Emergent Mind

Scheduling meets n-fold Integer Programming

(1603.02611)
Published Mar 8, 2016 in cs.DS

Abstract

Scheduling problems are fundamental in combinatorial optimization. Much work has been done on approximation algorithms for NP-hard cases, but relatively little is known about exact solutions when some part of the input is a fixed parameter. In 2014, Mnich and Wiese initiated a systematic study in this direction. In this paper we continue this study and show that several additional cases of fundamental scheduling problems are fixed parameter tractable for some natural parameters. Our main tool is n-fold integer programming, a recent variable dimension technique which we believe to be highly relevant for the parameterized complexity community. This paper serves to showcase and highlight this technique. Specifically, we show the following four scheduling problems to be fixed-parameter tractable, where p max is the maximum processing time of a job and w max is the maximum weight of a job: - Makespan minimization on uniformly related machines $(Q||C{max} )$ parameterized by $p{max}$, - Makespan minimization on unrelated machines $(R||C{max} )$ parameterized by $p{max}$ and the number of kinds of machines, - Sum of weighted completion times minimization on unrelated machines $(R|| \sum wi Ci )$ parameterized by $p{max} + w{max}$ and the number of kinds of machines, - The same problem, $(R|| \sum wi Ci),$ parameterized by the number of distinct job times and the number of machines.

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