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A hybrid GA-AUGMECON method to solve a cubic cell formation problem considering different worker skills

https://doi.org/10.1016/j.cie.2014.05.022
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27/27 checkable references clean · checked 2026-07-22

Every reference with a DOI in the deposited reference list resolved to a known work in Crossref or DataCite at the dated check, and none carried a retraction, withdrawal, or removal notice.

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The 27 checked references that resolve
resolves10.1016/j.ejor.2007.09.023
Integrated cellular manufacturing systems design with production planning and dynamic system reconfiguration
resolves10.1016/j.eswa.2011.01.161
Minimization of exceptional elements and voids in the cell formation problem using a multi-objective genetic algorithm
resolves10.1080/00207540110040466
Forming effective worker teams for cellular manufacturing
resolves10.1016/j.cor.2007.10.026
A multi-objective scatter search for a dynamic cell formation problem
resolves10.1016/j.ejor.2007.12.014
An exact -constraint method for bi-objective combinatorial optimization problems: Application to the Traveling Salesman Problem with Profits
resolves10.1016/j.cie.2003.03.002
Human related issues in manufacturing cell design, implementation, and operation: a review and survey
resolves10.1109/4235.996017
A fast and elitist multiobjective genetic algorithm: NSGA-II
resolves10.1080/00207540600620773
Multi-objective optimization of manufacturing cell design
resolves10.1016/j.apenergy.2010.09.014
Multi-objective congestion management by modified augmented ε-constraint method
resolves10.1016/S0925-5273(03)00010-0
The algorithm for integrating all incidence matrices in multi-dimensional group technology
resolves10.1016/j.eswa.2008.07.054
Genetic algorithm approach for solving a cell formation problem in cellular manufacturing
resolves10.1016/j.jmsy.2011.07.007
A new mathematical model for integrating all incidence matrices in multi-dimensional cellular manufacturing system
resolves10.1080/002075400189095
A review of the modern approaches to multi-criteria cell design
resolves10.1080/09537280310001597334
A genetic algorithm for multiple objective dealing with exceptional elements in cellular manufacturing
resolves10.1016/j.amc.2009.03.037
Effective implementation of the ε-constraint method in Multi-Objective Mathematical Programming problems
resolves10.1080/00207549308956859
Simultaneous formation of machine and human cells in group technology: a multiple objective approach
resolves10.1016/j.cie.2010.02.017
A simulation-based evolutionary multiobjective approach to manufacturing cell formation
resolves10.1016/j.cie.2012.06.015
Integrating workers’ differences into workforce planning
resolves10.1016/j.ejor.2009.10.020
The evolution of cell formation problem methodologies based on recent studies (1997–2008): Review and directions for future research
resolves10.1080/002075497194886
The multi-dimensional aspects of a group technology algorithm
resolves10.1016/j.cor.2012.10.016
A hybrid genetic-variable neighborhood search algorithm for the cell formation problem based on grouping efficacy
resolves10.1080/00207540310001638073
A multi-objective genetic algorithm approach to the design of cellular manufacturing systems
resolves10.1080/002075498192841
Multi-objective machine-part cell formation through parallel simulated annealing
resolves10.1080/00207540110072966
A multi-objective procedure for labour assignments and grouping in capacitated cell formation problems
resolves10.1016/0360-8352(92)90022-C
A genetic algorithm approach to the machine-component grouping problem with multiple objectives
resolves10.1080/00207540512331311859
A grouping genetic algorithm for the multi-objective cell formation problem
resolves10.1016/j.ijpe.2005.01.014
Similarity coefficient methods applied to the cell formation problem: A taxonomy and review
The 5 references without a DOI — listed, not checked
no DOI — not checkedDynamic cell formation and the worker assignment problem: A new model
no DOI — not checked10.1016/j.cie.2014.05.022_b0055
no DOI — not checked10.1016/j.cie.2014.05.022_b0060
no DOI — not checkedMulti-objective cell formation and production planning in dynamic virtual cellular manufacturing systems
no DOI — not checked10.1016/j.cie.2014.05.022_b0150
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