106
6 Engineering Applications of Facility Layout
the reader can compute the flows using the information provided. The defence
application in Sect. 6.3 is from Balamurugan (2012).
The shoe manufacturing application in Sect. 6.4 is from Ulutas and Islier (2015),
where it is considered in the broader context of the DFLP. We have presented
the data for one period, i.e., we consider a static (as opposed to dynamic) layout
problem. We thank the authors for providing this data.
The battery example in Sect. 6.5 is from Liu et al (2017); note that the matrix
of flow costs in their Appendix A.2 is not symmetric, but this appears to be a typo.
The evacuation example in Sect. 6.6 is from Hahn et al (2010), and the automotive
assembly example in Sect. 6.7 is from Kovács (2020).
The plastic parts example in Sect. 6.8 is from Azevedo et al (2017). The authors
propose a multi-objective approach for a QAP; their work includes additional
technical details and data that are not included here.
In Sect. 6.9 three hospital applications are presented. The university hospital
example in Sect. 6.9.1 is from Krarup and Pruzan (1978), and the data for this
instance is available on the QAPLIB (Burkard et al 1997) accessible at https://
www.miguelanjos.com/qaplib. The emergency service case in Sect. 6.9.2 is from
Zuo et al (2019). Their matrix of patient flows includes some nonzero diagonal
entries. These values arise when a patient visits the same department twice, but we
have omitted them because in these cases the distance travelled by the patient is
zero. They considered closeness ratings in addition to the flows; the ratings were
introduced in Heragu (2008). Finally, the Egyptian hospital example in Sect. 6.9.3
is from Elshafei (1977). The data for this instance can also be found on the QAPLIB.
References
Azevedo MM, Crispim JA, Pinho de Sousa J (2017) A dynamic multi-objective approach for the
reconfigurable multi-facility layout problem. J Manuf Syst 42:140–152
Balamurugan K (2012) Application of simulation and genetic algorithm for machine layout design.
J Inf Optim Sci 33(6):653–664
Burkard RE, Karisch SE, Rendl F (1997) QAPLIB—a quadratic assignment problem library. J
Global Optim 10(4):391–403
El-Baz MA (2004) A genetic algorithm for facility layout problems of different manufacturing
environments. Comput Ind Eng 47(2):233–246
Elshafei AN (1977) Hospital layout as a quadratic assignment problem. Oper Res Q 28(1):167–179
Hahn P, MacGregor Smith J, Zhu YR (2010) The multi-story space assignment problem. Ann Oper
Res 179(1):77–103
Heragu SS (2008) Facilities design. CRC Press
Kovács G (2020) Combination of lean value-oriented conception and facility layout design for even
more significant efficiency improvement and cost reduction. Int J Prod Res 58(10):2916–2936
Krarup J, Pruzan PM (1978) Computer-aided layout design. Springer, Berlin, Heidelberg, pp 75–94
Liu J, Wang D, He K, Xue Y (2017) Combining Wang–Landau sampling algorithm and heuristics
for solving the unequal-area dynamic facility layout problem. Eur J Oper Res 262(3):1052–
1063
6 Engineering Applications of Facility Layout
the reader can compute the flows using the information provided. The defence
application in Sect. 6.3 is from Balamurugan (2012).
The shoe manufacturing application in Sect. 6.4 is from Ulutas and Islier (2015),
where it is considered in the broader context of the DFLP. We have presented
the data for one period, i.e., we consider a static (as opposed to dynamic) layout
problem. We thank the authors for providing this data.
The battery example in Sect. 6.5 is from Liu et al (2017); note that the matrix
of flow costs in their Appendix A.2 is not symmetric, but this appears to be a typo.
The evacuation example in Sect. 6.6 is from Hahn et al (2010), and the automotive
assembly example in Sect. 6.7 is from Kovács (2020).
The plastic parts example in Sect. 6.8 is from Azevedo et al (2017). The authors
propose a multi-objective approach for a QAP; their work includes additional
technical details and data that are not included here.
In Sect. 6.9 three hospital applications are presented. The university hospital
example in Sect. 6.9.1 is from Krarup and Pruzan (1978), and the data for this
instance is available on the QAPLIB (Burkard et al 1997) accessible at https://
www.miguelanjos.com/qaplib. The emergency service case in Sect. 6.9.2 is from
Zuo et al (2019). Their matrix of patient flows includes some nonzero diagonal
entries. These values arise when a patient visits the same department twice, but we
have omitted them because in these cases the distance travelled by the patient is
zero. They considered closeness ratings in addition to the flows; the ratings were
introduced in Heragu (2008). Finally, the Egyptian hospital example in Sect. 6.9.3
is from Elshafei (1977). The data for this instance can also be found on the QAPLIB.
References
Azevedo MM, Crispim JA, Pinho de Sousa J (2017) A dynamic multi-objective approach for the
reconfigurable multi-facility layout problem. J Manuf Syst 42:140–152
Balamurugan K (2012) Application of simulation and genetic algorithm for machine layout design.
J Inf Optim Sci 33(6):653–664
Burkard RE, Karisch SE, Rendl F (1997) QAPLIB—a quadratic assignment problem library. J
Global Optim 10(4):391–403
El-Baz MA (2004) A genetic algorithm for facility layout problems of different manufacturing
environments. Comput Ind Eng 47(2):233–246
Elshafei AN (1977) Hospital layout as a quadratic assignment problem. Oper Res Q 28(1):167–179
Hahn P, MacGregor Smith J, Zhu YR (2010) The multi-story space assignment problem. Ann Oper
Res 179(1):77–103
Heragu SS (2008) Facilities design. CRC Press
Kovács G (2020) Combination of lean value-oriented conception and facility layout design for even
more significant efficiency improvement and cost reduction. Int J Prod Res 58(10):2916–2936
Krarup J, Pruzan PM (1978) Computer-aided layout design. Springer, Berlin, Heidelberg, pp 75–94
Liu J, Wang D, He K, Xue Y (2017) Combining Wang–Landau sampling algorithm and heuristics
for solving the unequal-area dynamic facility layout problem. Eur J Oper Res 262(3):1052–
1063