Abstract
The single-row facility layout problem (SRFLP) seeks the arrangement of given facilities along a straight row in such a way that the total material handling cost among the facilities is minimized. The SRFLP is studied till date as an unconstrained problem allowing the placement of the facilities in any location in any order without any restriction. However, a practical SRFLP instance may need to satisfy different types of constraints imposed on the placement of its facilities, e.g., the operation sequencing with precedence constraints in a process planning can be modeled as a SRFLP with ordering constraints. Such a SRFLP model, named as the constrained SRFLP (cSRFLP), is introduced here by instructing to place some facilities in fixed positions, and/or in specified orders with or without allowing the placement of other facilities in between two ordered facilities. Since it would be computationally too expensive for any search technique to satisfy such constraints, a permutation-based genetic algorithm (pGA), named as the constrained pGA (cpGA in short), is also proposed with some specially designed operators for exploring only feasible solutions of cSRFLP. In the numerical experimentation, investigating three case studies of the operation sequencing problem of process planning as cSRFLP instances, the cpGA found new sequences of operations with the same best-known objective value for the smaller-size case study, while improved the best-known solutions of the other two case studies of larger sizes. Further, transforming some large-size benchmark instances of SRFLP into cSRFLP, the cpGA found marginally inferior solutions than their best-known SRFLP solutions, which is obvious due to the constraints imposed in the transformed cSRFLP instances.
Similar content being viewed by others
References
Aiello G, Scalia GL, Enea M (2012) A multi objective genetic algorithm for the facility layout problem based upon slicing structure encoding. Expert Syst Appl 39:10352–10358
Anjos MF, Vannelli A (2008) Computing globally optimal solutions for single-row layout problems using semidefinite programming and cutting planes. INFORMS J Comput 20:611–617
Anjos MF, Yen G (2009) Provably near-optimal solutions for very large single-row facility layout problems. Optim Method Softw 24(4):805–817
Ayad AR, Awad HA, Yassin A (2013) Parametric analysis for genetic algorithms handling parameters. Alexandria Eng J 52:99–111
Branke J (2012) Evolutionary optimization in dynamic environments. Hardcover, ISBN: 978-0-7923-7631-6. Springer, US
Datta D, Amaral ARS, Figueira JR (2011) Single row facility layout problem using a permutation-based genetic algorithm. Eur J Oper Res 213(2):388–394
Datta D, Figueira JR (2011) Graph partitioning by multi-objective real-valued metaheuristics: a comparative study. Appl Soft Comput 11(5):3976–3987
Deb K (2001) Multi-objective optimization using evolutionary algorithms. Wiley, Chichester
Deb K, Agarwal S, Pratap A, Meyarivan T (2002) A fast and elitist multi-objective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 6(2):182–197
Drira A, Pierreval H, Hajri-Gabouj S (2007) Facility layout problems: a survey. Annu Rev Control 31:255–267
Heragu SS, Alfa AS (1992) Experiment analysis of simulated annealing based algorithms for the layout problem. Eur J Oper Res 57(2):190–202
Heragu SS, Kusiak A (1988) Machine layout problem in flexible manufacturing systems. Oper Res 36:258–268
Huang J, Lu X, Zhang G, Qu J (2014) Study on the rheological, thermal and mechanical properties of thermoplastic polyurethane/poly (butylene terephthalate) blends. Polym Test 36:69–74
Huang W, Lin W, Xu S (2017) Application of graph theory and hybrid GA-SA for operation sequencing in a dynamic workshop environment. Comput-Aid Des Appl 14(2):148–159
Javadi G, Aminian E (2017) A new method for tuning mutation and crossover rate in genetic algorithm. In: Proceedings of the 9th International Conference on Machine Learning and Computing, ICMLC 2017. ACM, New York, pp 217–220
Kafashi S (2011) Integrated setup planning and operation sequencing (ISOS) using genetic algorithm. Int J Adv Manuf Technol 56(5):589–600
Kothari R, Ghosh D (2013) Tabu search for the single row facility layout problem using exhaustive 2-opt and insertion neighborhoods. Eur J Oper Res 224(1):93–100
Kothari R, Ghosh D (2014) A scatter search algorithm for the single row facility layout problem. J Heuristics 20(2):125– 142
Krishna AG, Rao K (2006) Optimisation of operations sequence in CAPP using an ant colony algorithm. Int J Adv Manuf Technol 29(1–2):159–164
Kumar KR, Hadjinicola GC, Lin TL (1995) A heuristic procedure for the single-row facility layout problem. Eur J Oper Res 87:65–73
Kumar S, Asokan P, Kumanan S, Varma B (2008) Scatter search algorithm for single row layout problem in FMS. Advan Production Eng Manag 3:193–204
Lafou M, Mathieu L, Pois S, Alochet M (2016) Manufacturing system flexibility: sequence flexibility assessment. In: 49th CIRP Conference on Manufacturing System (CIRP CMS2016)
Li X, Gao L, Wen X (2013) Application of an efficient modified particle swarm optimization algorithm for process planning. Int J Adv Manuf Technol 67(5–8):1355–1369
Love RF, Wong JY (1976) On solving a single row space allocation problem with integer programming. INFOR 14:139–143
Luo G, Wen X, Li H, Ming W, Xie G (2017) An effective multi-objective genetic algorithm based on immune principle and external archive for multi-objective integrated process planning and scheduling. Int J Adv Manuf Technol 91(9–12):3145–3158
Maadi M, Javidnia M, Ramezani R (2017) Modified Cuckoo Optimization Algorithm (MCOA) to solve Precedence Constrained Sequencing Problem (PCSP). Applied Intelligence. https://doi.org/10.1007/s10489-017-1022-0
Miljković Z, Petrović M (2017) Application of modified multi-objective particle swarm optimisation algorithm for flexible process planning problem. Int J Comput Integr Manuf 30(2–3):271–291
Müller J (2016) MISO: Mixed-integer surrogate optimization framework. Optim Eng 17(1):177–203
Nallakumarasamy G, Srinivasan PSS, Raja KV, Malayalamurthi R (2011) Optimization of operation sequencing in CAPP using simulated annealing technique (SAT). Int J Adv Manuf Technol 54(5–8):721–728
Nguyen TT, Yang S, Branke J (2012) Evolutionary dynamic optimization: a survey of the state of the art. Swarm Evolutionary Comput 6:1–24
Ozgormus E (2015) Optimization of block layout for grocery stores. PhD thesis. Auburn University, USA
Padgaonkar AS (2004) Modelling and analysis of the hospital facility layout problem Master’s thesis. Department of Industrial and Manufacturing Engineering, New Jersey Institute of Technology
Petrović M, Mitić M, Vuković N, Miljković Z (2016) Chaotic particle swarm optimization algorithm for flexible process planning. Int J Adv Manuf Technol 85(9–12):2535–2555
Picard J, Queyranne M (1981) On the one dimensional space allocation problem. Oper Res 29(2):371–391
Reddy SB (1999) Operation sequencing in CAPP using genetic algorithms. Int J Prod Res 37(5):1063–1074
Samarghandi H, Eshghi K (2010) An efficient tabu algorithm for the single row facility layout problem. Eur J Oper Res 205:98–105
Samarghandi H, Taabayan P, Jahantigh FF (2010) A particle swarm optimization for the single row facility layout problem. Comput Industrial Eng 58:529–534
Simmons DM (1969) Single row space allocation: an ordering algorithm. Oper Res 17(5):812–826
Solimanpur M, Vrat P, Shankar R (2005) An ant algorithm for the single row layout problem in flexible manufacturing systems. Comput Oper Res 32:583–598
Sugden SJ (1992) A class of direct search methods for nonlinear integer programming. PhD Thesis, Bond University, Australia
Wang W, Li Y, Huang L (2016) Rule and branch-and-bound algorithm based sequencing of machining features for process planning of complex parts. Journal of Intelligent Manufacturing. https://doi.org/10.1007/s10845-015-1181-y
Wolpert DH, Macready WG (1997) No free lunch theorems for optimization. IEEE Trans Evol Comput 1 (1):67–82
Yun Y, Chung H, Moon C (2013) Hybrid genetic algorithm approach for precedence-constrained sequencing problem. Comput Industr Eng 65(1):137–147
Yun Y, Moon C (2011) Genetic algorithm approach for precedence-constrained sequencing problems. J Intell Manuf 22(3):379–388
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Kalita, Z., Datta, D. A constrained single-row facility layout problem. Int J Adv Manuf Technol 98, 2173–2184 (2018). https://doi.org/10.1007/s00170-018-2370-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00170-018-2370-6