Application of Spotted Hyena Optimizer in Cogeneration Power Plant on Single and Multiple-Objective

In this paper, a Spotted Hyena Optimizer (SHO) is employed in the context of addressing a constrained optimization problem to solve a cogeneration power plant (CGPP) problem through a classical approach. The paper examines the CGPP system through consideration of the 3E aspects (energy, exergy, and economy) through thermodynamic analysis. The equipment used in the system included a condenser, a turbo-generators, and a boiler. Two design optimization approaches were used: single objective optimization (SOO) and multi-objective optimization (MOO), with a comparison conducted using the SHO algorithm. On the basis of the findings, one optimal solution was returned by SOO-SHO from a single run, while a set of optimal solutions was discovered using MOO-SHO. The use of a SOO-SHO model requires the researcher to determine the preferred settings prior to starting the run, whereas the MOO-SHO does not require such decisions to be taken until after the run is complete. Typically, the SOO approach generates the optimal solution when considering a particular objective, while the MOO uses a broader array of information to reach richer solutions that consider the broader perspective.