Tackling complex problems with multiple goals: This survey provides a comprehensive overview of genetic algorithm (GA)-based multiobjective optimization techniques, offering a valuable resource for researchers and practitioners seeking to solve problems with conflicting objectives. The paper summarizes current approaches, emphasizing their foundation in operations research techniques. It reviews the main algorithms, highlighting their advantages and disadvantages, applicability, and known applications. Additionally, it addresses future trends and potential research directions. This survey serves as a guide to the diverse landscape of GA-based multiobjective optimization, helping researchers navigate the available techniques and identify promising avenues for future development and application.
This paper, published in ACM Computing Surveys, aligns with the journal's focus on providing comprehensive surveys and tutorials on important topics in computer science. By offering an updated overview of GA-based multiobjective optimization techniques, the paper serves as a valuable resource for researchers and practitioners in the field.