Multidisciplinary design optimization (MDO) deals with complex engineering problems which are decomposed into several subproblems called disciplines. The disciplines are often hierarchically organized. Moreover, each discipline may have many conflicting objectives to achieve at the same time. Thus, at each level of the hierarchy, trade-offs have to be found between multiobjective optimization problems. Multiobjective multidisciplinary methods designed to solve hierarchical multiobjective optimization problems such as EM-MOGA, MORDACE or COSMOS are searching for the whole Pareto set which corresponds to the multiobjective optimization problem that bring all the objectives of the problem together. But the solutions are just in a subset of the whole Pareto set. In this paper, we propose a definition of compromise between disciplines which are multiobjective optimization problems
