TY - JOUR
T1 - An optimisation approach for multi-floor facility layout design using flexible bays
AU - Enayaty-Ahangar, Forough
AU - Karimi, Behrooz
AU - Ahangar, Negin Enayaty
AU - Zadeh, Alireza Sheikh
N1 - Publisher Copyright:
© 2023 Inderscience Enterprises Ltd.. All rights reserved.
PY - 2023
Y1 - 2023
N2 - We present the problem of optimising a multi-floor facility layout using the flexible bay structure that assigns block-shaped departments in parallel bays. A mixed-integer linear programming formulation is proposed to solve this problem. The decisions are determining: 1) rectangular land dimensions; 2) the number of floors; 3) each floor’s layout with the bay structure. The proposed formulation minimises the total cost associated with the layout that includes land cost, floor construction cost, elevator installation cost, and material handling cost within and among floors. To address the challenge inherited from the problem’s combinatorial dynamics, we develop a genetic algorithm utilising novel crossovers and mutations. The model and the solution approach are tested on a suite of problems from the literature. Our computational results verify the model and demonstrate that the solution approach is able to find high-quality solutions for large-scale problems in less computational time compared to the standard software.
AB - We present the problem of optimising a multi-floor facility layout using the flexible bay structure that assigns block-shaped departments in parallel bays. A mixed-integer linear programming formulation is proposed to solve this problem. The decisions are determining: 1) rectangular land dimensions; 2) the number of floors; 3) each floor’s layout with the bay structure. The proposed formulation minimises the total cost associated with the layout that includes land cost, floor construction cost, elevator installation cost, and material handling cost within and among floors. To address the challenge inherited from the problem’s combinatorial dynamics, we develop a genetic algorithm utilising novel crossovers and mutations. The model and the solution approach are tested on a suite of problems from the literature. Our computational results verify the model and demonstrate that the solution approach is able to find high-quality solutions for large-scale problems in less computational time compared to the standard software.
KW - facility layout
KW - genetic algorithm
KW - metaheuristics
KW - mixed-integer linear programming
KW - optimisation
UR - http://www.scopus.com/inward/record.url?scp=85175350704&partnerID=8YFLogxK
U2 - 10.1504/IJISE.2023.134356
DO - 10.1504/IJISE.2023.134356
M3 - Article
AN - SCOPUS:85175350704
SN - 1748-5037
VL - 45
SP - 244
EP - 270
JO - International Journal of Industrial and Systems Engineering
JF - International Journal of Industrial and Systems Engineering
IS - 2
ER -