NDLI: Studies on applying incremental SAT solving to optimization and enumeration problems

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Studies on applying incremental SAT solving to optimization and enumeration problems

Content Provider	Semantic Scholar
Author	Soh, Takehide
Copyright Year	2011
Abstract	Optimization and enumeration problems have been actively studied. There are not only academic interests but also real world applications as many researches have been done for industrial purpose. However, despite the recent advancements in computer technology, there are still difficult problems to solve. To break this situation, we focus on technologies in solving propositional satisfiability (SAT). Although SAT technologies are not so focused as a method for optimization and enumeration problems, the recent progress of SAT technologies is so tremendous that it can be expected to become a potential approach. In this thesis, we study a method called incremental SAT solving. It incrementally computes the satisfiability of a sub-problem obtained from a given original problem until a given goal condition is satisfied. We review how previous approaches utilizing SAT technologies are explained by this solving method. Following that, we also review several applications of it and how to utilize learned clauses for acceleration. The main contribution of this thesis is applying this incremental SAT solving to the following optimization and enumeration problems. We apply incremental SAT solving to an optimization problem, the two-dimensional strip packing problem (2SPP). In this problem, we are given a set of rectangles and one large rectangle called a strip. The goal of the problem is to pack all rectangles without overlapping, into the strip by minimizing the overall height of the packing. Although the 2SPP has been studied in operations research, some instances are still hard to
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Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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