A new efficient optimization method, called ‘Teaching–Learning-Based Optimization (TLBO)’, is proposed in this paper for the optimization of mechanical design problems. This method works on the effect of influence of a teacher on learners. Like other nature-inspired algorithms, TLBO is also a population-based method and uses a population of solutions to proceed to the global solution. The popul...

Total Potential Optimization using Meta-heuristic Algorithms (TPO/MA) is an analyses technique developed by implementation of metaheuristic algorithms for finding an equilibrium state of a structural system according to the well-known principle of minimum total potential energy. According to this theory, a system is in equilibrium state only if total potential energy of it which means sum of th...

conclusions the findings of this study can be useful in competency development of health care management students. this approach paves the way towards effective and practical learning for these students to prepare them for opportunities in their future market job. background determination of the individual differences and students’ learning style are essential factors in the selection of proper...

background and purpose: small group teaching(sgt) in is a known method for developing intellectual skills, changing attitudes and encouraging the taking of responsibilities for learning. this study was an attempt to compare students’ attitudes and knowledge scores on sgt and lecture -based teaching (lbt). methods: 22 first year medical students were enrolled in a course using two methods (lectu...

: nowadays, organizations are faced with a multitude of project and investment opportunities. despite the importance of various criteria, complexity of multi-objective models and weakness of optimization algorithms often compelled manager to limit the selection criteria or only suffice to financial objects. in this paper, it is endeavored to extend selection criteria by using an efficient optim...

What if there is a teacher who knows the learning goal and wants to design good training data for a machine learner? We propose an optimal teaching framework aimed at learners who employ Bayesian models. Our framework is expressed as an optimization problem over teaching examples that balance the future loss of the learner and the effort of the teacher. This optimization problem is in general h...