Hybridization of Genetic Algorithm and Priority List to solve Economic Dispatch problems

This paper demonstrates the applicability in solving multi-objectives Economic Dispatch (ED) problems using an Evolutionary method called Genetic Algorithm (GA). In reality, the input-output characteristic given for a single generating unit is highly non-linear and trivial to solve using traditionally means. Thus, Hybridize Genetic Algorithm is premeditated to search for the cheapest operating fuel costs with the corresponding generator's output power ratings while satisfying ED's equality and inequality constraints. GAs have been popularized for its optimization algorithmic modus that uses decentralized communal behavior and robust search algorithm to solve mathematical problems stochastically. Alongside, Priority List Method (PLM) and Random Assignment Individual Index (RAII) technique are imbued, customizing GA's architecture to overtures greater dominancy, eradicate any possible divergence and abolish any uncertainty in initializing GA's parameters. The proposed methodology is cooperated to provide proximal and reasonable optimal solutions while formulating simplified genetic diversity algorithm for subsequent Generations which heeds premature convergence.