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ULL::A-Team tool is a library that provides a skeleton to solve multi-objective optimization problems by applying evolutionary algorithms. In addition to providing sequential implementations of some of the best-known evolutionary algorithms, the skeleton provides great flexibility in obtaining parallel schemes. This flexibility is achieved by specifying configurations that allow the execution of different parallel evolutionary models: homogeneous island-based model, heterogeneous island-based model and self-adaptive island-based model. To solve a particular problem, the user must specify all its properties by defining a set of C++ classes. Additionally, the user can also incorporate new evolutionary algorithms to the tool. This work explains how to carry out this task using IBEA algorithm as a case study. In order to check the contribution of the new algorithm, the computational results obtained for the multi-objective knapsack problem are presented.