chaotic grouping mechanism and dynamic regrouping strateg...This work proposes an improved multi-objective slime mould algorithm, called IBMSMA, for solving the multi-objective truss optimization problem. In IBMSMA, the chaotic grouping mechanism and dynamic regrouping strategy are employed to improve population diversity;the shift density estimation is used to assess the superiority of search agents and to provide selection pressure for population evolution;and the Pareto external archive is utilized to maintain the convergence and distribution of the non-dominated solution set. To evaluate the performance of IBMSMA, it is applied to eight multi-objective truss optimization problems. The results obtained by IBMSMA are compared with other 14 well-known optimization algorithms on hypervolume, inverted generational distance and spacing-to-extent indicators. The Wilcoxon statistical test and Friedman ranking are used for statistical analysis. The results of this study reveal that IBMSMA can find the Pareto front with better convergence and diversity in less time than state-of-the-art algorithms, demonstrating its capability in tackling large-scale engineering design problems.展开更多
This paper deals with a multi-objective parameter optimization framework for energy saving in injection molding process.It combines an experimental design by Taguchi's method,a process analysis by analysis of vari...This paper deals with a multi-objective parameter optimization framework for energy saving in injection molding process.It combines an experimental design by Taguchi's method,a process analysis by analysis of variance(ANOVA),a process modeling algorithm by artificial neural network(ANN),and a multi-objective parameter optimization algorithm by genetic algorithm(GA)-based lexicographic method.Local and global Pareto analyses show the trade-off between product quality and energy consumption.The implementation of the proposed framework can reduce the energy consumption significantly in laboratory scale tests,and at the same time,the product quality can meet the pre-determined requirements.展开更多
Sacrificial multi-piece molds can be used for producing complex parts. To obtain the optimal design of molds automatically, a multi-objective optimal approach is proposed. Mold pieces number, material utilization and ...Sacrificial multi-piece molds can be used for producing complex parts. To obtain the optimal design of molds automatically, a multi-objective optimal approach is proposed. Mold pieces number, material utilization and partitioning area are taken as the objective functions, and the machinability of each mold piece is taken as constraint condition. Genetic algorithm (GA) is adopted to realize global optimization of partitioning process. Each mold piece in optimal scheme can be manufactured by milling and drilling operations, which reduce the tooling cost and shorten product cycle obviously. Using the proposed approach, mold design can be significantly automated for making complex parts.展开更多
基金supported by the National Science Foundation of China under Grant No.U21A20464,62066005Innovation Project of Guangxi University for Nationalities Graduate Education under Grant gxun-chxs2021058.
文摘This work proposes an improved multi-objective slime mould algorithm, called IBMSMA, for solving the multi-objective truss optimization problem. In IBMSMA, the chaotic grouping mechanism and dynamic regrouping strategy are employed to improve population diversity;the shift density estimation is used to assess the superiority of search agents and to provide selection pressure for population evolution;and the Pareto external archive is utilized to maintain the convergence and distribution of the non-dominated solution set. To evaluate the performance of IBMSMA, it is applied to eight multi-objective truss optimization problems. The results obtained by IBMSMA are compared with other 14 well-known optimization algorithms on hypervolume, inverted generational distance and spacing-to-extent indicators. The Wilcoxon statistical test and Friedman ranking are used for statistical analysis. The results of this study reveal that IBMSMA can find the Pareto front with better convergence and diversity in less time than state-of-the-art algorithms, demonstrating its capability in tackling large-scale engineering design problems.
基金(Nos. 20806040,61073059 and 61034005) supported by the National Natural Science Foundation of China
文摘This paper deals with a multi-objective parameter optimization framework for energy saving in injection molding process.It combines an experimental design by Taguchi's method,a process analysis by analysis of variance(ANOVA),a process modeling algorithm by artificial neural network(ANN),and a multi-objective parameter optimization algorithm by genetic algorithm(GA)-based lexicographic method.Local and global Pareto analyses show the trade-off between product quality and energy consumption.The implementation of the proposed framework can reduce the energy consumption significantly in laboratory scale tests,and at the same time,the product quality can meet the pre-determined requirements.
文摘Sacrificial multi-piece molds can be used for producing complex parts. To obtain the optimal design of molds automatically, a multi-objective optimal approach is proposed. Mold pieces number, material utilization and partitioning area are taken as the objective functions, and the machinability of each mold piece is taken as constraint condition. Genetic algorithm (GA) is adopted to realize global optimization of partitioning process. Each mold piece in optimal scheme can be manufactured by milling and drilling operations, which reduce the tooling cost and shorten product cycle obviously. Using the proposed approach, mold design can be significantly automated for making complex parts.
