Layout optimization methods and tools: A systematic literature review

Authors

  • Lucas Stelle Chemim
  • Nicolle Christine Sotsek UFPR
  • Mariana Kleina

DOI:

https://doi.org/10.15675/gepros.v16i4.2806

Keywords:

Layout Optimization, Algorithm, Method, Facility Layout Planning

Abstract

Purpose: This article aims to show the methods used to optimize layout and tools that have been applied since 2010 in the most diverse production environments.
Theoretical Reference: Due to the intense competitiveness and uncertainties in the current market, improving processes and increasing production efficiency by managing the layout of a facility can be one of the methods to benefit organizations. In this context, knowledge of the main tools and methods is essential in defining the conduct of studies.
Design/methodology/approach: Research was carried out through a systematic literature review. The databases used were Science Direct and Portal Capes. Using keywords, a defined scope and the relevance of the theme, international articles were selected for reading and discussion.
Findings: Through the review, it was possible to select 51 articles which were relevant to the topic. Due to the complexity of the layout management study, it was found that increasingly more algorithms, mathematical and computational models are being used to solve these NP-hardness problems.
Research, Practical & Social implications: adjusting to new methods and ways of solving problems laying out facilities, although scenarios can be extremely varied, they can improve business results by making the process more efficient.
Originality/value: The article compiles and briefly explains the methods found to optimize the layout, which is of great importance considering the knowledge that these models spread on production management practices.
Keywords: Layout optimization. Algorithm. Method. Facility layout planning.

References

AFROOZ, Sonia; NAVIMIPOUR, Nima Jafari. Memory designing using quantum-dot cellular automata: systematic literature review, classification and current trends. Journal of Circuits, Systems and Computers, v. 26, n. 12, p. 1730004, 2017. DOI: https://doi.org/10.1142/S0218126617300045

AHMAD, Muhammad Ovais et al. Kanban em engenharia de software: Um estudo de mapeamento sistemático. Journal of Systems and Software , v. 137, p. 96-113, 2018.

ANJOS, Miguel F.; VIEIRA, Manuel VC. Mathematical optimization approaches for facility layout problems: The state-of-the-art and future research directions. European Journal of Operational Research, v. 261, n. 1, p. 1-16, 2017. DOI: https://doi.org/10.1016/j.ejor.2017.01.049

AIELLO, G; LA SCALIA, G; ENEA, M. A multi objective genetic algorithm for the facility layout problem based upon slicing structure encoding, Expert Systems with Applications, v. 39, 10352-10358, 2012. DOI: https://doi.org/10.1016/j.eswa.2012.01.125

AIELLO, G; LA SCALIA, G; ENEA, M. A non dominated ranking Multi Objective Genetic Algorithm and electre method for unequal area facility layout problems, Expert Systems with Applications, v.40, 4812-4819, 2013. DOI: https://doi.org/10.1016/j.eswa.2013.02.026

AZADEH, Ali et al. An integrated fuzzy simulation-fuzzy data envelopment analysis algorithm for job-shop layout optimization: the case of injection process with ambiguous data. European Journal of Operational Research, v. 214, n. 3, p. 768-779, 2011. DOI: https://doi.org/10.1016/j.ejor.2011.05.015

AZADEH, A.; HAGHIGHI, S. Motevali; ASADZADEH, S. M. A novel algorithm for layout optimization of injection process with random demands and sequence dependent setup times. Journal of Manufacturing Systems, v. 33, n. 2, p. 287-302, 2014. DOI: https://doi.org/10.1016/j.jmsy.2013.12.008

CAPUTO, Antonio C. et al. Safety-based process plant layout using genetic algorithm. Journal of Loss Prevention in the Process Industries, v. 34, p. 139-150, 2015. DOI: https://doi.org/10.1016/j.jlp.2015.01.021

CHANG, Mei-Shiang; KU, Ting-Chen. A slicing tree representation and QCP-model-based heuristic algorithm for the unequal-area block facility layout problem. Mathematical Problems in Engineering, v. 2013, 2013. DOI: https://doi.org/10.1155/2013/853586

CHE, Ada; ZHANG, Yipei; FENG, Jianguang. Bi-objective optimization for multi-floor facility layout problem with fixed inner configuration and room adjacency constraints. Computers & Industrial Engineering, v. 105, p. 265-276, 2017. DOI: https://doi.org/10.1016/j.cie.2016.12.018

DATTA, Dilip; AMARAL, André RS; FIGUEIRA, José Rui. Single row facility layout problem using a permutation-based genetic algorithm. European Journal of Operational Research, v. 213, n. 2, p. 388-394, 2011. DOI: https://doi.org/10.1016/j.ejor.2011.03.034

D’ANTONIO, Gianluca et al. An integrated mathematical model for the optimization of hybrid product-process layouts. Journal of manufacturing systems, v. 46, p. 179-192, 2018. DOI: https://doi.org/10.1016/j.jmsy.2017.12.003

DEB, Kalyanmoy. Multi-objective optimisation using evolutionary algorithms: an introduction. In: Multi-objective evolutionary optimisation for product design and manufacturing. Springer, London, 2011. p. 3-34. DOI: https://doi.org/10.1007/978-0-85729-652-8_1

DE CARLO, Filippo et al. Layout design for a low capacity manufacturing line: a case study. International Journal of Engineering Business Management, v. 5, n. Godište 2013, p. 5-35, 2013. DOI: https://doi.org/10.5772/56883

FRIEDRICH, Christian; KLAUSNITZER, Armin; LASCH, Rainer. Integrated slicing tree approach for solving the facility layout problem with input and output locations based on contour distance. European Journal of Operational Research, v. 270, n. 3, p. 837-851, 2018. DOI: https://doi.org/10.1016/j.ejor.2018.01.001

GARCÍA-HERNÁNDEZ, Laura et al. An evolutionary neural system for incorporating expert knowledge into the UA-FLP. Neurocomputing, v. 135, p. 69-78, 2014 DOI: https://doi.org/10.1016/j.neucom.2013.01.068

GARCÍA‐HERNÁNDEZ, Laura et al. Facility layout design using a multi‐objective interactive genetic algorithm to support the DM. Expert Systems, v. 32, n. 1, p. 94-107, 2015. DOI: https://doi.org/10.1111/exsy.12064

GARCÍA-HERNÁNDEZ, Laura et al. A novel hybrid evolutionary approach for capturing decision maker knowledge into the unequal area facility layout problem. Expert Systems with Applications, v. 42, n. 10, p. 4697-4708, 2015. DOI: https://doi.org/10.1016/j.eswa.2015.01.037

GARCIA-HERNANDEZ, L. et al. Resolver problemas de layout de instalações de áreas desiguais com o algoritmo de otimização de recife de coral com camadas de substrato. Aplicações de Engenharia de Inteligência Artificial , v. 93, p. 103697, 2020.

GARCÍA-HERNÁNDEZ, Laura et al. Applying the coral reefs optimization algorithm for solving unequal area facility layout problems. Expert Systems with Applications, v. 138, p. 112819, 2019. DOI: https://doi.org/10.1016/j.eswa.2019.07.036

GOLDBERG.D.E. Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley, New Jersey, USA (1989).

GONÇALVES, José Fernando; RESENDE, Mauricio GC. Um algoritmo genético de chave aleatória tendencioso para o problema de layout de instalações em áreas desiguais. European Journal of Operational Research, v. 246, n. 1, pág. 86-107, 2015.

GONZÁLEZ-CRUZ, Ma Carmen; MARTÍNEZ, Eliseo Gómez-Senent. An entropy-based algorithm to solve the facility layout design problem. Robotics and Computer-Integrated Manufacturing, v. 27, n. 1, p. 88-100, 2011. DOI: https://doi.org/10.1016/j.rcim.2010.06.015

GUAN, Chao et al. Multi-objective particle swarm optimization for multi-workshop facility layout problem. Journal of Manufacturing Systems, v. 53, p. 32-48, 2019. DOI: https://doi.org/10.1016/j.jmsy.2019.09.004

GUAN, Jian et al. A decomposition-based algorithm for the double row layout problem. Applied Mathematical Modelling, v. 77, p. 963-979, 2020. DOI: https://doi.org/10.1016/j.apm.2019.08.015

HADI-VENCHEH, A.; MOHAMADGHASEMI, A. An integrated AHP–NLP methodology for facility layout design. Journal of Manufacturing Systems, v. 32, n. 1, p. 40-45, 2013. DOI: https://doi.org/10.1016/j.jmsy.2012.07.009

HERNÁNDEZ-GRESS, Eva Selene et al. The solution of the concurrent layout scheduling problem in the job-shop environment through a local neighborhood search algorithm. Expert Systems with Applications, v. 144, p. 113096, 2020. DOI: https://doi.org/10.1016/j.eswa.2019.113096

HO, Nicholas; NGOOI, Syn-Dee; CHUI, Chee-Kong. Optimization of workcell layout for hybrid medical device fabrication. Journal of Manufacturing Systems, v. 50, p. 163-179, 2019. DOI: https://doi.org/10.1016/j.jmsy.2018.12.010

JANKOVITS, Ibolya et al. A convex optimisation framework for the unequal-areas facility layout problem. European Journal of Operational Research, v. 214, n. 2, p. 199-215, 2011. DOI: https://doi.org/10.1016/j.ejor.2011.04.013

JIANG, S.; NEE, A. Y. C. A novel facility layout planning and optimization methodology. CIRP Annals, v. 62, n. 1, p. 483-486, 2013. DOI: https://doi.org/10.1016/j.cirp.2013.03.133

KANNAN, V.R. Analyzing the Trade-off Between Efficiency and Flexibility in Cellular Manufacturing Systems. Production Planning & Control, v. 9, n.4, p. 572-579, 2010. DOI: https://doi.org/10.1080/095372898233821

KITCHENHAM, Barbara et al. Systematic literature reviews in software engineering–a systematic literature review. Information and software technology, v. 51, n. 1, p. 7-15, 2009. DOI: https://doi.org/10.1016/j.infsof.2008.09.009

LINDSKOG, Erik; VALLHAGEN, Johan; JOHANSSON, Björn. Production system redesign using realistic visualisation. International Journal of Production Research, v. 55, n. 3, p. 858-869, 2017. DOI: https://doi.org/10.1080/00207543.2016.1218085

LIU, Jingfa; LIU, Jun. Applying multi-objective ant colony optimization algorithm for solving the unequal area facility layout problems. Applied Soft Computing, v. 74, p. 167-189, 2019. DOI: https://doi.org/10.1016/j.asoc.2018.10.012

LIU, Jingfa et al. Combining Wang–Landau sampling algorithm and heuristics for solving the unequal-area dynamic facility layout problem. European Journal of Operational Research, v. 262, n. 3, p. 1052-1063, 2017. DOI: https://doi.org/10.1016/j.ejor.2017.04.002

LIU, Jingfa et al. Multi-objective particle swarm optimization algorithm based on objective space division for the unequal-area facility layout problem. Expert Systems with Applications, v. 102, p. 179-192, 2018. DOI: https://doi.org/10.1016/j.eswa.2018.02.035

LIU, Jingfa et al. A heuristic algorithm combining Pareto optimization and niche technology for multi-objective unequal area facility layout problem. Engineering Applications of Artificial Intelligence, v. 89, p. 103453, 2020. DOI: https://doi.org/10.1016/j.engappai.2019.103453

LIU, Jingfa et al. Configuration space evolutionary algorithm for multi-objective unequal-area facility layout problems with flexible bays. Applied Soft Computing, v. 89, p. 106052, 2020. DOI: https://doi.org/10.1016/j.asoc.2019.106052

LEE, Jonghwan; HAN, Soonhung; YANG, Jeongsam. Construction of a computer-simulated mixed reality environment for virtual factory layout planning. Computers in Industry, v. 62, n. 1, p. 86-98, 2011. DOI: https://doi.org/10.1016/j.compind.2010.07.001

MANZINI, Massimo et al. An integrated framework for design, management and operation of reconfigurable assembly systems. Omega, v. 78, p. 69-84, 2018. DOI: https://doi.org/10.1016/j.omega.2017.08.008

MATAI, Rajesh; SINGH, S. P.; MITTAL, M. L. Modified simulated annealing based approach for multi objective facility layout problem. International Journal of Production Research, v. 51, n. 14, p. 4273-4288, 2013. DOI: https://doi.org/10.1080/00207543.2013.765078

MEHTA, Nishita; PANDIT, Anil. Concurrence of big data analytics and healthcare: A systematic review. International journal of medical informatics, v. 114, p. 57-65, 2018. DOI: https://doi.org/10.1016/j.ijmedinf.2018.03.013

MOSCATO, Pablo et al. Sobre evolução, pesquisa, otimização, algoritmos genéticos e artes marciais: Rumo a algoritmos meméticos. Programa de computação simultânea Caltech, C3P Report , v. 826, p. 1989, 1989.

MOSLEMIPOUR, Ghorbanali; LEE, Tian Soon; RILLING, Dirk. A review of intelligent approaches for designing dynamic and robust layouts in flexible manufacturing systems. The International Journal of Advanced Manufacturing Technology, v. 60, n. 1-4, p. 11-27, 2012. DOI: https://doi.org/10.1007/s00170-011-3614-x

MUTHER, RICHARD. Planejamento do layout: Sistema SLP. Editora Edgard Blucher LTDA, São Paulo, São Paulo, 1978.

NEE, Andrew YC et al. Augmented reality applications in design and manufacturing. CIRP annals, v. 61, n. 2, p. 657-679, 2012. DOI: https://doi.org/10.1016/j.cirp.2012.05.010

NEGRÃO, J. Negrão, GIMENES, H.G, PEGO, L.A.S, SOTSEK, N.C, SANTOS, A.P.L. A Literature Systematic Review of Layout Rearrangement Methods, IX Congresso Brasileiro de Engenharia de Produção (2019), Ponta Grossa, PR, 2019.

NING, Xin et al. Reducing noise pollution by planning construction site layout via a multi-objective optimization model. Journal of cleaner production, v. 222, p. 218-230, 2019. DOI: https://doi.org/10.1016/j.jclepro.2019.03.018

PALOMO-ROMERO, Juan M.; SALAS-MORERA, Lorenzo; GARCÍA-HERNÁNDEZ, Laura. An island model genetic algorithm for unequal area facility layout problems. Expert Systems with Applications, v. 68, p. 151-162, 2017. DOI: https://doi.org/10.1016/j.eswa.2016.10.004

SAHAB, Mohammed Ghasem; TOROPOV, Vassili V .; GANDOMI, Amir Hossein. Uma revisão sobre otimização estrutural tradicional e moderna: problemas e técnicas. Aplicações metaheurísticas em estruturas e infraestruturas , p. 25-47, 2013.

SAMARGHANDI, Hamed; ESHGHI, Kourosh. An efficient tabu algorithm for the single row facility layout problem. European Journal of Operational Research, v. 205, n. 1, p. 98-105, 2010. DOI: https://doi.org/10.1016/j.ejor.2009.11.034

SAMARGHANDI, Hamed; TAABAYAN, Pouria; JAHANTIGH, Farzad Firouzi. A particle swarm optimization for the single row facility layout problem. Computers & Industrial Engineering, v. 58, n. 4, p. 529-534, 2010. DOI: https://doi.org/10.1016/j.cie.2009.11.015

SANJEEVI, Sujeevraja; KIANFAR, Kiavash. A polyhedral study of triplet formulation for single row facility layout problem. Discrete Applied Mathematics, v. 158, n. 16, p. 1861-1867, 2010. DOI: https://doi.org/10.1016/j.dam.2010.07.005

SALCEDO-SANZ, S. et al. The coral reefs optimization algorithm: a novel metaheuristic for efficiently solving optimization problems. The Scientific World Journal, v. 2014, 2014. DOI: https://doi.org/10.1155/2014/739768

SLACK, N., CHAMBERS, S., JOHNSTON, R. Administração da Produção, 2ª Edição. São Paulo: Editora Atlas, 2002.

SCHUH, Günther et al. Technology roadmapping for the production in high-wage countries. Production Engineering, v. 5, n. 4, p. 463-473, 2011. DOI: https://doi.org/10.1007/s11740-011-0324-z

SUMAN, Balram; KUMAR, Prabhat. A survey of simulated annealing as a tool for single and multiobjective optimization. Journal of the operational research society, v. 57, n. 10, p. 1143-1160, 2006. DOI: https://doi.org/10.1057/palgrave.jors.2602068

SILVA, C. S.; MORAIS, M. C.; FERNANDES, F. A. A practical methodology for cellular manufacturing systems design-An industrial study. Transaction on Control and Mechanical Systems, v. 2, n. 4, p. 198-211, 2012.

SINGH, Ajit Pal; YILMA, Manderas. Production floor layout using systematic layout planning in Can manufacturing company. In: 2013 International Conference on Control, Decision and Information Technologies (CoDIT). IEEE, 2013. p. 822-828. DOI: https://doi.org/10.1109/CoDIT.2013.6689649

TAYAL, Akash; SOLANKI, Arun; SINGH, Simar Preet. Integrated frame work for identifying sustainable manufacturing layouts based on big data, machine learning, meta-heuristic and data envelopment analysis. Sustainable Cities and Society, v. 62, p. 102383, 2020. DOI: https://doi.org/10.1016/j.scs.2020.102383

TOMPKINS, James A. et al. Facilities planning. John Wiley & Sons, 2010.

VITAYASAK, Srisatja; PONGCHAROEN, Pupong; HICKS, Chris. A tool for solving stochastic dynamic facility layout problems with stochastic demand using either a Genetic Algorithm or modified Backtracking Search Algorithm. International Journal of Production Economics, v. 190, p. 146-157, 2017. DOI: https://doi.org/10.1016/j.ijpe.2016.03.019

WONG, Kuan Yew et al. Applying ant system for solving unequal area facility layout problems. European Journal of Operational Research, v. 202, n. 3, p. 730-746, 2010. DOI: https://doi.org/10.1016/j.ejor.2009.06.016

WONG, Kuan Yew; SEE, Phen Chiak. A hybrid ant colony optimization algorithm for solving facility layout problems formulated as quadratic assignment problems. Engineering Computations, 2010.

ZAWIDZKI, Machi; SZKLARSKI, Jacek. Multi-objective optimization of the floor plan of a single story family house considering position and orientation. Advances in Engineering Software, v. 141, p. 102766, 2020. DOI: https://doi.org/10.1016/j.advengsoft.2019.102766

ZHANG, Yudong; WANG, Shuihua; JI, Genlin. A comprehensive survey on particle swarm optimization algorithm and its applications. Mathematical Problems in Engineering, v. 2015, 2015. DOI: https://doi.org/10.1155/2015/931256

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2021-12-13

How to Cite

Chemim, L. S., Sotsek, N. C., & Kleina, M. (2021). Layout optimization methods and tools: A systematic literature review. Revista Gestão Da Produção Operações E Sistemas, 16(4), 59. https://doi.org/10.15675/gepros.v16i4.2806

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