A bottom-up multi-objective optimisation approach to dynamic facility layout planning

Dynamic facility layout planning (DFLP) involves determining an appropriate arrangement scheme of the elements making up the production system for each time period into which the planning horizon is divided. When formulating the problem as an optimisation model, using the traditional top-down approa...

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Bibliographic Details
Published in:International journal of production research Vol. 62; no. 3; pp. 626 - 643
Main Authors: Pérez-Gosende, Pablo, Mula, Josefa, Díaz-Madroñero, Manuel
Format: Journal Article
Language:English
Published: London Taylor & Francis 01.02.2024
Taylor & Francis LLC
Subjects:
Block layout
Facility layout
facility planning
Integer programming
Linear programming
Materials handling
Mixed integer
mixed integer linear programming
multicriteria decision making
Multiple criteria decision making
Multiple objective analysis
non-linear programming
Nonlinear programming
Optimization
ISSN:0020-7543, 1366-588X
Online Access:Get full text
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Summary:Dynamic facility layout planning (DFLP) involves determining an appropriate arrangement scheme of the elements making up the production system for each time period into which the planning horizon is divided. When formulating the problem as an optimisation model, using the traditional top-down approach is usual, which firstly determines the block layout (BL) and then the detailed layout (DL) of each work cell. However by this approach, the BL generates area constraints in the detailed phase, which sometimes limit its implementation. In this context, the present paper presents a multi-objective mixed integer non-linear programming (MOMINLP) model that allows the problem to be addressed by considering an alternative approach, known in the literature as the bottom-up approach. The proposed model, called bottom-up mDFLP, considers three objective functions: (1) minimise the total material handling cost (TMHC) and the total rearrangement cost (TRAC); (2) maximise the total closeness rating (TCR) between departments; (3) maximise the area utilisation ratio (AUR). The original MOMINLP is transformed into a more computationally efficient multi-objective mixed integer linear programming (MOMILP) model. The proposed model is applied and validated in a case study of a company in the metal-mechanic sector with 12 departments for three 4-month periods.
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ISSN:0020-7543
1366-588X
DOI:10.1080/00207543.2023.2168308