A scatter search algorithm for the single row facility layout problem

Kothari, Ravi; Ghosh, Diptesh

doi:10.1007/s10732-013-9234-x

Cited by 48 publications

(42 citation statements)

References 37 publications

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“…The second column of Table 5 shows the best known values for the sko instances. We refer the reader to Table 4 in [25], which provides sources where these values come from. The second column of Tables 6 and 7 contains, for each instance, the value of the best solution obtained from all runs of all versions of MSA.…”

Section: Computational Results Of Multi-start Simulated Annealingmentioning

confidence: 99%

“…It is, however, clear that comparison of MSA with SS-1P is not fair because MSA was designed to solve the SREFLP, which is a special case of the SRFLP. We just say that the running times of SS-1P reported in [25] (on a different computer than we used) are significantly longer than those of MSA. For example, for the largest problem instance in Table 5, sko100-1, the SS-1P algorithm took 877 s on a PC with four Intel Core i5-2,500 3.30 GHz processors (see Table 5 in [25]).…”

Section: Instancementioning

confidence: 91%

“…We just say that the running times of SS-1P reported in [25] (on a different computer than we used) are significantly longer than those of MSA. For example, for the largest problem instance in Table 5, sko100-1, the SS-1P algorithm took 877 s on a PC with four Intel Core i5-2,500 3.30 GHz processors (see Table 5 in [25]). Our MSA algorithm with either P = 0 or P = 0.5 obtained the best known solution for the same instance in each of the 10 runs, taking 60 s per run.…”

Section: Instancementioning

confidence: 91%

“…We remark that the dataset of Anjos and Yen [5] has been used in several studies to test the performance of various algorithms for the SRFLP. One of the most recent studies is that of Kothari and Ghosh [25]. The authors developed four variants of the scatter search algorithm for the SRFLP and presented numerical results for one of them, named SS-1P.…”

Section: Instancementioning

confidence: 99%

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Fast simulated annealing for single-row equidistant facility layout

Palubeckis

2015

Applied Mathematics and Computation

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Section: Computational Results Of Multi-start Simulated Annealingmentioning

confidence: 99%

Section: Instancementioning

confidence: 91%

Section: Instancementioning

confidence: 91%

Section: Instancementioning

confidence: 99%

See 2 more Smart Citations

Fast simulated annealing for single-row equidistant facility layout

Palubeckis

2015

Applied Mathematics and Computation

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“…This approach also implemented by Pantrigo et al (2012). Kothari and Ghosh (2014b) suggested a SS algorithm for the single row facility layout problem. Saravanan and Arulkumar (2015) implemented artificial bee colony algorithm for design and optimise the fixed area layout problems.…”

Section: Tabu Searchmentioning

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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A Scatter Search Approach for the Facility Layout Problem with Aisle Design

Klausnitzer

2019

Operations Research Proceedings

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A scatter search algorithm for the single row facility layout problem

Cited by 48 publications

References 37 publications

Fast simulated annealing for single-row equidistant facility layout

Fast simulated annealing for single-row equidistant facility layout

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

A Scatter Search Approach for the Facility Layout Problem with Aisle Design

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