In this paper, to integrate the decisions of parts scheduling, Material Requirement Planning (MRP), Production Planning (PP) and Transportation Planning (TP) for designing a Cellular Manufacturing System (CMS) under a dynamic environment, a Mixed-Integer Nonlinear Programming (MINLP) mathematical model is formulated. The proposed mathematical model integrates extensive coverage of significant manufacturing characteristics in designing a CMS to be implemented in a three-layer supply chain. The considered features include markets demands, heterogeneous vehicles, raw materials requirements planning, parts due dates, cell size limits, machines capacity, intra/inter cell material handling time/cost, transportation time/cost, operation time, alternative processing routes in addition to the main decisions of parts scheduling, PP, TP and dynamic cell formation. Also, some novel characteristics are incorporated based on a three-layer supply chain that make the presented model remarkable respect to the literature including (1) In the first layer, planning the orders of raw materials with different lead times and usage coefficients is performed, (2) In the second layer, decisions of dynamic cell formation and parts scheduling are made, and (3) In the third layer, optimal vehicles are selected as a generalized fixed-charge TP based on transportation time and cost to satisfy multi-markets with different demand volumes. The components in the objective function to be minimized include total costs of holding the parts inventories in the markets, backorders, tardiness, transportation of the parts from the plant to the markets, purchase of raw materials, keeping raw materials in the plant warehouse, intercellular/intracellular movements and machine relocation. An illustrative numerical example is solved by the CPLEX solver to illustrate the achievements obtained by the incorporated characteristics in the integrated model. Furthermore, a sensitivity analysis is performed to assess the effects of important parameters on the model performance. Since the proposed model is NP-hard, a Simulated Annealing (SA) algorithm is improved by an elaborately-designed matrix-based chromosome representation is applied to represent all decision variables, as well as a sequential procedure generating initial solutions. Several test problems either generated randomly or taken from the literature with various sizes are solved and the results are compared with the solutions gained using CPLEX solver. The comparisons results show that the designed SA is capable of evolving optimal or near-optimal solutions with reasonable relative gaps in a computationally satisfactory manner.
Keywords: Dynamic cellular manufacturing system, three-layer supply chain, scheduling, production planning, transportation planning
@article{RO_2021__55_S1_S1875_0,
author = {Shafiee-Gol, Shima and Kia, Reza and Tavakkoli-Moghaddam, Reza and Kazemi, Mohammad and Kamran, Mehdi A.},
title = {Integration of parts scheduling, {MRP,} production planning and generalized fixed-charge transportation planning in the design of a dynamic cellular manufacturing system},
journal = {RAIRO. Operations Research},
pages = {S1875--S1912},
year = {2021},
publisher = {EDP-Sciences},
volume = {55},
doi = {10.1051/ro/2020062},
mrnumber = {4223079},
language = {en},
url = {https://www.numdam.org/articles/10.1051/ro/2020062/}
}
TY - JOUR AU - Shafiee-Gol, Shima AU - Kia, Reza AU - Tavakkoli-Moghaddam, Reza AU - Kazemi, Mohammad AU - Kamran, Mehdi A. TI - Integration of parts scheduling, MRP, production planning and generalized fixed-charge transportation planning in the design of a dynamic cellular manufacturing system JO - RAIRO. Operations Research PY - 2021 SP - S1875 EP - S1912 VL - 55 PB - EDP-Sciences UR - https://www.numdam.org/articles/10.1051/ro/2020062/ DO - 10.1051/ro/2020062 LA - en ID - RO_2021__55_S1_S1875_0 ER -
%0 Journal Article %A Shafiee-Gol, Shima %A Kia, Reza %A Tavakkoli-Moghaddam, Reza %A Kazemi, Mohammad %A Kamran, Mehdi A. %T Integration of parts scheduling, MRP, production planning and generalized fixed-charge transportation planning in the design of a dynamic cellular manufacturing system %J RAIRO. Operations Research %D 2021 %P S1875-S1912 %V 55 %I EDP-Sciences %U https://www.numdam.org/articles/10.1051/ro/2020062/ %R 10.1051/ro/2020062 %G en %F RO_2021__55_S1_S1875_0
Shafiee-Gol, Shima; Kia, Reza; Tavakkoli-Moghaddam, Reza; Kazemi, Mohammad; Kamran, Mehdi A. Integration of parts scheduling, MRP, production planning and generalized fixed-charge transportation planning in the design of a dynamic cellular manufacturing system. RAIRO. Operations Research, Tome 55 (2021), pp. S1875-S1912. doi: 10.1051/ro/2020062
[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 dynamic non-linear mixed integer-programming model for the CMS design with production planning. Int. J. Ind. Syst. Eng. 16 (2014) 70–87.
[3] , and , Integrated cellular manufacturing systems design with production planning and dynamic system reconfiguration. Eur. J. Oper. Res. 192 (2009) 414–428. | MR | Zbl | DOI
[4] and , Sequencing a batching flexible cell to minimise set-up costs. Int. J. Prod. Res. 52 (2014) 2461–2476. | DOI
[5] , Cellular manufacturing system design considering machines reliability and parts alternative process routings. Int. J. Prod. Res. 54 (2016) 846–863. | DOI
[6] , and , Integrating cell formation with cellular layout and operations scheduling. Int. J. Adv. Manuf. Technol. 61 (2012) 637–647. | DOI
[7] , , , and , Unique NSGA-II and MOPSO algorithms for improved dynamic cellular manufacturing systems considering human factors. Appl. Math. Model. 48 (2017) 655–672. | MR | DOI
[8] and , A comprehensive mathematical model for dynamic cellular manufacturing system design and Linear Programming embedded hybrid solution techniques. Comput. Ind. Eng. 91 (2016) 10–29. | DOI
[9] , Production flow analysis. Prod. Eng. 50 (1971) 139–152. | DOI
[10] and , Experimental Designs, 2nd edtion. John Wiley & Sons, New York, NY (1992). | MR | Zbl
[11] and , Design of robust cellular manufacturing system for dynamic part population considering multiple processing routes using genetic algorithm. J. Manuf. Syst. 35 (2015) 155–163. | DOI
[12] and , A mathematical model and a parallel multiple search path simulated annealing for an integrated distributed layout design and machine cell formation. J. Manuf. Syst. 43 (2017) 195–212. | DOI
[13] and , 2016. A multi-layer perceptron for scheduling cellular manufacturing systems in the presence of unreliable machines and uncertain cost. Appl. Soft Comput. 49 (2016) 27–55. | DOI
[14] , , and , A multi-period scheduling of dynamic cellular manufacturing systems in the presence of cost uncertainty. Comput. Ind. Eng. 100 (2016) 110–132. | DOI
[15] , and , Simulation-based performance comparison between dynamic cells, classical cells and job shops: a case study. Int. J. Prod. Res. 46 (2008) 509–536. | Zbl | DOI
[16] , and , Solving a mathematical model integrating unequal-area facilities layout and part scheduling in a cellular manufacturing system by a genetic algorithm. SpringerPlus 5 (2016) 1254. | DOI
[17] , , and , Concurrent cell formation and layout design based on hybrid approaches. Appl. Soft Comput. 66 (2018) 346–359. | DOI
[18] , A new stochastic mixed integer programming to design integrated cellular manufacturing system: a supply chain framework. Int. J. Ind. Eng. Comput. 2 (2011) 563–574.
[19] , Designing integrated cellular manufacturing systems with tactical decisions. J. Chin. Inst. Eng. 38 (2015) 332–341. | DOI
[20] , and , Integrating strategic and tactical decisions to robust designing of cellular manufacturing under uncertainty: fixed suppliers in supply chain. Int. J. Comput. Intel. Syst. 4 (2011) 837–854.
[21] , and , Applying soft-computing techniques in solving dynamic multi-objective layout problems in cellular manufacturing system. Int. J. Adv. Manuf. Technol. 86 (2016) 237–257. | DOI
[22] 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
[23] , Group technology and cellular manufacturing. IEEE Trans. Syst. Man Cybern. 24 (1994) 203–214. | DOI
[24] and , Energy-efficient cellular manufacturing system: eco-friendly revamping of machine shop configuration. Energy 163 (2018) 863–872. | DOI
[25] , , , and , A comprehensive mathematical model for the design of a dynamic cellular manufacturing system integrated with production planning and several manufacturing attributes. Int. J. Ind. Eng. Prod. Res. 22 (2011) 199–212.
[26] , , , , and , Solving a group layout design model of a dynamic cellular manufacturing system with alternative process routings, lot splitting and flexible reconfiguration by simulated annealing. Comput. Oper. Res. 39 (2012) 2642–2658. | MR | Zbl | DOI
[27] , , and , A simulated annealing for intra-cellularlayout design of dynamic cellular manufacturing systems with route selection, purchasing machines and cell reconfiguration. Asia-Pac. J. Oper. Res. 30 (2013) 1350004. | MR | Zbl | DOI
[28] , and , A simulated annealing algorithm to determine a group layout and production plan in a dynamic cellular manufacturing system. J. Optim. Ind. Eng. 14 (2014) 37–52.
[29] , , , and , A mathematical model for assessing the effects of a lot splitting feature on a dynamic cellular manufacturing system. Prod. Eng. 11 (2017) 557–573. | DOI
[30] , and , Optimization by simulated annealing. Science 220 (1983) 671–680. | MR | Zbl | DOI
[31] , and , Production planning in virtual cell of reconfiguration manufacturing system using genetic algorithm. Int. J. Adv. Manuf. Technol. 74 (2014) 47–64. | DOI
[32] , and , Solving the multi-objective flowline manufacturing cell scheduling problem by hybrid harmony search. Expert Syst. App. 42 (2015) 1409–1417. | DOI
[33] 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
[34] , and , Worker assignment and production planning with learning and forgetting in manufacturing cells by hybrid bacteria foraging algorithm. Comput. Ind. Eng. 96 (2016) 162–179. | DOI
[35] , 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
[36] and , An integrated model of dynamic cellular manufacturing and supply chain system design. Int. J. Adv. Manuf. Technol. 62 (2012) 385–404. | DOI
[37] and , An integrated mathematical model for solving dynamic cell formation problem considering operator assignment and inter/intra cell layouts. Appl. Soft Comput. 42 (2016) 325–341. | DOI
[38] , The Scientific Principles of Group Technology. National Lending Library Translation, Boston, MA (1966).
[39] and , Designing cellular manufacturing systems considering S-shaped layout. Comput. Ind. Eng. 98 (2016) 221–236. | DOI
[40] , , and , Solving a fuzzy fixed charge solid transportation problem by metaheuristics. Math. Comput. Model. 57 (2013) 1543–1558. | MR | DOI
[41] , Design and Analysis of Experiments. John Wiley & Sons, New York, NY (2017). | MR | Zbl
[42] , , and , A bi-objective model in sustainable dynamic cell formation problem with skill-based worker assignment. J. Manuf. Syst. 38 (2016) 46–62. | DOI
[43] , Evolution of operations planning and control: from production to supply chains. Int. J. Prod. Res. 51 (2013) 6836–6843. | DOI
[44] , and , CMS scheduling problem considering material handling and routing flexibility. Int. J. Adv. Manuf. Technol. 72 (2014) 881–893. | DOI
[45] 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
[46] , 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
[47] , , and , A numerical comparison between simulated annealing and evolutionary approaches to the cell formation problem. Expert Syst. App. 37 (2010) 5476–5483. | DOI
[48] , , and , A new approach towards integrated cell formation and inventory lot sizing in an unreliable cellular manufacturing system. Appl. Math. Modell. 35 (2011) 1810–1819. | MR | Zbl | DOI
[49] 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
[50] , and , Solving a new robust green cellular manufacturing problem with environmental issues under uncertainty using Benders decomposition. Eng. Optim. 51 (2019) 1229–1250. | MR | Zbl | DOI
[51] , , 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.
[52] and , Design and reconfiguration models for dynamic cellular manufacturing to handle market changes. Int. J. Comput. Integr. Manuf. 28 (2015) 170–186. | DOI
[53] , and , Physically reconfigurable virtual cells: a dynamic model for a highly dynamic environment. Comput. Ind. Eng. 29 (1995) 221–225. | DOI
[54] , and , Solving the flowshop scheduling problem with sequence dependent setup times using advanced metaheuristics. Eur. J. Oper. Res. 165 (2005) 34–54. | MR | Zbl | DOI
[55] , , and , A robust optimization approach for an integrated dynamic cellular manufacturing system and production planning with unreliable machines. Appl. Math. Modell. 40 (2016) 169–191. | MR | Zbl | DOI
[56] , and , A linear programming embedded simulated annealing in the design of distributed layout with production planning and systems reconfiguration. Int. J. Adv. Manuf. Technol. 88 (2017) 1119–1140. | DOI
[57] , Introduction to quality engineering: designing quality into products and processes. White Plains: Asian Productivity Organisation/UNIPUB, Tokyo (1986).
[58] , , and , Optimization of parts scheduling in multiple cells considering intercell move using scatter search approach. J. Intell. Manuf. 21 (2010) 525–537. | DOI
[59] , , and , Using Lagrangian relaxation decomposition with heuristic to integrate the decisions of cell formation and parts scheduling considering intercell moves. IEEE Trans. Autom. Sci. Eng. 11 (2014) 1110–1121. | DOI
[60] and , Procedures for the part family/machine group identification problem in cellular manufacturing. J. Oper. Manage. 6 (1986) 125–147. | DOI
[61] and , Cellular Manufacturing in the US industry: a survey of users. Int. J. Prod. Res. 27 (1989) 1511–1530. | DOI
[62] , , and , Genetic algorithms for integrating cell formation with machine layout and scheduling. Comput. Ind. Eng. 53 (2007) 277–289. | DOI
[63] , and , A hybrid simulated annealing for scheduling in dual-resource cellular manufacturing system considering worker movement. Automatika 60 (2019) 172–180. | DOI
[64] , , , , , and , Hybridization of simulated annealing with genetic algorithm for cell formation problem. Int. J. Adv. Manuf. Technol. 86 (2016) 2243–2254. | DOI
Cité par Sources :
