A large-scale hybrid simulated annealing algorithm for cyclic facility layout problems

Kulturel-Konak, Sadan; Konak, Abdullah

doi:10.1080/0305215x.2014.933825

Cited by 51 publications

(29 citation statements)

References 36 publications

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“…These two problems were also used by Dunker et al (2005), Mckendall & Hakobyan (2010) and Derakhshan Asl and Wong (2017) to test the performance of their solution approaches. Kulturel- Konak and Konak (2015) used P6 and P12 problems in their study by relaxing the assumption of fixed dimensions of facilities and used common maximum aspect ratio as two but their solution approach is not for the flexible bay structure arrangement. Kulturel- Konak and Konak (2015) gave the P15 problem for the UA-DFLPs literature which has 15-facility with 3-period in the planning horizon.…”

Section: Proposed Sa Heuristic For Unequal Area Dflps Data Setmentioning

confidence: 99%

“…Kulturel- Konak and Konak (2015) used P6 and P12 problems in their study by relaxing the assumption of fixed dimensions of facilities and used common maximum aspect ratio as two but their solution approach is not for the flexible bay structure arrangement. Kulturel- Konak and Konak (2015) gave the P15 problem for the UA-DFLPs literature which has 15-facility with 3-period in the planning horizon. Test problems DFLP-12-3, DFLP-12-5 and DFLP-20-3 are from Lacksonen (1997).…”

Section: Proposed Sa Heuristic For Unequal Area Dflps Data Setmentioning

confidence: 99%

“…Tam (1992) used SA for general type UA-FLPs but not for UA-DFLP with FBS. Recently, Kulturel- Konak and Konak (2015) used SA heuristic to solve unequal area cyclic facility layout problems, but it is not based on FBS. The research works (Kusiak & Heragu, 1987;Balakrishnan & Cheng, 1998;Singh & Sharma, 2006;Drira, et al, 2007;Moslemipour et al, 2012) give the detailed review of various types of facility layout problems and different heuristic and meta-heuristic approaches followed to solve the FLPs.…”

Section: Literature Reviewmentioning

confidence: 99%

“…However, fixed dimension facilities lead to poor space utilisation and unnecessary rearrangement of facilities in the planning horizon. Kulturel- Konak and Konak (2015) considered aspect ratio constraint for facilities to solve the unequal area cyclic facility layout problem. In this model, authors considered the north-east and south-west (i.e., diagonal) corners of the facilities to quantify the rearrangement costs.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Researchers (Dunker et al, 2005;McKendall & Hakobyan, 2010;Derakhshan Asl & Wong 2017) used various meta-heuristics like combined GA and dynamic programming, boundary search and tabu search heuristics, and particle swarm optimization to solve fixed shape facilities problem of P6 and P12. Kulturel- Konak and Konak (2015) apply large scale simulated annealing algorithm as solution methodology to solve P6, P12, P15, DFLP-12-3, DFLP-12-5 and DFLP-20-3 problems with aspect ratio constraint for the facilities and without FBS in layout. Table 6 gives the comparison of PHC of proposed FBS based SA heuristic with other meta-heuristics used for solving UA-DFLPs without bays formation in the layout.…”

Section: Performance Comparison Of the Proposed Sa Heuristic For Ua-dmentioning

confidence: 99%

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A simulated annealing algorithm for unequal area dynamic facility layout problems with flexible bay structure

Hunagund¹,

Pillai²,

Kempaiah³

2018

10.5267/j.ijiec

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In this article, we propose Simulated Annealing (SA) heuristic to solve Unequal Area Dynamic Facility Layout Problem (FBS) with Flexible Bay Structure (UA-DFLPs with FBS). The UA-DFLP with FBS is the problem of determining the facilities dimension and their location coordinates with flexible bays formation in the layout for various periods of the planning horizon. The UA-DFLP with FBS is more constrained than general UA-DFLP and it is an NP-complete problem. The proposed SA is tested with the available UA-DFLPs instances in the literature. The proposed SA heuristic has given new best solution or the same solution for FBS based problems as compared with the best-known reported in the UA-DFLPs with FBS literature. The proposed SA heuristic is also tested on standard UA-DFLPs used in non-FBS approaches. The SA heuristic solution is not significantly different from the best solution reported in the literature for non-FBS approaches. Equal area DFLP instances are also solved with the proposed SA and the results obtained are promising with the solutions reported in the literature. Hence the results obtained indicate that the proposed SA for UA-DFLP with FBS is effective and versatile for both equal and unequal area dynamic facility layout problems. The computational efficiency of the proposed SA heuristic is very much competitive as compared to other meta-heuristics computational timings reported in the literature.

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Section: Proposed Sa Heuristic For Unequal Area Dflps Data Setmentioning

confidence: 99%

Section: Proposed Sa Heuristic For Unequal Area Dflps Data Setmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Performance Comparison Of the Proposed Sa Heuristic For Ua-dmentioning

confidence: 99%

See 3 more Smart Citations

A simulated annealing algorithm for unequal area dynamic facility layout problems with flexible bay structure

Hunagund¹,

Pillai²,

Kempaiah³

2018

10.5267/j.ijiec

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Driver Analysis to Solve Dynamic Facility Layout Problems: A Literature Review

Sotamba,

Peña,

Siguenza-Guzman

2023

Flexible Automation and Intelligent Manufacturing: Establishing Bridges for More Sustainable Manufacturing Systems

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Experimental Examination of Facilities Layout Problems in Logistics Systems Including Objects with Diverse Sizes and Shapes

Grobelny

Michalski

2016

Advances in Intelligent Systems and Computing

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This study demonstrates a simulation experiment results regarding a flexible approach to solving facilities layout problem on a regular grid. In this paper approach we model objects with different dimensions and various shapes. We have implemented our version of the simulated annealing algorithm (Kirkpatrick et al., 1983) and analyzed how the number of cycles (100, 200, 300), objects types (uniform, diverse) affect average goal function values, mean concentration degrees, and the number of disintegrated objects. The formal statistical analysis was conducted separately for two sizes of regular grids, i.e. 66 and 1010. The outcomes generally showed a significant influence of the studied effects on the analyzed dependent variables.

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A large-scale hybrid simulated annealing algorithm for cyclic facility layout problems

Cited by 51 publications

References 36 publications

A simulated annealing algorithm for unequal area dynamic facility layout problems with flexible bay structure

A simulated annealing algorithm for unequal area dynamic facility layout problems with flexible bay structure

Driver Analysis to Solve Dynamic Facility Layout Problems: A Literature Review

Experimental Examination of Facilities Layout Problems in Logistics Systems Including Objects with Diverse Sizes and Shapes

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