An efficient genetic algorithm for single row facility layout

Kothari, Ravi; Ghosh, Diptesh

doi:10.1007/s11590-012-0605-2

Cited by 45 publications

(37 citation statements)

References 22 publications

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“…A multi-floor layout design model for dynamic cellular manufacturing system has been proposed by Kia et al (2014). An efficient GA approach for facility layout problems has been suggested by Kothari and Ghosh (2014a). Zhang et al (2014) applied GA in designing the functional area layout of railway logistics park.…”

Section: Genetic Algorithmmentioning

confidence: 99%

A review on implementation of meta-heuristic approaches for layout problems in dynamic business environment

Sharma¹,

Singhal²

2016

IJMDA

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Arrangement of the facilities on shop floor in industries termed as facility layout planning. It is a vital issue at the premature stage while designing a manufacturing structure because it affects the total manufacturing cost considerably. The dynamic environment is such an industrial condition in which flexibility exists in the demand of the product. The purpose of this research paper is to present a review on the implementation of meta-heuristics approaches for handling the problem of facility layout in a dynamic environment. Various meta-heuristic approaches which have been implemented in facility layout planning (FLP) are discussed briefly and the percent utilisation of different approaches is analysed in various time spans. Tabu search (TS), genetic algorithm (GA), particle swarm optimisation (PSO), and ant colony optimisation (ACO) are several typically used methods by researchers for layout optimisation. In the present study, % utilisation of these algorithms has been analysed for different time span, ACO utilised by maximum researchers in the time span '2010-2015'. The present study also revealed GA has been executed by most of the researchers (25%), whereas PSO (8%) utilised by very least designers.Keywords: dynamic environment; meta-heuristic; optimisation; facility layout planning; hybrid approaches.Reference to this paper should be made as follows: Sharma, P. and Singhal, S. A review on implementation of meta-heuristic approaches for layout problems 7Sandeep Singhal is currently working as an Associate Professor in Department of Mechanical Engineering, National Institute of Technology (NIT), Kurukshetra, Haryana, India, an institution of national importance. Currently, he is the Chairman of ISTE, Haryana Chapter. He is a PhD from NIT, Kurukshetra. He has more than 25 years of teaching, research and professional experience and has authored more than 40 research papers in reputed national and international peer reviewed journals and conferences. He has authored a book on entrepreneurship. His areas of interest are SCM, ERP, TQM, entrepreneurship, facility management, etc. He has worked with AICTE and NBA the apex regulatory body for technical education in various capacities for seven years and was closely associated with Washington Accord. He has guided/guiding research scholars at MTech and PhD levels.

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Section: Genetic Algorithmmentioning

confidence: 99%

A review on implementation of meta-heuristic approaches for layout problems in dynamic business environment

Sharma¹,

Singhal²

2016

IJMDA

View full text Add to dashboard Cite

show abstract

“…There are also several layout methods available which follow the genetic paradigm. These include genetic algorithms of Ficko, Brezocnik, and Balic (2004) and Datta et al (2011) as well as hybrid genetic algorithms of Ozcelik (2012) and Kothari and Ghosh (2014a). A similar evolutionary technique called the imperialist competitive algorithm was presented by Lian, Zhang, Gao, and Shao (2011).…”

Section: Introductionmentioning

confidence: 99%

“…From the literature, it can be seen that many algorithms for the SR-FLP incorporate a local search procedure (Amaral & Letchford, 2013;Heragu & Alfa, 1992;Heragu & Kusiak, 1991;Kothari & Ghosh, 2013a, 2014a, 2014bKumar et al, 2008;Ozcelik, 2012;Samarghandi & Eshghi, 2010;Solimanpur et al, 2005;Teo & Ponnambalam, 2008). Two main types of local searches have been used for this problem (Kothari & Ghosh, 2013b).…”

Section: Introductionmentioning

confidence: 99%

“…Two main types of local searches have been used for this problem (Kothari & Ghosh, 2013b). The first of them is based on pairwise interchanges of facilities (Amaral & Letchford, 2013;Heragu & Alfa, 1992;Heragu & Kusiak, 1991;Kothari & Ghosh, 2013a;Samarghandi & Eshghi, 2010;Solimanpur et al, 2005;Teo & Ponnambalam, 2008), whereas the second one proceeds by executing insertion moves, where a facility is moved from one position to another in the permutation (Kothari & Ghosh, 2013a, 2014a, 2014bKumar et al, 2008;Ozcelik, 2012). The performance of local search (LS) algorithms greatly depends on the neighborhood exploration (NE) procedures (Kothari & Ghosh, 2013a).…”

Section: Introductionmentioning

confidence: 99%

“…Recently, Kothari and Ghosh (2013a) developed NE procedures (for both interchange and insertion neighborhood structures) whose time complexity is O(n 3 ). The algorithms of Kothari and Ghosh (2013a, 2013b, 2014a, 2014b use these procedures and show good performance compared to other methods in the literature.…”

Section: Introductionmentioning

confidence: 99%

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