金豺算法求解CCFELD问题的实现

R. Ramamoorthi, R. Balamurugan
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引用次数: 0

摘要

本研究提出了Golden Jackal Optimization (GJO)算法,这是一种有效且值得信赖的群体优化算法,用于解决使用立方燃料成本函数的经济负荷调度(ELD)问题。实际ELD的非光滑代价函数存在等等约束和不等约束,导致难以找到整体最优结果。首先用二次成本函数和三次燃料成本函数对建议的GJO进行了测试,以证明其有效性和有效性。使用3个发电机组系统、5个发电机组系统、6个发电机组系统、26个具有二次和三次燃料成本函数的发电机组对GJO算法进行了评估。许多案例研究和其他现有算法的评估已经证实,建议的GJO技术产生了出色的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Implementations of Golden Jackal Algorithm for Solving CCFELD Problems
This study offers the Golden Jackal Optimization (GJO) algorithm, an effective and trustworthy swarm optimization for tackling economic load dispatch (ELD) issues using cubic fuel cost functions. The presence of equal and unequal constraints of the non-smooth cost functions of a practical ELD has caused difficulties in finding an overall optimal result. The suggested GJO is tested first with quadratic cost functions as well as the cubic fuel cost functions to demonstrate its usefulness and efficiency. Three generator systems, five generator systems, six generating systems, 26 generators with quadratic and cubic fuel cost functions have all been used to assess the proposed GJO algorithm. Numerous case studies and evaluation with the other existing algorithms have substantiated that the suggested GJO technique yields outstanding outcomes.
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