Sorting Can Exponentially Speed Up Pure Dynamic Programming

Stasys Jukna; Hannes Seiwert

doi:10.1016/j.ipl.2020.105962

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arXiv · 2012.12838

Sorting Can Exponentially Speed Up Pure Dynamic Programming

Stasys Jukna·Hannes Seiwert

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Abstract

Many discrete minimization problems, including various versions of the shortest path problem, can be efficiently solved by dynamic programming (DP) algorithms that are "pure" in that they only perform basic operations, as min, max, +, but no conditional branchings via if-then-else in their recursion equations. It is known that any pure (min,+) DP algorithm solving the minimum weight spanning tree problem on undirected n-vertex graphs must perform at least $2^{\Omega(\sqrt{n})}$ operations. We show that this problem can be solved by a pure (min,max,+) DP algorithm performing only $O(n^3)$ operations. The algorithm is essentially a (min,max) algorithm: addition operations are only used to output the final values. The presence of both min and max operations means that now DP algorithms can sort: this explains the title of the paper.

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BibTeX RIS

Stasys Jukna, Hannes Seiwert. 2020-12-23. Sorting Can Exponentially Speed Up Pure Dynamic Programming. https://doi.org/10.1016/j.ipl.2020.105962

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