Abstract

The problems of scheduling jobs on a single machine subject to precedence constraints can often be modelled as the jump number problem for posets, where a linear extension of a given partial order is to be found which minimizes the number of noncomparabilities. In this paper, we are investigating a restricted class of posets, called interval orders, admitting approximation algorithms for the jump number problem, in which the problem remains NP-complete. We have implemented three known approximation algorithms for this problem, all of which are guaranteed to produce solutions that are at most 50% worse than the optimal ones. More importantly, we have performed an exhaustive search for particularly hard interval orders, which enforce the algorithms to generate orderings which are exactly 50% worse than the optimal linear extensions. The main purpose of this paper is to present the database of those problematic posets.

Highlights

  • The jump number problem for posets consists in determining a linear extension with a minimum number of adjacent pairs that are incomparable in a given poset

  • -approximation algorithms are known in a restricted class of interval orders, where the problem remains

  • We introduce our methodology of tackling the problem, and review the approximation algorithms under investigation

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Summary

Introduction

The jump number problem for posets consists in determining a linear extension with a minimum number of adjacent pairs that are incomparable in a given poset. Possible applications of this NP-hard optimization problem can be found in the area of task scheduling with precedence constraints. -approximation algorithms are known in a restricted class of interval orders, where the problem remains. The database of interval orders difficult for the jump. Both help the attracted individuals come up with new concepts and restrain them from following unfortunate thoughts. Our genetic procedure of obtaining difficult interval orders is presented, together with an elaboration concerning the database for storing those posets

Problem statement
Example application
Interval orders
Methodology
The algorithm of Felsner
Searching for hard instances
The database of interval orders
Findings
Future work
Full Text
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