A GRASP algorithm to solve the problem of dependent tasks scheduling in different machines

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

2 Scopus citations

Abstract

Industrial planning has experienced notable advancements since its beginning by the middle of the 20th century. The importance of its application within the several industries where it is used has been demonstrated, regardless of the difficulty of the design of the exact algorithms that solve the variants. Heuristic methods have been applied for planning problems due to their high complexity; especially Artificial Intelligence when developing new strategies to solve one of the most important variants called task scheduling. It is possible to define task scheduling as: a set of N production line tasks and M machines, which can execute those tasks, where the goal is to find an execution order that minimizes the accumulated execution time, known as makespan. This paper presents a GRASP meta heuristic strategy for the problem of scheduling dependent tasks in different machines.

Original languageEnglish
Title of host publicationArtificial Intelligence in Theory and Practice
Subtitle of host publicationIFIP 19th World Computer Congress, TC 12: IFIP AI 2006 Stream, August 21-24, 2006, Santiago, Chile
EditorsMax Bramer
Pages325-334
Number of pages10
DOIs
StatePublished - 2006

Publication series

NameIFIP International Federation for Information Processing
Volume217
ISSN (Print)1571-5736

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