Abstract

This paper studies optimal matroid partitioning problems for various objective functions. In the problem, we are given k weighted-matroids on the same ground set. Our goal is to find a feasible partition that minimizes (maximizes) the value of an objective function. A typical objective is the maximum over all subsets of the total weights of the elements in a subset, which is extensively studied in the scheduling literature. Likewise, as an objective function, we handle the maximum/minimum/sum over all subsets of the maximum/minimum/total weight(s) of the elements in a subset. In this paper, we determine the computational complexity of the optimal partitioning problem with the above-described objective functions. Namely, for each objective function, we either provide a polynomial time algorithm or prove NP-hardness. We also discuss the approximability for the NP-hard cases.

Highlights

  • The matroid partitioning problem is one of the most fundamental problems in combinatorial optimization

  • We study weighted versions of the matroid partitioning problem

  • For any feasible partition (I1, . . . , Ik) for (E, Ii)i∈[k], it is an optimal solution for the minimum (Op(1), Op(2))-value matroid partitioning problem instance (E, (Ii, wi)i∈[k]) if and only if it is optimal for the maximum (Op(1), Op(2))-value matroid partitioning problem instance (E, (Ii, wi)i∈[k]), where wmax = maxi∈[k] maxe∈E wi(e)

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Summary

Introduction

The matroid partitioning problem is one of the most fundamental problems in combinatorial optimization. Special cases of the minimum (max, )-value matroid partitioning problem have been extensively addressed in the scheduling literature under the name of the minimum makespan scheduling Since this problem is NP-hard, many papers have proposed polynomial-time approximation algorithms. Approximation algorithms for the maximum (min, )-value matroid partitioning problem are well-studied, see, e.g., [3, 13, 25, 20]. For the (max, min) and ( , min) cases, we give polynomial-time algorithms when the matroids and weights are respectively identical, and prove strong NP-hardness even to approximate for the general case. Due to the space limitation, we omit proofs of some results, which are found in [14]

Preliminaries
Basic properties
Strong NP-hardness of the identical case
PTAS for the identical case
Hardness of the general case
Algorithm for the general case
Complexity of other optimal matroid partitioning problems
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