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Brain Storming Incorporated Teaching-Learning-Based Algorithm with Application to Electric Power Dispatch

机译:头脑风暴结合教学法的算法及其在电力调度中的应用

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This paper intends to incorporate a brain storming mechanism into the existing Teaching-Learning-Based Optimization (TLBO) algorithm. The potential solutions of TLBO evolve using the primitive steps that are maintained between the acts of teaching and learning. Another novel algorithm, Brain Storm Optimization (BSO) sticks to the philosophy of interchange of ideas by a team to develop as a whole. The brain storming methods from BSO are introduced into the working of TLBO and applied to a well-studied electric power dispatch problem of high intricacy. The results are compared to best of the existing solutions to demonstrate the efficacy of the proposed hybrid algorithm.
机译:本文打算将脑力激荡机制纳入现有的基于教学-学习的优化(TLBO)算法中。 TLBO的潜在解决方案是通过在教学活动之间保持的原始步骤发展而来的。另一个新颖的算法,头脑风暴优化(BSO)坚持团队交换思想以进行整体开发的理念。 BSO的脑力激荡方法被引入TLBO的工作中,并被广泛研究用于解决复杂度很高的电力分配问题。将结果与现有最佳解决方案进行比较,以证明所提出的混合算法的有效性。

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