基于量子力学行为的蝙蝠算法的经济负荷调度

Hafiz Tehzeeb ul Hassan, Muhammad Usman Asghar, Muhammad Zunair Zamir, Hafiz M. Aamir Faiz
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引用次数: 6

摘要

经济负荷调度是一个非线性的、复杂的、有约束的优化问题。本文提出了一种基于生物启发的元启发式优化技术,即新型蝙蝠算法来解决经济负荷调度问题。三单元无损耗热系统和六单元含损耗热系统的结果表明,新型蝙蝠算法在全局最优解和收敛速度方面优于拉格朗日松弛法、lambda迭代法、遗传算法、粒子群算法、模式搜索算法、改进细菌觅食算法、智能水滴算法和传统蝙蝠算法。
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Economic load dispatch using novel bat algorithm with quantum and mechanical behaviour
Economic load dispatch is a non-linear, complex and constrained optimization problem. In this paper a bio inspired meta-heuristic optimization technique namely novel bat algorithm is proposed for solving economic load dispatch problem. The results of three unit thermal system without losses and six units thermal system inclusive of losses had shown that novel bat algorithm had outperformed Lagrange relaxation, lambda iteration method, genetic algorithm, particle swarm optimization, pattern search algorithm, modified bacterial foraging algorithm, intelligent water drop algorithm and traditional bat algorithm in term of the best global optimum solution and fastest convergence.
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