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.
