Genetic search and the dynamic layout problem

Balakrishnan, Jaydeep; Cheng, Chun Hung

doi:10.1016/s0305-0548(99)00052-0

Cited by 108 publications

(53 citation statements)

References 4 publications

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“…At any rate, based on our own experimentation and those of others, 7,8 it appears that the GAs are generally not competitive. The SA due to Baykasoglu and Gindy 8 (SA_BG) on the other hand, appears to be quite competitive (for the larger problem instances in particular) and the FORTRAN code has been readily available to us (as part of the Baykasoglu-Gindy paper).…”

Section: Computational Studymentioning

confidence: 71%

New heuristic for the dynamic layout problem

Erel

Ghosh

Simon

2003

Journal of the Operational Research Society

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The dynamic layout problem addresses the situation where the traffic among the various units within a facility changes over time. Its objective is to determine a layout for each period in a planning horizon such that the total of the flow and the relocation costs is minimized. The problem is computationally very hard and has begun to receive attention only recently. In this paper, we present a new heuristic scheme, based on the idea of viable layouts, which is easy to operationalize. A limited computational study shows that, depending upon how it is implemented, this scheme can be reasonably fast and can yield results that are competitive with those from other available solution methods.

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Section: Computational Studymentioning

confidence: 71%

New heuristic for the dynamic layout problem

Erel

Ghosh

Simon

2003

Journal of the Operational Research Society

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“…The dynamic environment QAP is still more complex than static QAP due to an introduction of periods in the dynamic QAP. Hence researchers use different meta-heuristic methods to solve equal area DFLPs (Conway & Venkataramanan, 1994;Balakrishnan & Cheng, 2000;Baykasoglu & Gindy, 2001;Balakrishnan et al, 2003;McKendall et al, 2006;Yang et al, 2011;Pourvaziri & Naderi, 2014;Bozorgi et al, 2015). Pillai et al (2011) and Forghani et al (2013) used the robust approach to solve equal area DFLPs.…”

Section: Literature Reviewmentioning

confidence: 99%

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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“…They claim their proposed algorithm finds better solution. They compared their proposed algorithm to the three works done [18][19][20]. In the first comparison, their SA approach found optimum solution and revealed better solution than dynamic programming algorithm of Rosenblatt [18].…”

Section: Literature Reviewmentioning

confidence: 99%

“…The optimum solution was not found; however, the results of SA showed a slight improvement over that of Rosenblatt [18]. Finally, in the third comparison the data set obtained from Balakrishnan and Cheng [20]. They develop non-linear genetic algorithm (NLGA).…”

Section: Literature Reviewmentioning

confidence: 99%

Facility Layout Problem for Cellular Manufacturing Systems

Allahyari¹,

Azab²

2017

Computational Optimization in Engineering - Paradigms and Applications

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Good layout plan leads to in improve machine utilization, part demand quality, efficient setup time, less work-in-process inventory and material handling cost. Cellular Manufacturing (CM) is an application of GTCM is the combination of job shop and/or flow shop. Facility Layout Problem (FLP) for CMS includes both inter-cell layout and intra-cell layout. A bi-level mixed-integer non-linear programming continuous model has been formulated to fully define the problem and the relationship between intra-cell and inter-cell layout design. Facilities are assumed unequal size; operation sequences, part demands, overlap elimination, aisle are considered. The problem is NP-hard; hence, a simulated annealing meta-heuristic employing a novel constructive radial-based heuristic for initialization have been designed and implemented. For the first time, a novel heuristic algorithm has been designed to allocate and displace facilities in radial direction. In order to improve the search efficiency of the developed SA algorithm, the cell size used in the initialization heuristic algorithm is assumed twice as that of the original size of the cells. A real case study from the metal cutting inserts industry has been used. Results demonstrate the superiority of the developed SA algorithm against rival comparable meta-heuristics and algorithms from the literature.

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Genetic search and the dynamic layout problem

Cited by 108 publications

References 4 publications

New heuristic for the dynamic layout problem

New heuristic for the dynamic layout problem

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

Facility Layout Problem for Cellular Manufacturing Systems

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