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Progress in Artificial Intelligence

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01-02-2016 | Regular Paper

GRASP for sequencing mixed models in an assembly line with work overload, useless time and production regularity

Authors: Joaquín Bautista, Rocío Alfaro-Pozo, Cristina Batalla-García

Published in: Progress in Artificial Intelligence | Issue 1/2016

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Abstract

A GRASP algorithm is presented for solving a sequencing problem in a mixed-model assembly line. The problem is focused on obtaining a manufacturing sequence that completes the greatest possible amount of required work and fulfils the production regularity property. The implemented GRASP algorithm is compared with other resolution procedures by means of instances from a case study linked to the Nissan’s engine plant in Barcelona.

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Title: GRASP for sequencing mixed models in an assembly line with work overload, useless time and production regularity
Authors: Joaquín Bautista
Rocío Alfaro-Pozo
Cristina Batalla-García
Publication date: 01-02-2016
Publisher: Springer Berlin Heidelberg
Published in: Progress in Artificial Intelligence / Issue 1/2016
Print ISSN: 2192-6352
Electronic ISSN: 2192-6360
DOI: https://doi.org/10.1007/s13748-015-0071-z

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