Multi-objective optimization is a field of research that involves optimizing multiple conflicting objectives simultaneously. This type of optimization problem arises in various real-world applications where decision-makers need to consider multiple criteria or objectives when making decisions. The goal of multi-objective optimization is to find a set of solutions that represent a trade-off between the different objectives, known as the Pareto optimal front. Researchers in this area develop algorithms and methods to efficiently solve these complex optimization problems and help decision-makers make informed decisions in the presence of multiple conflicting objectives.