Hardness and Approximation of Submodular Minimum Linear Ordering Problems
Majid Farhadi, Swati Gupta, Shengding Sun, Prasad Tetali, Michael C., Wigal

TL;DR
This paper establishes NP-hardness for the graphic matroid MLOP, introduces a new approximation algorithm for monotone submodular MLOP, and provides improved bounds and complexity results for related problems.
Contribution
It proves NP-hardness of graphic matroid MLOP, develops a novel combinatorial approximation algorithm for monotone submodular MLOP, and offers new bounds for special cases including matroid MLOP.
Findings
NP-hardness of graphic matroid MLOP established
New approximation algorithm for monotone submodular MLOP proposed
Minimum latency vertex cover is 4/3-approximable
Abstract
The minimum linear ordering problem (MLOP) generalizes well-known combinatorial optimization problems such as minimum linear arrangement and minimum sum set cover. MLOP seeks to minimize an aggregated cost due to an ordering of the items (say ), i.e., , where is the set of items mapped by to indices . Despite an extensive literature on MLOP variants and approximations for these, it was unclear whether the graphic matroid MLOP was NP-hard. We settle this question through non-trivial reductions from mininimum latency vertex cover and minimum sum vertex cover problems. We further propose a new combinatorial algorithm for approximating monotone submodular MLOP, using the theory of principal partitions. This is in contrast to the rounding algorithm by Iwata, Tetali, and Tripathi [ITT2012],…
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Taxonomy
TopicsOptimization and Packing Problems · Advanced Manufacturing and Logistics Optimization · Complexity and Algorithms in Graphs
