Many industrial domains are concerned by large and complex optimization problems, involving significant financial cost and requiring decisions to be made in an optimal way. The development of advanced hybrid optimization methods from combinatorial optimization in operations research, decision in artificial intelligence and parallel and distributed computing, is an important issue in solving in a reasonable search time this class of problems, which are more and more complex. The goal of the DOLPHIN team is the modeling and parallel resolution of large (multi-objective) combinatorial optimization problems. Efficient parallel cooperative optimization methods are developed from the analysis of the structure of the solved problem. The target optimization problems are generic problems (flow-shop scheduling, vehicle routing, etc.) and industrial problems from logistics, transportation, energy, and bioinformatics.