Structure, Duality, and Randomization: Common Themes in AI and OR

Carla P. Gomes, Cornell University

Both the Artificial Intelligence (AI) community and the Operations Research (OR) community are interested in developing techniques for solving hard combinatorial problems. OR has relied heavily on mathematical programming formulations such as integer and linear programming, while AI has developed constrained-based search and inference methods. Recently, we have seen a convergence of ideas, drawing on the individual strengths of these paradigms. Furthermore, there is a great deal of overlap in research on local search and meta-heuristics by both communities. Problem structure, duality, and randomization are overarching themes in the study of AI/OR approaches. I will compare and contrast the different views from AI and OR on these topics, highlighting potential synergistic benefits.1

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