Decision Diagrams for Discrete Optimization: A Survey of Recent Advances

  • Margarita P. Castro
    Department of Industrial and Systems Engineering, Pontificia Universidad Católica de Chile, Santiago 7820436, Chile;
  • Andre A. Cire
    Department of Management, University of Toronto Scarborough and Rotman School of Management, Toronto, Ontario M1E 1A4, Canada;
  • J. Christopher Beck
    Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Ontario M5S 3G8, Canada

抄録

<jats:p> In the last decade, decision diagrams (DDs) have been the basis for a large array of novel approaches for modeling and solving optimization problems. Many techniques now use DDs as a key tool to achieve state-of-the-art performance within other optimization paradigms, such as integer programming and constraint programming. This paper provides a survey of the use of DDs in discrete optimization, particularly focusing on recent developments. We classify these works into two groups based on the type of diagram (i.e., exact or approximate) and present a thorough description of their use. We discuss the main advantages of DDs, point out major challenges, and provide directions for future work. </jats:p>

収録刊行物

  • INFORMS Journal on Computing

    INFORMS Journal on Computing 34 (4), 2271-2295, 2022-07

    Institute for Operations Research and the Management Sciences (INFORMS)

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