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This chapter describes the technical background for solving combinatorial problems using zero-suppressed binary decision diagrams (ZDDs). A ZDD can store a vast number of feasible solutions of a combinatorial problem, such as vertex sets and subgraphs of a given graph. ZDDs enable obtaining many good solutions, random sampling, filtering, and more, rather than just finding a single optimal solution. In this chapter, we describe the definition and characteristics of ZDDs, explain two typical ZDD construction frameworks, and show algorithms that utilize constructed ZDDs.

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ZDDs and Frontier-Based Search for Solving Combinatorial Problems

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  • 发表日期：

    2025年

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  • Jun Kawahara

摘要

This chapter describes the technical background for solving combinatorial problems using zero-suppressed binary decision diagrams (ZDDs). A ZDD can store a vast number of feasible solutions of a combinatorial problem, such as vertex sets and subgraphs of a given graph. ZDDs enable obtaining many good solutions, random sampling, filtering, and more, rather than just finding a single optimal solution. In this chapter, we describe the definition and characteristics of ZDDs, explain two typical ZDD construction frameworks, and show algorithms that utilize constructed ZDDs.