Multiobjective optimization is a branch of optimization, which deals with several objectif functions, often in contradiction with each others. The use of several objectives can potentially enrich the model, but at the same time increases its resolution complexity. This tutorial will start by the definition of the core concepts (what is a solution in multiobjective optimization). Then it will present the classical methods of resolution (scalarization methods, continuation, descent-based methods). It will end by a mention to heuristics (evolutionary algorithms) and derivative-free methods.