article

A novel intelligent particle swarm optimization algorithm for solving cell formation problem

Authors:

Vahid Mahmoodian,

Armin Jabbarzadeh,

Hassan Rezazadeh,

Farnaz BarzinpourAuthors Info & Claims

Neural Computing and Applications, Volume 31, Issue 2

Pages 801 - 815

https://doi.org/10.1007/s00521-017-3020-x

Published: 01 February 2019 Publication History

Abstract

The formation of manufacturing cells forms the backbone of designing a cellular manufacturing system. In this paper, we present a novel intelligent particle swarm optimization algorithm for the cell formation problem. The proposed solution method benefits from the advantages of particle swarm optimization algorithm (PSO) and self-organization map neural networks by combining artificial individual intelligence and swarm intelligence. Numerical examples demonstrate that the proposed intelligent particle swarm optimization algorithm significantly outperforms PSO and yields better solutions than the best solutions existed in the literature of cell formation. The application of the proposed approach is examined in a case problem where real data is utilized for cell reconfiguration of an actual company involved in agricultural manufacturing sector.

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Cited By

Alamiparvin RMehdizadeh ESoleimani H(2024)A New Mathematical Model for Cell Layout Problem considering Rotation of Unequal Dimensions of Cells and MachinesComplexity10.1155/2024/64890872024Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1155/2024/6489087
Ao WZhang GLi YJin DSingh ASun YAkoglu LGunopulos DYan XKumar ROzcan FYe J(2023)Learning to Solve Grouped 2D Bin Packing Problems in the Manufacturing IndustryProceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3580305.3599860(3713-3723)Online publication date: 6-Aug-2023
https://dl.acm.org/doi/10.1145/3580305.3599860

A novel intelligent particle swarm optimization algorithm for solving cell formation problem
1. Theory of computation
  1. Design and analysis of algorithms

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cover image Neural Computing and Applications

Neural Computing and Applications Volume 31, Issue 2

February 2019

870 pages

ISSN:0941-0643

EISSN:1433-3058

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Copyright © Copyright © 2019 Springer-Verlag London Ltd., part of Springer Nature.

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Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 01 February 2019

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Cited By

Alamiparvin RMehdizadeh ESoleimani H(2024)A New Mathematical Model for Cell Layout Problem considering Rotation of Unequal Dimensions of Cells and MachinesComplexity10.1155/2024/64890872024Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1155/2024/6489087
Ao WZhang GLi YJin DSingh ASun YAkoglu LGunopulos DYan XKumar ROzcan FYe J(2023)Learning to Solve Grouped 2D Bin Packing Problems in the Manufacturing IndustryProceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3580305.3599860(3713-3723)Online publication date: 6-Aug-2023
https://dl.acm.org/doi/10.1145/3580305.3599860

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