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A Hybrid PSO Based Algorithm for Solving the Machine-Part Cell Formation Problem

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Title A Hybrid PSO Based Algorithm for Solving the Machine-Part Cell Formation Problem
 
Creator Tariq, Adnan
Javaid, Waqas
Shahzad, Waseem
Yasir, Muhammad
Iqbal, Shahid
 
Subject Cellular manufacturing
Genetic algorithms
Local search heuristic
Meta-heuristics
Particle swarm optimization
 
Description 748-760
Cellular Manufacturing (CM), an approach primarily based on the concept of Group Technology (GT), is one of the
recent trends that help the manufacturing industry in reducing manufacturing cost and increasing productivity while
maintaining quality. The idea of manufacturing parts in dedicated cells is beneficial as it results in increased manufacturing
quality and reduced lead times. However, implementation of such a system in a real-life situation is always a challenging
task. To overcome this challenge, several techniques, including AI-based approaches, have been developed over the years
and regularly reported in literature. A very small portion of these approaches are utilizing Particle Swarm Optimization
(PSO) in standard or hybrid form, whereas a larger chunk is either GA-based or utilizing other heuristics. To test the
effectiveness of PSO while handling the Machine-Part Cell Formation (MPCF) problem in a CM environment, initially a
standard PSO is developed during this research. Later, the same is hybridized with a Local Search Heuristic (LSH). The
results of both standard and hybrid PSOs, developed during this research, are compared with the corresponding GA based
methodologies, already available in literature. Computational results show that the GA based approaches have been
outperformed both in terms of accuracy and computational effort. Further comparison of the results generated by the Hybrid
PSO (HPSO) with several other techniques also shows that HPSO is either more or, in few cases, equally effective.
 
Date 2024-07-05T11:26:01Z
2024-07-05T11:26:01Z
2024-07
 
Type Article
 
Identifier 0022-4456 (Print); 0975-1084 (Online)
http://nopr.niscpr.res.in/handle/123456789/64213
https://doi.org/10.56042/jsir.v83i7.3871
 
Language en
 
Publisher NIScPR-CSIR,India
 
Source JSIR Vol.83(7) [July 2024]