Solving the manufacturing cell design problem via invasiveweed optimization

RICARDO JAVIER SOTO DE GIORGIS, BRODERICK CRAWFORD LABRIN, Carlos Castillo, Fernando Paredes

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

8 Scopus citations

Abstract

Manufacturing plants are commonly organized in cells containing machines that process different parts of a given product. The Manufacturing Cell Design Problem (MCDP) aims at efficiently organizing the machines into cells in order to increase productivity by minimizing the inter-cell moves of parts. In this paper, we present a new approach based on Invasive Weed Optimization (IWO) for solving such a problem. The IWO algorithm is a recent metaheuristic inspired on the colonization behavior of the invasive weeds in agriculture. IWO represents the solutions as weeds that grow and produce seeds to be randomly dispersed over the search area. We additionally incorporate a binary neighbor operator in order to efficiently handle the binary nature of the problem. The experimental results demonstrate the efficiency of the proposed approach which is able to reach several global optimums for a set of 90 well-known MCDP instances.

Original languageEnglish
Title of host publicationArtificial Intelligence Perspectives in Intelligent Systems - Proceedings of 5th Computer Science On-line Conference, CSOC 2016
EditorsRadek Silhavy, Roman Senkerik, Zuzana Kominkova Oplatkova, Petr Silhavy, Zdenka Prokopova
PublisherSpringer Verlag
Pages115-126
Number of pages12
ISBN (Print)9783319336237
DOIs
StatePublished - 1 Jan 2016
Event5th Computer Science On-line Conference, CSOC 2016 - Prague, Czech Republic
Duration: 27 Apr 201630 Apr 2016

Publication series

NameAdvances in Intelligent Systems and Computing
Volume464
ISSN (Print)2194-5357

Conference

Conference5th Computer Science On-line Conference, CSOC 2016
CountryCzech Republic
CityPrague
Period27/04/1630/04/16

Keywords

  • Invasive Weed Optimization
  • Manufacturing Cell Design
  • Metaheuristics
  • Optimization

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