Parallel variable neighborhood search for solving fuzzy multi-objective dynamic facility layout problem

Abedzadeh, Mostafa; Mazinani, Mostafa; Moradinasab, Nazanin; Roghanian, Emad

doi:10.1007/s00170-012-4160-x

Cited by 27 publications

(26 citation statements)

References 44 publications

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“…The limitation in the solution methodology (GA) of the Mazinani et al (2013) is that it can only be used for given maximum number of bays as input data. Further, Abedzadeh et al (2013) presented the multi-objective formulation for UA-DFLP with FBS and authors used the parallel variable neighbourhood search and fuzzy concept as a solution method. Simulated Annealing (SA) is another simple meta-heuristic used to solve combinatorial problems.…”

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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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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“…Norman and Smith [21], Norman and Smith [22], and Enea et al [8] studied FBLP with uncertain material flows; Lee et al [16], Aiello et al [2], Kulturel-Konak et al [15], Ardestani-Jaafari et al [4], and Aiello et al [3] studied multi-objective FBLP. Recently, Mazinani et al [18] and Abedzadeh et al [1] studied dynamic FBLP in which material flow can be changed over periods. Mazinani et al [18] developed a genetic algorithm for single-period and multi-period FBLP with minimizing material handling and relayout cost.…”

Section: Introductionmentioning

confidence: 99%

“…Mazinani et al [18] developed a genetic algorithm for single-period and multi-period FBLP with minimizing material handling and relayout cost. Abedzadeh et al [1] proposed a mixed integer programming formulation with three objectives: minimizing material handling and relayout cost, maximizing adjacency ratio, and minimizing shape ratio difference. They applied fuzzy programming technique for multi-objective FBLP and developed parallel variable neighborhood search algorithm to solve large instances.…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, we correct the formulation proposed by Abedzadeh et al [1]. This correction is mainly focused on the three objectives of their formulation.…”

Section: Introductionmentioning

confidence: 99%

“…Finally, we correct their fuzzy programming technique of solving multi-objective FBLP in section 5. To prevent any confusion, we number the objectives and the constraints as numbered in Abedzadeh et al [1].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A note on “Parallel variable neighborhood search for solving fuzzy multi-objective dynamic facility layout problem”

Ardestani-Jaafari

2014

Int J Adv Manuf Technol

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Abedzadeh et al. (Int J Adv Manuf Technol 65:197-211, 2013) proposed a mixed integer programming formulation for dynamic flexible bay layout problem with three objectives: minimizing material handling and relayout cost, maximizing adjacency ratio, and minimizing shape ratio difference. In this paper, we correct the formulation proposed by Abedzadeh et al. (Int J Adv Manuf Technol 65:197-211, 2013). This correction is mainly focused on the three objectives of their formulation. It is shown that the relayout cost was miscalculated, the adjacency ratio was improperly linearized, the third objective was incorrectly linearized and fuzzy programming technique for multi-objective linear programming problems was not applied correctly for this problem.

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Reference Optimisation Models for Facility Layout Planing in the Metal-Mechanic Industry

Pérez-Gosende

Mula

Díaz‐Madroñero

2023

Lecture Notes on Data Engineering and Communications Technologies

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Parallel variable neighborhood search for solving fuzzy multi-objective dynamic facility layout problem

Cited by 27 publications

References 44 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

A note on “Parallel variable neighborhood search for solving fuzzy multi-objective dynamic facility layout problem”

Reference Optimisation Models for Facility Layout Planing in the Metal-Mechanic Industry

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