Today’s complicated business environment has underscored the importance of integrated decision-making in supply chains. In this paper, a novel mixed-integer nonlinear mathematical model is proposed to integrate cellular manufacturing systems into a three-stage supply chain to deal with customers’ changing demands, which has been little explored in the literature. This model determines the types of vehicles to transport raw materials and final parts, the suppliers to procure, the priorities of parts to be processed, and the cell formation to configure work centers. In addition, queueing theory is used to formulate the uncertainties in demands, processing times, and transportation times in the model more realistically. A linearization method is employed to facilitate the tractability of the model. A genetic algorithm is also developed to deal with the NP-hardness of the problem. Numerous instances are used to validate the effectiveness of the modeling and the efficiency of solution procedures. Finally, a sensitivity analysis and a real case study are discussed to provide important management insights and evaluate the applicability of the proposed model.
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DOI : 10.1051/ro/2021138
@article{RO_2021__55_6_3575_0,
author = {Esmailnezhad, Bahman and Saidi-mehrabad, Mohammad},
title = {Making an integrated decision in a three-stage supply chain along with cellular manufacturing under uncertain environments: {A} queueing-based analysis},
journal = {RAIRO. Operations Research},
pages = {3575--3602},
year = {2021},
publisher = {EDP-Sciences},
volume = {55},
number = {6},
doi = {10.1051/ro/2021138},
mrnumber = {4347305},
language = {en},
url = {https://www.numdam.org/articles/10.1051/ro/2021138/}
}
TY - JOUR AU - Esmailnezhad, Bahman AU - Saidi-mehrabad, Mohammad TI - Making an integrated decision in a three-stage supply chain along with cellular manufacturing under uncertain environments: A queueing-based analysis JO - RAIRO. Operations Research PY - 2021 SP - 3575 EP - 3602 VL - 55 IS - 6 PB - EDP-Sciences UR - https://www.numdam.org/articles/10.1051/ro/2021138/ DO - 10.1051/ro/2021138 LA - en ID - RO_2021__55_6_3575_0 ER -
%0 Journal Article %A Esmailnezhad, Bahman %A Saidi-mehrabad, Mohammad %T Making an integrated decision in a three-stage supply chain along with cellular manufacturing under uncertain environments: A queueing-based analysis %J RAIRO. Operations Research %D 2021 %P 3575-3602 %V 55 %N 6 %I EDP-Sciences %U https://www.numdam.org/articles/10.1051/ro/2021138/ %R 10.1051/ro/2021138 %G en %F RO_2021__55_6_3575_0
Esmailnezhad, Bahman; Saidi-mehrabad, Mohammad. Making an integrated decision in a three-stage supply chain along with cellular manufacturing under uncertain environments: A queueing-based analysis. RAIRO. Operations Research, Tome 55 (2021) no. 6, pp. 3575-3602. doi: 10.1051/ro/2021138
[1] and , Revised multi-choice goal programming for incorporated dynamic virtual cellular manufacturing into supply chain management: a case study. Eng. App. Artif. Intell. 47 (2016) 3–15. | DOI
[2] and , A robust optimization model for cellular manufacturing system into supply chain management. Int. J. Prod. Econ. 183 (2017) 667–679. | DOI
[3] , , and , A novel approach to determine cell formation, intracellular machine layout and cell layout in the CMS problem based on TOPSIS method. Comput. Oper. Res. 36 (2009) 1478–1496. | Zbl | DOI
[4] , and , Integrating cell formation with cellular layout and operations scheduling. Int. J. Adv. Manuf. Technol. 61 (2012) 637–647. | DOI
[5] , and , Multi-objective genetic algorithm for cell formation problem considering cellular layout and operations scheduling. Int. J. Comput. Integr. Manuf. 25 (2012) 625–635. | DOI
[6] , An investigation of part family/machine group formation in designing a cellular manufacturing system. Ph.D. thesis. University of Wisconsin (1985).
[7] , and , NP-completeness of cell formation problem with grouping efficacy objective. Int. J. Prod. Res. 58 (2020) 6159–6169. | DOI
[8] , and , Multi-plant cellular manufacturing design within a supply chain. J. Oper. Logistics 4 (2011) II.1–II.17.
[9] and , A new branch&bound-enhanced genetic algorithm for the manufacturing cell formation problem. Comput. Oper. Res. 33 (2006) 2219–2245. | Zbl | DOI
[10] , and , Application of decision-making techniques in supplier selection: a systematic review of literature. Expert Syst. App. 40 (2013) 3872–3885. | DOI
[11] and , Supply chain management: strategy, planning & operation. In: Das summa summarum des management. Springer (2007) 265–275. | DOI
[12] , and , Supply chain management: an analytical framework for critical literature review. Eur. J. Purchasing Supply Manage. 6 (2000) 67–83. | DOI
[13] , and , A flexible job shop cell scheduling with sequence-dependent family setup times and intercellular transportation times using conic scalarization method. Int. Trans. Oper. Res. 26 (2019) 2410–2431. | MR | DOI
[14] , , and , Group scheduling in a cellular manufacturing shop to minimise total tardiness and nT: a comparative genetic algorithm and mathematical modelling approach. Int. J. Serv. Oper. Manage. 24 (2016) 125–146.
[15] , , and , Cell formation and scheduling of part families for reconfigurable cellular manufacturing systems using Tabu search. Simulation 89 (2013) 1056–1072. | DOI
[16] , and , Proposal of a nonlinear multi-objective genetic algorithm using conic scalarization to the design of cellular manufacturing systems. Flexible Serv. Manuf. J. 27 (2015) 30–57. | DOI
[17] , Mixed integer linear programming model for integrating cell formation, group layout and group scheduling. In: 2015 IEEE International Conference on Industrial Technology (ICIT) (2015) 2403–2408. | DOI
[18] , , and , A review of supplier selection methods in manufacturing industries. Suranaree. J. Sci. Technol. 15 (2008) 201–208.
[19] , and , A three-layer chromosome genetic algorithm for multi-cell scheduling with flexible routes and machine sharing. Int. J. Prod. Econ. 196 (2018) 269–283. | DOI
[20] and , Fundamentals of Queueing Theory. John Wiley and Sons Inc, New York (2008). | Zbl | MR | DOI
[21] and , Concurrent scheduling of manufacturing cells considering sequence-dependent family setup times and intercellular transportation times. Int. J. Adv. Manuf. Technol. 77 (2015) 1907–1915. | DOI
[22] , and , An international supplier selection model with inventory and transportation management decisions. Flexible Serv. Manuf. J. 24 (2012) 4–27. | DOI
[23] and , A heuristic approach for machine cell formation problems with alternative routings. Proc. Comput. Sci. 89 (2016) 228–242. | DOI
[24] , Group technology and cellular manufacturing. IEEE Trans. Syst. Man Cybern. 24 (1994) 203–215. | DOI
[25] , and , Multi-criteria decision making approaches for supplier evaluation and selection: a literature review. Eur. J. Oper. Res. 202 (2010) 16–24. | Zbl | DOI
[26] , and , What is required for greener supplier selection? A literature review and conceptual model development. J. Purchasing Supply Manage. 19 (2013) 247–263. | DOI
[27] , Handbook of Cellular Manufacturing Systems. John Wiley & Sons (1999). | DOI
[28] , and , Fast genetic algorithm approaches to solving discrete-time mixed integer linear programming problems of capacity planning and scheduling of biopharmaceutical manufacture. Comput. Chem. Eng. 121 (2019) 212–223. | DOI
[29] , and , Planning, Design, and Analysis of Cellular Manufacturing Systems. Newnes 24 (1995).
[30] and , Job scheduling in virtual manufacturing cells with lot-streaming strategy: a new mathematical model formulation and a genetic algorithm approach. J. Oper. Res. Soc. 63 (2012) 683–695. | DOI
[31] and , Machine-component group formation in group technology: review and extension. Int. J. Prod. Res. 20 (1982) 117–133. | DOI
[32] and , Modified SA algorithm for bi-objective robust stochastic cellular facility layout in cellular manufacturing systems. In: Advanced Computing and Communication Technologies. Springer (2019) 19–33. | DOI
[33] and , Makespan optimization in a no-wait flowline manufacturing cell with sequence-dependent family setup times. Comput. Ind. Eng. 128 (2019) 1–7. | DOI
[34] and , Cell formation and task scheduling considering multi-functional resource and part movement using hybrid simulated annealing. Int. J. Comput. Intell. Syst. 9 (2016) 765–777. | DOI
[35] , , and , Solving cell formation and task scheduling in cellular manufacturing system by discrete bacteria foraging algorithm. Int. J. Prod. Res. 54 (2016) 923–944. | DOI
[36] , and , Integrated bacteria foraging algorithm for cellular manufacturing in supply chain considering facility transfer and production planning. Appl. Soft Comput. 62 (2018) 602–618. | DOI
[37] , and , Control problems and management policies in health systems: application to intensive care units. Flexible Serv. Manuf. J. 28 (2016) 62–89. | DOI
[38] , and , Supplier selection criteria and methods in supply chains: a review. Int. J. Soc. Manage. Econ. Bus. Eng. 7 (2013) 1403–1409.
[39] , Scheduling in cellular manufacturing systems. Iberoam. J. Ind. Eng. 4 (2012) 231–243.
[40] and , Revised multi-choice goal programming for integrated supply chain design and dynamic virtual cell formation with fuzzy parameters. Int. J. Comput. Integr. Manuf. 28 (2015) 251–265. | DOI
[41] and , A hybrid genetic algorithm for dynamic virtual cellular manufacturing with supplier selection. Int. J. Adv. Manuf. Technol. 92 (2017) 3001–3017. | DOI
[42] , and , A robust optimisation model for generalised cell formation problem considering machine layout and supplier selection. Int. J. Comput. Integr. Manuf. 27 (2014) 772–786. | DOI
[43] , and , Efficient implementation of the genetic algorithm to solve rich vehicle routing problems. Oper. Res. 21 (2021) 1763–1791.
[44] , and , Scheduling with sequencing flexibility. Decis. Sci. 24 (1993) 315–342. | DOI
[45] , , and , A novel hybrid SA/GA algorithm for solving an integrated cell formation–job scheduling problem with sequence-dependent set-up times. Int. J. Manage. Sci. Eng. Manage. 11 (2016) 134–142.
[46] and , Integration of multi-product supply chain network design and assembly line balancing. Oper. Res. 21 (2021) 453–483.
[47] and , Impact of cellular manufacturing on supply chain management: exploration of interrelationships between design issues. Int. J. Manuf. Technol. Manage. 5 (2003) 507–520. | DOI
[48] , , and , Cellular manufacturing design and replenishment strategy in a capacitated supply chain system: a simulation-based analysis. Comput. Ind. Eng. 141 (2020) 106282. | DOI
[49] and , Scheduling optimization cell formation problem for cellular manufacturing system using meta-heuristic methods. Appl. Mech. Mater. 786 (2015) 340–344. | DOI
[50] and , An integrated model of dynamic cellular manufacturing and supply chain system design. Int. J. Adv. Manuf. Technol. 62 (2012) 385–404. | DOI
[51] , Incorporating cellular manufacturing into supply chain design. Int. J. Prod. Res. 46 (2008) 4925–4945. | Zbl | DOI
[52] and , A multi-stage stochastic programming approach in a dynamic cell formation problem with uncertain demand: a case study. Int. J. Supply Oper. Manage. 6 (2019) 67–87.
[53] , and , Managing the Supply Chain: Definitive Guide. Tata McGraw-Hill Education (2004).
[54] and , A tabu search approach for cell scheduling problem with makespan criterion. Int. J. Prod. Econ. 141 (2013) 639–645. | DOI
[55] and , Incorporating dynamic cellular manufacturing into strategic supply chain design. Int. J. Adv. Manuf. Technol. 95 (2018) 2429–2447. | DOI
[56] , , and , Supply chain scheduling in a collaborative manufacturing mode: model construction and algorithm design. Ann. Oper. Res. 275 (2019) 685–714. | MR | Zbl | DOI
[57] , , and , Scheduling problem of virtual cellular manufacturing systems (VCMS); Using simulated annealing and genetic algorithm based heuristics. J. Mod. Processes Manuf. Prod. 3 (2014) 45–60.
[58] , and , Uncertainty factors in real manufacturing environment. Aust. J. Basic Appl. Sci. 3 (2009) 342–351.
[59] and , Research issues in cellular manufacturing. Int. J. Prod. Res. 25 (1987) 413–431. | DOI
[60] and , Cellular manufacturing in the US industry: a survey of users. Int. J. Prod. Res. 27 (1989) 1511–1530. | DOI
[61] , , and , Genetic algorithms for integrating cell formation with machine layout and scheduling. Comput. Ind. Eng. 53 (2007) 277–289. | DOI
[62] and , Integrated optimization of dynamic cell formation and hierarchical production planning problems. Comput. Ind. Eng. 139 (2020) 106155. | DOI
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Supplementary Material is only available in electronic form at https://www.rairo-ro.org/10.1051/ro/2021138/olm.
