With the rapid development and furthering of higher education, most Chinese colleges have carried out large-scale enrollment program, which is a necessary improvement toward higher education reform. Meanwhile, the inc...With the rapid development and furthering of higher education, most Chinese colleges have carried out large-scale enrollment program, which is a necessary improvement toward higher education reform. Meanwhile, the increasing number of students has posed new problems and requirements for the old teaching method： the English teachers are facing more students and larger classes. In Zhejiang University, City College （ZUCC） the credit system and course selection has challenged the English teachers on a higher level. Every English teacher is facing classes of more than 40 students from various departments with sharp contrast among individual students in their English proficiency level and local background. How can every student actively participate in teaching activity so as to achieve better performance in English class？ Many teachers, therefore, have adopted team activity and cooperative teaching method to stimulate student participation in class. Inspired by the management theory to optimize student groups into independent teams, the concept of team construction and team management has been introduced into College English Teaching in ZUCC, which has given new meaning to team activity--it will become an interdisciplinary teaching method with its own feature.展开更多
Purpose–The purpose of this paper is to propose a novel improved teaching and learning-based algorithm(TLBO)to enhance its convergence ability and solution accuracy,making it more suitable for solving large-scale opt...Purpose–The purpose of this paper is to propose a novel improved teaching and learning-based algorithm(TLBO)to enhance its convergence ability and solution accuracy,making it more suitable for solving large-scale optimization issues.Design/methodology/approach–Utilizing multiple cooperation mechanisms in teaching and learning processes,an improved TBLO named CTLBO(collectivism teaching-learning-based optimization)is developed.This algorithm introduces a new preparation phase before the teaching and learning phases and applies multiple teacher–learner cooperation strategies in teaching and learning processes.Applying modularizationidea,based on the configuration structure of operators ofCTLBO,six variants ofCTLBOare constructed.Foridentifying the best configuration,30 general benchmark functions are tested.Then,three experiments using CEC2020(2020 IEEE Conference on Evolutionary Computation)-constrained optimization problems are conducted to compare CTLBO with other algorithms.At last,a large-scale industrial engineering problem is taken as the application case.Findings–Experiment with 30 general unconstrained benchmark functions indicates that CTLBO-c is the best configuration of all variants of CTLBO.Three experiments using CEC2020-constrained optimization problems show that CTLBO is one powerful algorithm for solving large-scale constrained optimization problems.The application case of industrial engineering problem shows that CTLBO and its variant CTLBO-c can effectively solve the large-scale real problem,while the accuracies of TLBO and other meta-heuristic algorithm are far lower than CLTBO and CTLBO-c,revealing that CTLBO and its variants can far outperform other algorithms.CTLBO is an excellent algorithm for solving large-scale complex optimization issues.Originality/value–The innovation of this paper lies in the improvement strategies in changing the original TLBO with two-phase teaching–learning mechanism to a new algorithm CTLBO with three-phase multiple cooperation teaching–learning mechanism,self-learning mechanism in teaching and group teaching mechanism.CTLBO has important application value in solving large-scale optimization problems.展开更多
文摘With the rapid development and furthering of higher education, most Chinese colleges have carried out large-scale enrollment program, which is a necessary improvement toward higher education reform. Meanwhile, the increasing number of students has posed new problems and requirements for the old teaching method： the English teachers are facing more students and larger classes. In Zhejiang University, City College （ZUCC） the credit system and course selection has challenged the English teachers on a higher level. Every English teacher is facing classes of more than 40 students from various departments with sharp contrast among individual students in their English proficiency level and local background. How can every student actively participate in teaching activity so as to achieve better performance in English class？ Many teachers, therefore, have adopted team activity and cooperative teaching method to stimulate student participation in class. Inspired by the management theory to optimize student groups into independent teams, the concept of team construction and team management has been introduced into College English Teaching in ZUCC, which has given new meaning to team activity--it will become an interdisciplinary teaching method with its own feature.
基金This research is funded by the National Natural Science Foundation of China(#71772191).
文摘Purpose–The purpose of this paper is to propose a novel improved teaching and learning-based algorithm(TLBO)to enhance its convergence ability and solution accuracy,making it more suitable for solving large-scale optimization issues.Design/methodology/approach–Utilizing multiple cooperation mechanisms in teaching and learning processes,an improved TBLO named CTLBO(collectivism teaching-learning-based optimization)is developed.This algorithm introduces a new preparation phase before the teaching and learning phases and applies multiple teacher–learner cooperation strategies in teaching and learning processes.Applying modularizationidea,based on the configuration structure of operators ofCTLBO,six variants ofCTLBOare constructed.Foridentifying the best configuration,30 general benchmark functions are tested.Then,three experiments using CEC2020(2020 IEEE Conference on Evolutionary Computation)-constrained optimization problems are conducted to compare CTLBO with other algorithms.At last,a large-scale industrial engineering problem is taken as the application case.Findings–Experiment with 30 general unconstrained benchmark functions indicates that CTLBO-c is the best configuration of all variants of CTLBO.Three experiments using CEC2020-constrained optimization problems show that CTLBO is one powerful algorithm for solving large-scale constrained optimization problems.The application case of industrial engineering problem shows that CTLBO and its variant CTLBO-c can effectively solve the large-scale real problem,while the accuracies of TLBO and other meta-heuristic algorithm are far lower than CLTBO and CTLBO-c,revealing that CTLBO and its variants can far outperform other algorithms.CTLBO is an excellent algorithm for solving large-scale complex optimization issues.Originality/value–The innovation of this paper lies in the improvement strategies in changing the original TLBO with two-phase teaching–learning mechanism to a new algorithm CTLBO with three-phase multiple cooperation teaching–learning mechanism,self-learning mechanism in teaching and group teaching mechanism.CTLBO has important application value in solving large-scale optimization problems.
