[1] J Gao, L Sun, M Gen. A hybrid genetic and variable neighborhood descent algorithm for flexible job shop scheduling problems. Computers & Operations Research, 35, 2892-2907(2008).

[2] [2] Altom R J. Costs savings of group technology, Research Rept[R]. Dearbn: Society of Manufacturing Engineers, 1978.

[3] Nomden, J Slomp, N C Suresh. Virtual manufacturing cells: A taxonomy of past research and identification of future research issues.. International Journal of Flexible Manufacturing Systems, 17, 71-92(2006).

[4] S M Ratchev. Concurrent process and facility prototyping for formation of virtual manufacturing cells. Integrated Manufacturing Systems, 12, 306-315(2001).

[5] N Safaei, M Saidi-Mehrabad, M S Jabal-Ameli. A hybrid simulated annealing for solving an extended model of dynamic cellular manufacturing system. European Journal of Operational Research, 185, 563-592(2008).

[6] K Deep, P K Singh. Dynamic cellular manufacturing system design considering alternative routing and part operation tradeoff using simulated annealing based genetic algorithm. Sādhanā, 41, 1063-1079(2016).

[7] Nomden Gert, der Zee Durk-Joukevan. Virtual cellular manufacturing: configuring routing flexibility. International Journal of Production Economics, 112, 439-451(2008).

[8] S E Kesen, S K Das, Z Güngör. A genetic algorithm based heuristic for scheduling of virtual manufacturing cells (VMCs). Computers & Operations Research, 37, 1148-1156(2010).

[9] Gorkemli, Latife, Baykasoglu, et al. Dynamic virtual cellular manufacturing through agent-based modelling. International Journal of Computer Integrated Manufacturing, 30, 564-579(2017).

[10] A Delgoshaei, Ariffin M K A, C Gomes, et al. A multi-period scheduling of dynamic cellular manufacturing systems in the presence of cost uncertainty. Computers & Industrial Engineering, 100, 110-132(2016).

[11] A Azadeh, S Elahi, M H Farahani, et al. A genetic algorithm-taguchi based approach to inventory routing problem of a single perishable product with transshipment. Computers & Industrial Engineering, 104, 124-133(2017).

[12] H Bayram, R Sahin. A comprehensive mathematical model for dynamic cellular manufacturing system design and linear programming embedded hybrid solution techniques. Computers & Industrial Engineering, 91, 10-29(2016).

[13] J Hu, X Gu, W Gu. Robust optimization approach for short-term scheduling of batch plants under demand uncertainty. Kybernetes, 40, 860-870(2011).

[14] A Aksoy, N Öztürk. Simulated annealing approach in scheduling of virtual cellular manufacturing in the automotive industry. International Journal of Vehicle Design, 52, 82-95(2010).

[15] M Sakhaii, R Tavakkoli-Moghaddam, M Bagheri, et al. A robust optimization approach for an integrated dynamic cellular manufacturing system and production planning with unreliable machines. Applied Mathematical Modelling, 40, 1-13(2015).

[16] [16] Jiang Y, Zhou P, Zhan R, et al. An artificial bee colony with selfadaptive operats alterable search depth approach f intercell scheduling [C]2016 IEEE Congress on Evolutionary Computation (CEC), 2016: 112–119.

[17] J Tang, X Wang, I Kaku, et al. Optimization of parts scheduling in multiple cells considering intercell move using scatter search approach. Journal of Intelligent Manufacturing, 21, 525-537(2010).

[18] [18] Di Tong. Study on virtual cellular dynamic fmation scheduling with new task ion [D]. Zhenjiang: Jiangsu University of Science Technology, 2015. (in Chinese)

[19] [19] Xu Y. Research on manufacturing cell reconfiguration technology of discrete production line[D]. Guiyang: Guizhou University, 2019. (in Chinese)