An adaptive class topper optimization algorithm to solve ecological emission economic load dispatch problem

Abstract

In this paper, an improved version of class topper optimization algorithm with adaptive improvement factor is proposed to solve a multi-objective ecological emission economic load dispatch (EELD) problems. The proposed ACTO algorithm is an extended and enhanced improved version of existing class topper optimization algorithm [1] which mimics the learning behaviour of students in a class. In ACTO algorithm, to improve the learning behavior of students, an adaptive improvement factor is mapped with the existing CTO. This technique enhances the searching capability of ACTO and helps in finding the optimal solution at a better convergence rate. The performance of ACTO is evaluated by solving three test cases of a multi-objective ecological emission economic load dispatch problems. The results are compared and validated with some existing methods to prove the supremacy of the proposed technique.