SEARCH GROUP ALGORITHM FOR MULTI-OBJECTIVE OPTIMIZATION IN ENERGY APPLICATIONS

One of the critical challenges of the new era is the provision of reliable and secure power and an energy system. The effective operation of energy systems contributes to minimize fuel consumption and pollution, conserve natural resources, ensure better planning for sustainability, and provide cleaner energy. The modern optimization methods lead to more efficient and potential solutions for managing, planning, and operating energy systems. This study proposed a new multi-objective version of the Search Group Algorithm (SGA) called the Multi-Objective Search Group Algorithm (MOSGA), aiming for the multi-objective optimization in energy applications. The MOSGA was inspired by the primary mechanism of conventional SGA and integrated an elitist non-dominated sorting technique, enabling to help determine non-dominated solutions via the mutation, generation, and selection.