Teaching Learning Based Optimization (TLBO)是一种population method,它基于以下知识:与学生共享教室的老师会想办法提高班级的知识水平。 此外,通过班级学生的平均value of the qualification评估学生。同时,学生之间的互动学习可以改善求解结果。 population由一组学生组成,所提供的科目由变量构成,适应度与学生的学习结果相...
具有有限回程容量的无线小单元基站sBS中缓存内容的优化问题研究。 sBS具有大型缓存内存,并通过向其覆盖区域内的用户提供高数据率内容来提供内容级选择性卸载。sBS内容控制器(CC)的目标是将最流行的内容存储在sBS缓存内存中,以便可以直接从sBS获取最大数量的数据,而不依赖于峰值流量期间有限的回程资源。如果提前知道流行...
Robust optimization (RO) is a common approach to tractably obtain safeguarding solutions for optimization problems with uncertain constraints. In this paper, we study a statistical framework to integrate data into RO, based on learning a prediction set using (combinations of) geometric shapes that ar...
John, N., Janamala, V., Rodrigues, J. (2023). Teaching Learning-Based Optimization with Learning Enthusiasm Mechanism for Optimal Control of PV Inverters in Utility Grids for Techno-Economic Goals. In: Shetty, N.R., Patnaik, L.M., Prasad, N.H. (eds) Emerging Research in Computing, In...
To navigate this learning problem, we present an algorithm combining stochastic optimization and the penalty method (StoPM). The convergence of StoPM using the conservative gradient is proved. Empirical validation of our framework is conducted through extensive numerical experiments across a diverse set...
In this paper, a new efficient optimization algorithm called Teaching-Learning-Based Optimization (TLBO) is used for the least weight design of trusses with continuous design variables. The TLBO algorithm is based on the effect of the influence of a teacher on the output of learners in a class...
Moreover, a multi-objective teachinglearning-based optimization algorithm is proposed, and two objectives to minimize carbon emissions and operation time are considered simultaneously. Cutting parameters were optimized by the proposed algorithm. Finally, the analytic hierarchy process was used to determine ...
Combinatorial optimization problems are ubiquitous and computationally hard to solve in general. Quantum approximate optimization algorithm (QAOA), one of the most representative quantum-classical hybrid algorithms, is designed to solve combinatorial opt
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论文笔记:Meta-Learning-Based Deep Reinforcement Learningfor Multiobjective Optimization Problems 1.研究内容: 多目标组合优化问题: 在现实生活中,优化问题往往有不止一个维度,这些问题可以被建模为多目标优化问题,目标是获得一个种群大小的解集。 minx∈XF(x)=(f1(x),f2(x),...,fm(x))T 文章...