Resolving the manufacturing cell design problem using the flower pollination algorithm

Ricardo Soto, Broderick Crawford, Rodrigo Olivares, Michele De Conti, Ronald Rubio, Boris Almonacid, Stefanie Niklander

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

The Manufacturing cell design problem focuses on the creation of an optimal distribution of the machinery on a productive plant, through the creation of highly independent cells where the parts of certain products are processed. The main objective is to reduce the movements between this cells, decreasing production times, costs and getting other advantages. To find solutions to this problem, in this paper, the usage of the Flower Pollination Algorithm is proposed, which is one of the many nature-based algorithms, which in this case is inspired in the Pollination of the flowers, and has shown great capacities in the resolution of complex problems. Experimental results are shown, with 90 instances taken from Boctor’s experiments, where the optimum is achieved in all them.

Original languageEnglish
Title of host publicationMulti-disciplinary Trends in Artificial Intelligence - 10th International Workshop, MIWAI 2016, Proceedings
EditorsFrieder Stolzenburg, Abhaya Nayak, Fangzhen Lin, Chattrakul Sombattheera
PublisherSpringer Verlag
Pages184-195
Number of pages12
ISBN (Print)9783319493961
DOIs
StatePublished - 2016
Event10th Multi-Disciplinary International Workshop on Artificial Intelligence, MIWAI 2016 - Chiang Mai, Thailand
Duration: 7 Dec 20169 Dec 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10053 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th Multi-Disciplinary International Workshop on Artificial Intelligence, MIWAI 2016
Country/TerritoryThailand
CityChiang Mai
Period7/12/169/12/16

Keywords

  • Flower pollination algorithm
  • Manufacturing cell design problem
  • Metaheuristics
  • Optimization

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