An Improved Solution to Generation Scheduling Problem Using Slime Mold Algorithm

Abstract

The slime mold algorithm (SMA) is a novel meta-heuristic search that replicates the characteristics of slime mold during oscillation. This is presented in a novel mathematical formulation that employs changeable weights to modify the sequence of both negative and positive propagation waves in order to build a mechanism for linking food availability with intensive exploration capacity and exploitation affinity. The study demonstrates how to solve a non-convex and cost-effective load dispatch issue (ELD) in an electric power system using the SM method. The efficacy of SMA is explored for a single-area economic load dispatch on small-scale power systems, using 3-, 5-, and 6-unit test systems, and the results are validated by comparing the results to those of other well-known meta-heuristic algorithms.