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This paper presents a competent meta-heuristic algorithm, named, Particle Swarm Optimization-Enhanced Bat optimization (PSO-EBO) algorithm to solve the optimal operating approach of the ELD issue.The developed technique integrates two fundamental ideas.Initially, the swarm behavior of the particle is exploited to find the optimal values of the EBO technique.To illustrate the developed method performance, it is used on large, medium, and small, scale test systems to solve the ELD issues of 13-unit, 40-unit and160-unit systems.Moreover, the comparative results are performed to examine the effectiveness of the developed PSO-EBO algorithm with the existing Grey Wolf Optimization (GWO), Artificial Bee Colony (ABC), Whale Optimization Algorithm (WOA) and Differential Evolution (DE) algorithms.Finally, the experimentation outcomes obviously propose that the developed PSO-EBO algorithm can find superior solutions regarding the computational time and fuel cost than conventional methods.
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Rupam Gupta Roy (2020) studied this question.
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