In recent years, optimization based on decision diagrams have come up as an alternative technology that operations researchers should have in their toolbox. Decision diagrams (DDs) are graphical data structures which can compactly represent the solution set of a combinatorial problem. In this talk, we mainly discuss the basics of decision diagrams theory for optimization and then, a framework which integrates approximate DDs and mixed integer programming (MIP) technology for modeling and tackling optimization problems. In the framework, an approximate DD plays the role of a search tree by identifying parts of the search space that can be efficiently explored with MIP technology while dual bounds can also be obtained. Conversely, the MIP results are iteratively employed to refine the DD and find primal bounds.
Ce séminaire s'adresse seulement aux étudiants du GERAD.
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