Multi-objective Search Group Algorithm for Engineering Design Problems

This study proposes a new multi-objective version of the Search Group Algorithm (SGA) called the Multi-Objective Search Group Algorithm (MOSGA). The MOSGA integrates the conventional SGA with an elitist non-dominated sorting technique, enabling the definition of Pareto optimal solutions via mutation, offspring generation, and selection. The method is validated on twenty-five case studies, including nineteen unconstrained multi-objective benchmark problems, six constrained multi-objective benchmark problems, and five multi-objective engineering design problems. The results indicate that MOSGA is robust and superior in handling a wide variety of multi-objective problems.