A Hybrid Genetic Algorithm for Cell Formation Problems Using Operational Time

Chaudhuri, Barnali; Jana, Rabin K.; Dan, Pranab K.

doi:10.1007/978-981-10-3153-3_13

Cited by 2 publications

(1 citation statement)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…2 Literature review on hybrid GA techniques in CMS CMS problems and their different variants have been widely studied in literature (Paydar et al, 2013;Messaoudi and Rebaï, 2014;Mousavi et al, 2018). A majority of these techniques use GA (Karthikeyan et al, 2016;Moradgholi et al, 2016;Rezazadeh and Khiali-Miab, 2017;Vitayasak et al, 2017) and GA-based hybrid techniques (Chaudhuri et al, 2017;Costa et al, 2017). An extensive review on the application of GA and its hybridisations in CMSs have been done by Chaudhuri et al (2018).…”

Section: Introductionmentioning

confidence: 99%

A goal programming embedded genetic algorithm for multi-objective manufacturing cell design

Chaudhuri

Jana

Sharma

et al. 2019

IJADS

Self Cite

View full text Add to dashboard Cite

In this paper, a multi-objective manufacturing cell design problem is studied. A goal programming (GP) embedded real-coded genetic algorithm (GA) is designed for solving this problem. Initially, the GA is used to obtain the individual minimum of each objective. Thereafter, utilising the concepts of GP, an equivalent problem is derived, and the sum of deviation variables associated with the objectives are minimised. The GA is used further to obtain the optimal cell design. A software toolkit is developed based on the proposed technique using C Sharp.net to ensure its use in a larger scale. The effectiveness of the technique is judged based on a set of test problems of different sizes. The proposed technique is found to be better in terms of the performance measure over the existing ones.

show abstract