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Tabu search for multiple-criteria manufacturing cell design

Cellular manufacturing (CM) is an important application of group technology (GT) in which families of parts are produced in manufacturing cells or in a group of various machines. Cell design/formation is the first step in the design of cellular manufacturing systems. Many efforts have been made towa... Full description

Journal Title: International journal of advanced manufacturing technology 2006-07, Vol.28 (9), p.950-956
Main Author: Lei, Deming
Other Authors: Wu, Zhiming
Format: Electronic Article Electronic Article
Language: English
Subjects:
Publisher: London: Springer-Verlag
ID: ISSN: 0268-3768
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recordid: cdi_springer_primary_2006_170_28_9_289950
title: Tabu search for multiple-criteria manufacturing cell design
format: Article
creator:
  • Lei, Deming
  • Wu, Zhiming
subjects:
  • Algorithms
  • Cell formation
  • Cell load
  • Cellular manufacture
  • Computer-Aided Engineering (CAD, CAE) and Design
  • Engineering
  • Genetic algorithms
  • Group technology
  • Industrial and Production Engineering
  • Manufacturing cells
  • Mechanical Engineering
  • Multiple criterion
  • Multiple objective analysis
  • Multiple objectives
  • Pareto optimality
  • Production scheduling
  • Production/Logistics
  • Searching
  • Tabu search
  • Total moves
  • Variation
ispartof: International journal of advanced manufacturing technology, 2006-07, Vol.28 (9), p.950-956
description: Cellular manufacturing (CM) is an important application of group technology (GT) in which families of parts are produced in manufacturing cells or in a group of various machines. Cell design/formation is the first step in the design of cellular manufacturing systems. Many efforts have been made towards cell design taking into consideration multiple criteria. This paper presents a Pareto-optimality-based multi-objective tabu search (MOTS) algorithm to the machine-part grouping problems with multiple objectives: minimizing the weighted sum of inter-cell and intra-cell moves and minimizing the total cell load variation A new approach is developed to evaluate the non-dominance of solutions produced by the tabu search. Comparisons between MOTS and the genetic algorithm (GA) are done and the results show that MOTS is quite promising in multi-objective cell design.
language: eng
source:
identifier: ISSN: 0268-3768
fulltext: no_fulltext
issn:
  • 0268-3768
  • 1433-3015
url: Link


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descriptionCellular manufacturing (CM) is an important application of group technology (GT) in which families of parts are produced in manufacturing cells or in a group of various machines. Cell design/formation is the first step in the design of cellular manufacturing systems. Many efforts have been made towards cell design taking into consideration multiple criteria. This paper presents a Pareto-optimality-based multi-objective tabu search (MOTS) algorithm to the machine-part grouping problems with multiple objectives: minimizing the weighted sum of inter-cell and intra-cell moves and minimizing the total cell load variation A new approach is developed to evaluate the non-dominance of solutions produced by the tabu search. Comparisons between MOTS and the genetic algorithm (GA) are done and the results show that MOTS is quite promising in multi-objective cell design.
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subjectAlgorithms ; Cell formation ; Cell load ; Cellular manufacture ; Computer-Aided Engineering (CAD, CAE) and Design ; Engineering ; Genetic algorithms ; Group technology ; Industrial and Production Engineering ; Manufacturing cells ; Mechanical Engineering ; Multiple criterion ; Multiple objective analysis ; Multiple objectives ; Pareto optimality ; Production scheduling ; Production/Logistics ; Searching ; Tabu search ; Total moves ; Variation
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abstractCellular manufacturing (CM) is an important application of group technology (GT) in which families of parts are produced in manufacturing cells or in a group of various machines. Cell design/formation is the first step in the design of cellular manufacturing systems. Many efforts have been made towards cell design taking into consideration multiple criteria. This paper presents a Pareto-optimality-based multi-objective tabu search (MOTS) algorithm to the machine-part grouping problems with multiple objectives: minimizing the weighted sum of inter-cell and intra-cell moves and minimizing the total cell load variation A new approach is developed to evaluate the non-dominance of solutions produced by the tabu search. Comparisons between MOTS and the genetic algorithm (GA) are done and the results show that MOTS is quite promising in multi-objective cell design.
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