We propose a general solution method framework based on a Collaborative Agent Teams (CAT) architecture to tackle large-scale mixed-integer optimization problems with complex structures. This frame- work introduces several conceptual improvements over previous agent teams' approaches. We discuss how to configure the three key compo- nents of a CAT solver for multidimensional optimization problems: the problem representation, the design of agents, and the information sharing mechanisms between agents. Implementation guidelines are also given.