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Volume 6 Issue 4
Jul.  2019

IEEE/CAA Journal of Automatica Sinica

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Article Contents
Kaizhou Gao, Zhiguang Cao, Le Zhang, Zhenghua Chen, Yuyan Han and Quanke Pan, "A Review on Swarm Intelligence and Evolutionary Algorithms for Solving Flexible Job Shop Scheduling Problems," IEEE/CAA J. Autom. Sinica, vol. 6, no. 4, pp. 904-916, July 2019. doi: 10.1109/JAS.2019.1911540
Citation: Kaizhou Gao, Zhiguang Cao, Le Zhang, Zhenghua Chen, Yuyan Han and Quanke Pan, "A Review on Swarm Intelligence and Evolutionary Algorithms for Solving Flexible Job Shop Scheduling Problems," IEEE/CAA J. Autom. Sinica, vol. 6, no. 4, pp. 904-916, July 2019. doi: 10.1109/JAS.2019.1911540

A Review on Swarm Intelligence and Evolutionary Algorithms for Solving Flexible Job Shop Scheduling Problems

doi: 10.1109/JAS.2019.1911540
Funds:  This work was supported in part by the National Natural Science Foundation of China (61603169, 61773192, 61803192), in part by the funding from Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology and in part by Singapore National Research Foundation (NRF-RSS2016-004)
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  • Flexible job shop scheduling problems (FJSP) have received much attention from academia and industry for many years. Due to their exponential complexity, swarm intelligence (SI) and evolutionary algorithms (EA) are developed, employed and improved for solving them. More than 60% of the publications are related to SI and EA. This paper intents to give a comprehensive literature review of SI and EA for solving FJSP. First, the mathematical model of FJSP is presented and the constraints in applications are summarized. Then, the encoding and decoding strategies for connecting the problem and algorithms are reviewed. The strategies for initializing algorithms? population and local search operators for improving convergence performance are summarized. Next, one classical hybrid genetic algorithm (GA) and one newest imperialist competitive algorithm (ICA) with variables neighborhood search (VNS) for solving FJSP are presented. Finally, we summarize, discus and analyze the status of SI and EA for solving FJSP and give insight into future research directions.

     

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  • [1]
    M. R. Garey, D. S. Johnson, and R. Sethi, " The complexity of flow shop and job shop scheduling,” Math. Oper. Res., vol. 1, no. 2, pp. 117–129, 1976. doi: 10.1287/moor.1.2.117
    [2]
    P. Brucker, R. Schlie, " Job-shop scheduling with multi-purpose machines,” Computing, vol. 45, no. 4, pp. 369–375, 1990. doi: 10.1007/BF02238804
    [3]
    A.S. Jain, S. Meeran, " Deterministic job-shop scheduling: past, present and future,” Eur. J. Oper. Res., vol. 113, no. 2, pp. 390–434, 1998.
    [4]
    I. Kacem, S. Hammadi, P. Borne, " Approach by localization and multi-objective evolutionary optimization for flexible job shop scheduling problems,” IEEE Trans. Syst.,Man,Cybern, vol. 32, no. 1, pp. 1–13, Jan. 2002. doi: 10.1109/TSMCC.2002.1009117
    [5]
    A. Bagheri, M. Zandieh, I. Mahdavi, and M. Yazdani, " An artificial immune algorithm for the flexible job-shop scheduling problem,” Future Gener. Comput. Syst., vol. 26, no. 4, pp. 533–541, 2010. doi: 10.1016/j.future.2009.10.004
    [6]
    F. Pezzella, G. Morganti, G. Ciaschetti, " A genetic algorithm for the Flexible Job-shop Scheduling Problem,” Comput. Oper. Res., vol. 35, no. 10, pp. 3202–3212, 2008. doi: 10.1016/j.cor.2007.02.014
    [7]
    J. Gao, L. Y. Sun, M. Gen, " A hybrid genetic and variable neighborhood descent algorithm for flexible job shop scheduling problems,” Comput. Oper. Res., vol. 35, no. 9, pp. 2892–2907, 2008. doi: 10.1016/j.cor.2007.01.001
    [8]
    G. H. Zhang, L. Gao, Y. Shi, " An effective genetic algorithm for the flexible job-shop scheduling problem,” Expert Syst. Appl., vol. 38, no. 4, pp. 3563–3573, 2011. doi: 10.1016/j.eswa.2010.08.145
    [9]
    M. T. Jensen, " Generating robust and flexible job shop schedules using genetic algorithms,” IEEE Trans. Evolut. Comput., vol. 7, no. 3, pp. 275–288, 2003. doi: 10.1109/TEVC.2003.810067
    [10]
    J. Gao, M. Gen, L. Y. Sun, X. H. Zhao, " A hybrid of genetic algorithm and bottleneck shifting for multiobjective flexible job shop scheduling problems,” Comput. Ind. Eng., vol. 53, no. 1, pp. 149–162, 2007. doi: 10.1016/j.cie.2007.04.010
    [11]
    J. Gao, M. Gen, L.Y. Sun, " Scheduling jobs and maintenances in flexible job shop with a hybrid genetic algorithm,” J. Intel. Manuf., vol. 17, no. 4, pp. 493–507, 2006. doi: 10.1007/s10845-005-0021-x
    [12]
    G. L. De, F. Pezzella, " An improved genetic algorithm for the distributed and flexible job-shop scheduling problem,” Euro. J. Oper. Res, vol. 200, no. 2, pp. 95–408, 2010.
    [13]
    X.B. Huang, L.X. Yang, " A hybrid genetic algorithm for multi-objective flexible job shop scheduling problem considering transportation time,” Int. J Intell. Comput. Cyber., vol. 12, no. 2, pp. 154–174, 2019. doi: 10.1108/IJICC-10-2018-0136
    [14]
    N. Al-Hinai, T. Y. ElMekkawy, " Robust and stable flexible job shop scheduling with random machine breakdowns using a hybrid genetic algorithm,” Int. J. Prod. Res., vol. 132, no. 2, pp. 279–291, 2011. doi: 10.1016/j.ijpe.2011.04.020
    [15]
    D. M. Lei, " A genetic algorithm for flexible job shop scheduling with fuzzy processing time,” Int. J. Prod. Res., vol. 48, no. 10, pp. 2995–3013, 2010. doi: 10.1080/00207540902814348
    [16]
    L. Sun, L. Lin, M.S. Gen, H.J. Li, " A hybrid cooperative coevolution algorithm for fuzzy flexible job shop scheduling,” IEEE Trans. Fuzzy Syst., vol. 27, no. 5, pp. 1008–1022, 2019. doi: 10.1109/TFUZZ.91
    [17]
    J. C. Chen, C. C. Wu, C. W. Chen, K. H. Chen, " Flexible job shop scheduling with parallel machines using genetic algorithm and grouping genetic algorithm,” Expert Syst. Appl., vol. 39, no. 11, pp. 10016–10021, 2012. doi: 10.1016/j.eswa.2012.01.211
    [18]
    M. Gholami, M. Zandieh, " Integrating simulation and genetic algorithm to schedule a dynamic flexible job shop,” J. Intel. Manuf., vol. 20, no. 4, pp. 481–498, 2009. doi: 10.1007/s10845-008-0150-0
    [19]
    A. Corominas, A. Garcia-Villoria, N.A. Gonzalez, R. Pastor, " A multistage graph-based procedure for solving a just-in-time flexible job shop scheduling problem with machine and time-dependent processing cost,” J. Oper. Res. Soc., vol. 70, no. 4, pp. 620–633, 2019. doi: 10.1080/01605682.2018.1452537
    [20]
    D. M. Lei, " Co-evolutionary genetic algorithm for fuzzy flexible job shop scheduling,” Appl. Soft Comput., vol. 12, no. 8, pp. 2237–2245, 2012. doi: 10.1016/j.asoc.2012.03.025
    [21]
    F. M. Defersha, M. Y. Chen, " A parallel genetic algorithm for a flexible job-shop scheduling problem with sequence dependent setups,” Int. J. Adv. Manuf. Tech., vol. 49, no. 1-4, pp. 263–279, 2010. doi: 10.1007/s00170-009-2388-x
    [22]
    Y. Demir, S.K. Isleyen, " An effective genetic algorithm for flexible job-shop scheduling with overlapping in operations,” Int. J. Prod. Res., vol. 52, no. 13, pp. 3905–3921, 2014. doi: 10.1080/00207543.2014.889328
    [23]
    C. Gutierrez, I. Garcia-Magarino, " Modular design of a hybrid genetic algorithm for a flexible job-shop scheduling problem,” Knowl-Based Syst., vol. 24, no. 1, pp. 102–112, 2011. doi: 10.1016/j.knosys.2010.07.010
    [24]
    N. Al-Hinai, T.Y. ElMekkawy, " An efficient hybridized genetic algorithm architecture for the flexible job shop scheduling problem,” Flex. Serv. Manuf. J., vol. 23, no. 1, pp. 64–85, 2011. doi: 10.1007/s10696-010-9067-y
    [25]
    I. Driss, K.N. Mouss, A. Laggoun, " A new genetic algorithm for flexible job-shop scheduling problems,” J. Mech. Sci. Tech., vol. 29, no. 3, pp. 1273–1281, 2015. doi: 10.1007/s12206-015-0242-7
    [26]
    H. C. Chang, Y. P. Chen, T. K. Liu, J. H. Chou, " Solving the flexible job shop scheduling problem with Makespan optimization by using a hybrid taguchi-genetic algorithm,” IEEE Access, vol. 3, pp. 1740–1754, 2015. doi: 10.1109/ACCESS.2015.2481463
    [27]
    S. Ishikawa, R. Kubota, K. Horio, " Effective hierarchical optimization by a hierarchical multi-space competitive genetic algorithm for the flexible job-shop scheduling problem,” Expert Syst. Appl., vol. 42, no. 24, pp. 9434–9440, 2015. doi: 10.1016/j.eswa.2015.08.003
    [28]
    A. Jalilvand-Nejad, P. Fattahi, " A mathematical model and genetic algorithm to cyclic flexible job shop scheduling problem,” J. Intel. Manuf., vol. 26, no. 6, pp. 1085–1098, 2015. doi: 10.1007/s10845-013-0841-z
    [29]
    W. Sun, Y. Pan, X.H. Lu, Q.Y. Ma, " Research on flexible job-shop scheduling problem based on a modified genetic algorithm,” J. Mech. Sci. Tech., vol. 24, no. 10, pp. 2119–2125, 2010. doi: 10.1007/s12206-010-0526-x
    [30]
    Y. M. Wang, H. L. Yin, K. D. Qin, " A novel genetic algorithm for flexible job shop scheduling problems with machine disruptions,” Int. J. Adv. Manuf. Tech., vol. 68, no. 5-8, pp. 1317–1326, 2013. doi: 10.1007/s00170-013-4923-z
    [31]
    G. Z. Rey, A. Bekrar, V. Prabhu, D. Trentesaux, " Coupling a genetic algorithm with the distributed arrival-time control for the JIT dynamic scheduling of flexible job-shops,” Int. J. Prod. Res., vol. 52, no. 12, pp. 3688–3709, 2014. doi: 10.1080/00207543.2014.881575
    [32]
    H. Piroozfard, K.Y. Wong, W.P. Wong, " Minimizing total carbon footprint and total late work criterion in flexible job shop scheduling by using an improved multi-objective genetic algorithm,” Resour. Conserv and Recy., vol. 128, pp. 267–283, 2018. doi: 10.1016/j.resconrec.2016.12.001
    [33]
    M. Rohaninejad, A. Kheirkhah, P. Fattahi, B. Vahedi-Nouri, " A hybrid multi-objective genetic algorithm based on the ELECTRE method for a capacitated flexible job shop scheduling problem,” Int. J. Adv. Manuf. Tech., vol. 77, no. 1–4, pp. 51–66, 2015. doi: 10.1007/s00170-014-6415-1
    [34]
    D. Cinar, J. A. Oliveira, Y. I. Topcu, P. M. Pardalos, " A priority-based genetic algorithm for a flexible job shop scheduling problem,” J. Ind. Manag. Optim, vol. 12, no. 4, pp. 1391–1415, 2016. doi: 10.3934/jimo
    [35]
    R. Agrawal, L.N. Pattanaik, S. Kumar, " Scheduling of a flexible job-shop using a multi-objective genetic algorithm,” J. Adv. Manag. Res., vol. 9, no. 2, pp. 178–188, 2012. doi: 10.1108/09727981211271922
    [36]
    K. Ida, K. Oka, " Flexible job-shop scheduling problem by genetic algorithm,” Electr. Eng. Jpn., vol. 177, no. 3, pp. 28–35, 2011. doi: 10.1002/eej.v177.3
    [37]
    Ha. C. Chang, T. K. Liu, " Optimisation of distributed manufacturing flexible job shop scheduling by using hybrid genetic algorithms,” J. Intel. Manuf., vol. 28, no. 8, pp. 1973–1986, 2017. doi: 10.1007/s10845-015-1084-y
    [38]
    W. Zhang, J. B. Wen, Y. C. Zhu, Y. Hu, " Multi-objective scheduling sumulation of flexible job-shop based on multi-population genetic algorithm,” Int. J. Simu. Model., vol. 16, no. 2, pp. 313–321, 2017. doi: 10.2507/IJSIMM
    [39]
    X. J. Wang, L. Gao, C. Y. Zhang, X. Y. Li, " A multi-objective genetic algorithm for fuzzy flexible job-shop scheduling problem,” Int. J. Comput. Appl. Tech., vol. 45, no. 2–3, pp. 115–125, 2012.
    [40]
    P. H. Lu, M. C. Wu, H. Tan, Y. H. Peng, Ch. F. Chen, " A genetic algorithm embedded with a concise chromosome representation for distributed and flexible job-shop scheduling problems,” J. Intel. Manuf., vol. 29, no. 1, pp. 19–34, 2018. doi: 10.1007/s10845-015-1083-z
    [41]
    X. J. Wang, W. F. Li, Y. Zhang, " An improved multi-objective genetic algorithm for fuzzy flexible job-shop scheduling problem,” Int. J. Comput. Appl. Tech., vol. 47, no. 2–3, pp. 280–288, 2013.
    [42]
    P. Kaweegitbundit, T. Eguchi, "Flexible job shop scheduling using genetic algorithm and heuristic rules," J. Adv. Mech. Des. Syst. Manuf., vol. 10, no. 1, JAMDSM0010, 2016.
    [43]
    S. Yokoyama, H. Iizuka, M. Yamamoto, " Priority rule-based construction procedure combined with genetic algorithm for flexible job-shop scheduling problem,” J. Adv. Comput. Intel. Inform., vol. 19, no. 6, pp. 892–899, 2015. doi: 10.20965/jaciii.2015.p0892
    [44]
    R. Wu, Y. B. Li, S. S. Guo, W. X. Xu, " Solving the dual-resource constrained flexible job shop scheduling problem with learning effect by a hybrid genetic algorithm,” Adv. Mech. Eng., vol. 10, no. 10, pp. 1–14, 2018.
    [45]
    M. E. Meziane, N. Taghezout, " A hybrid genetic algorithm with a neighborhood function for flexible job shop scheduling,” Multi-Agent Grid Syst., vol. 14, no. 2, pp. 161–175, 2018. doi: 10.3233/MGS-180286
    [46]
    Z. S. Zhang, Y. M. Chen, Y. J. Tan, J. G. Yan, " Non-crossover and multi-mutation based genetic algorithm for flexible job-shop scheduling problem,” IEICE Trans. Fund. Electron. Commun. Comput. Sci., vol. 99, no. 10, pp. 1856–1862, 2016.
    [47]
    Y. Demir, S. K. Isleyen, " Note to Scheduling jobs and maintenances in flexible job shop with a hybrid genetic algorithm,” J. Intel. Manuf., vol. 25, no. 1, pp. 209–211, 2014. doi: 10.1007/s10845-012-0693-y
    [48]
    H. J. Huang, T. P. Lu, " Solving a multi-objective flexible job shop scheduling problems with timed petri nets and genetic algorithm,” Discrete Math. Algorithms Appl., vol. 2, no. 2, pp. 221–237, 2010. doi: 10.1142/S1793830910000607
    [49]
    G. H. Zhang, X. Y. Shao, P. G. Li, L. Gao, " An effective hybrid particle swarm optimization algorithm for multi-objective flexible job-shop scheduling problem,” Comput. Ind. Eng., vol. 56, no. 4, pp. 1309–1318, 2009. doi: 10.1016/j.cie.2008.07.021
    [50]
    G. Moslehi, M. Mahnam, " A Pareto approach to multi-objective flexible job-shop scheduling problem using particle swarm optimization and local search,” Int. J. Prod. Econ., vol. 129, no. 1, pp. 14–22, 2011. doi: 10.1016/j.ijpe.2010.08.004
    [51]
    X.Y. Shao, W.Q. Liu, Q. Liu, C.Y. Zhang, " Hybrid discrete particle swarm optimization for multi-objective flexible job-shop scheduling problem,” Int. J. Adv. Manuf. Tech., vol. 67, no. 9-12, pp. 2885–2901, 2885.
    [52]
    M. Nouiri, A. Bekrar, A. Jemai, S. Niar, A. C. Ammari, " An effective and distributed particle swarm optimization algorithm for flexible job-shop scheduling problem,” J. Intel. Manuf., vol. 29, no. 3, pp. 603–615, 2018. doi: 10.1007/s10845-015-1039-3
    [53]
    M. R. Singh, S. S. Mahapatra, " A quantum behaved particle swarm optimization for flexible job shop scheduling,” Comput. Ind. Eng., vol. 93, pp. 36–44, 2016. doi: 10.1016/j.cie.2015.12.004
    [54]
    M. Nouiri, A. Bekrar, A. Jemai, D. Trentesaux, A. C. Ammari, S. Niar, " Two stage particle swarm optimization to solve the flexible job shop predictive scheduling problem considering possible machine breakdowns,” Comput. Ind. Eng., vol. 112, pp. 595–606, 2017. doi: 10.1016/j.cie.2017.03.006
    [55]
    S. Huang, N. Tian, Y. Wang, Z. C. Ji, " Multi-objective flexible job-shop scheduling problem using modified discrete particle swarm optimization,” SPRINGER PLUS, vol. 5, no. 1, pp. 1432, 2016. doi: 10.1186/s40064-016-3054-z
    [56]
    S. Nourali, N. Imanipour, " A particle swarm optimization-based algorithm for flexible assembly job shop scheduling problem with sequence dependent setup times,” Sci. Iran, vol. 21, no. 3, pp. 1021–1033, 2014.
    [57]
    H. Boukef, M. Benrejeb, P. Borne, " Flexible job-shop scheduling problems resolution inspired from particle swarm optimization,” Stud. Inform. Control, vol. 17, no. 3, pp. 241–252, 2008.
    [58]
    M. R. Singh, M. Singh, S. S. Mahapatra, N. Jagadev, " Particle swarm optimization algorithm embedded with maximum deviation theory for solving multi-objective flexible job shop scheduling problem,” Int. J. Adv. Manuf. Tech., vol. 85, no. 9–12, pp. 2353–2366, 2016. doi: 10.1007/s00170-015-8075-1
    [59]
    W. Teekeng, A. Thammano, P. Unkaw, J. Kiatwuthiamorn, " A new algorithm for flexible job-shop scheduling problem based on particle swarm optimization,” Artif. Life Robo., vol. 21, no. 1, pp. 18–23, 2016. doi: 10.1007/s10015-015-0259-0
    [60]
    T. Jamrus, C. F. Chien, M. Gen, K. Sethanan, " Hybrid particle swarm optimization combined with genetic operators for flexible job-shop scheduling under uncertain processing time for semiconductor manufacturing,” IEEE Trans. Semicond. Manuf., vol. 31, no. 1, pp. 32–41, 2018. doi: 10.1109/TSM.2017.2758380
    [61]
    J. Zhang, J. Jie, W. L. Wang, X. L. Xu, " A hybrid particle swarm optimisation for multi-objective flexible job-shop scheduling problem with dual-resources constrained,” Int. J. Comput. Sci. Math., vol. 8, no. 6, pp. 526–532, 2017. doi: 10.1504/IJCSM.2017.088956
    [62]
    H. Daliria, H. Mokhtari, I. N. Kamalabadi, " A particle swarm optimization approach to joint location and scheduling decisions in a flexible job shop environment,” Int. J. Eng., vol. 28, no. 12, pp. 756–1764, 2015.
    [63]
    L. N. Xing, Y. W. Chen, P. Wang, Q. S. Zhao, J. Xiong, " Knowledge-based ant colony optimization for flexible job shop scheduling problems,” Appl. Soft Comput., vol. 10, no. 3, pp. 888–896, 2010. doi: 10.1016/j.asoc.2009.10.006
    [64]
    A. Rossi, G. Dini, " Flexible job-shop scheduling with routing flexibility and separable setup times using ant colony optimisation method,” Robot. Comput.Integr. Manuf., vol. 23, no. 5, pp. 503–516, 2007. doi: 10.1016/j.rcim.2006.06.004
    [65]
    R. H. Huang, C. L. Yang, W. C. Cheng, " Flexible job shop scheduling with due window a two-pheromone ant colony approach,” Int. J. Prod. Econ., vol. 141, no. 2, pp. 685–697, 2013. doi: 10.1016/j.ijpe.2012.10.011
    [66]
    A. Rossi, " Flexible job shop scheduling with sequence-dependent setup and transportation times by ant colony with reinforced pheromone relationships,” Int. J. Prod. Econ, vol. 153, pp. 253–267, 2014. doi: 10.1016/j.ijpe.2014.03.006
    [67]
    B. Z. Yao, C. Y. Yang, J. J. Hu, J. B. Yao, J. Sun, " An improved ant colony optimization for flexible job shop scheduling problems,” Adv. Sci. Lett., vol. 4, no. 6–7, pp. 2127–2131, 2011.
    [68]
    F. El Khoukhi, J. Boukachour, A.E. Alaoui, " The dual-ants colony: a novel hybrid approach for the flexible job shop scheduling problem with preventive maintenance,” Comput. Ind. Eng., vol. 106, pp. 236–255, 2017. doi: 10.1016/j.cie.2016.10.019
    [69]
    D. L. Luo, H. P. Chen, S. X. Wu, Y. X. Shi, " Hybrid ant colony multi-objective optimization for flexible job shop scheduling problems,” J. Internet Tech., vol. 11, no. 3, pp. 361–369, 2010.
    [70]
    L. Wang, J. C. Cai, M. Li, Z. H. Liu, " Flexible job shop scheduling Pproblem using an improved ant colony optimization,” Sci. Program., pp. 9016303, 2017.
    [71]
    J. Q. Li, Q. K. Pan, Y. C. Liang, " An effective hybrid tabu search algorithm for multi-objective flexible job-shop scheduling problems,” Comput. Ind. Eng., vol. 59, no. 4, pp. 647–662, 2010. doi: 10.1016/j.cie.2010.07.014
    [72]
    J. Q. Li, Q. K. Pan, P. N. Suganthan, T. J. Chua, " A hybrid tabu search algorithm with an efficient neighborhood structure for the flexible job shop scheduling problem,” Int. J. Adv Manuf. Tech., vol. 52, no. 5–8, pp. 683–697, 2011. doi: 10.1007/s00170-010-2743-y
    [73]
    S.-M. Mohammad, F. Parviz, " Flexible job shop scheduling with tabu search algorithms,” Int. J. Adv. Manuf. Tech., vol. 32, no. 5–6, pp. 563–570, 2007. doi: 10.1007/s00170-005-0375-4
    [74]
    Q. Zhang, H. Manier, M. A. Manier, " A genetic algorithm with tabu search procedure for flexible job shop scheduling with transportation constraints and bounded processing times,” Comput. Oper. Res., vol. 39, no. 7, pp. 1713–1723, 2012. doi: 10.1016/j.cor.2011.10.007
    [75]
    X.Y. Li, L. Gao, " An effective hybrid genetic algorithm and tabu search for flexible job shop scheduling problem,” Int. J. Prod. Econ, vol. 174, pp. 93–110, 2016. doi: 10.1016/j.ijpe.2016.01.016
    [76]
    S. Jia, Z. H. Hu, " Path-relinking Tabu search for the multi-objective flexible job shop scheduling problem,” Comput. Oper. Res,vol. 47,pp.11-26, vol. 47, pp. 11–26, 2014.
    [77]
    G. Vilcot, J. C. Billaut, " A tabu search algorithm for solving a multicriteria flexible job shop scheduling problem,” Int. J. Prod. Res., vol. 49, no. 23, pp. 6963–6980, 2011. doi: 10.1080/00207543.2010.526016
    [78]
    R. Logendran, A. Sonthinen, " A Tabu search-based approach for scheduling job-shop type flexible manufacturing systems,” J. Oper. Res. Soc., vol. 48, no. 3, pp. 264–277, 1997. doi: 10.1057/palgrave.jors.2600373
    [79]
    A.T. Eshlaghy, S.A. Sheibatolhamdy, " Scheduling in flexible job-shop manufacturing system by improved tabu search,” Afr. J. Bus. Manag., vol. 5, no. 12, pp. 4863–4872, 2011.
    [80]
    B. Marzouki, O. B. Driss, K. Ghedira, " Multi-agent model based on combination of chemical reaction optimisation metaheuristic with Tabu search for flexible job shop scheduling problem,” Int. J. Intel. Eng. Inform., vol. 6, no. 3-4, pp. 242–265, 2018.
    [81]
    J. Q. Li, P. Y. Duan, J. D. Cao, X. P. Lin, Y. Y. Han, " A hybrid Pareto-based Tabu search for the distributed flexible job shop scheduling problem with E/T criteria,” IEEE Access, vol. 6, pp. 58883–58897, 2018. doi: 10.1109/ACCESS.2018.2873401
    [82]
    J. Q. Li, Q. K. Pan, K. Z. Gao, " Pareto-based discrete artificial bee colony algorithm for multi-objective flexible job shop scheduling problems,” Int J. Adv. Manuf. Tech., vol. 55, no. 9–12, pp. 1159–1169, 2011. doi: 10.1007/s00170-010-3140-2
    [83]
    L. Wang, G. Zhou, Y. Xu, S.Y. Wang, Liu Min, " An effective artificial bee colony algorithm for the flexible job-shop scheduling problem,” Int. J. Adv. Manuf. Tech., vol. 60, no. 1-4, pp. 303–315, 2012. doi: 10.1007/s00170-011-3610-1
    [84]
    J. Q. Li, Q. K. Pan, M. F. Tasgetiren, " A discrete artificial bee colony algorithm for the multi-objective flexible job-shop scheduling problem with maintenance activities,” Appl. Math. Model., vol. 38, no. 3, pp. 1111–1132, 2014. doi: 10.1016/j.apm.2013.07.038
    [85]
    L. Wang, G. Zhou, Y. Xu, M. Liu, " An enhanced Pareto-based artificial bee colony algorithm for the multi-objective flexible job-shop scheduling,” Int. J. Adv. Manuf. Tech., vol. 60, no. 9–12, pp. 1111–1123, 2012. doi: 10.1007/s00170-011-3665-z
    [86]
    L. Wang, G. Zhou, Y. Xu, M. Liu, " A hybrid artificial bee colony algorithm for the fuzzy flexible job-shop scheduling problem,” Int. J. Prod. Res, vol. 51, no. 12, pp. 3593–3608, 2013. doi: 10.1080/00207543.2012.754549
    [87]
    K. Z. Gao, P. N. Suganthan, T. J. Chua, C. S. Chong, T. X. Cai, Q. K. Pan, " A two-stage artificial bee colony algorithm scheduling flexible job-shop scheduling problem with new job insertion,” Expert Syst. Appl., vol. 42, no. 21, pp. 7652–7663, 2015. doi: 10.1016/j.eswa.2015.06.004
    [88]
    J. Q. Li, Q. K. Pan, S. X. Xie, S. Wang, " A hybrid artificial bee colony algorithm for flexible job shop scheduling problems,” Int. J. Comput. Commun. Control, vol. 6, no. 2, pp. 286–296, 2011. doi: 10.15837/ijccc.2011.2
    [89]
    K. Z. Gao, P. N. Suganthan, Q. K. Pan, T. J. Chua, C. S. Chong, T. X. Cai, " An improved artificial bee colony algorithm for flexible job-shop scheduling problem with fuzzy processing time,” Expert Syst Appl., vol. 65, pp. 52–67, 2016. doi: 10.1016/j.eswa.2016.07.046
    [90]
    K. Z. Gao, P. N. Suganthan, Q. K. Pan, M. F. Tasgetiren, A. Sadollah, " Artificial bee colony algorithm for scheduling and rescheduling fuzzy flexible job shop problem with new job insertion,” Knowl-Based Syst., vol. 109, pp. 1–16, 2016. doi: 10.1016/j.knosys.2016.06.014
    [91]
    D. M. Lei, " Multi-objective artificial bee colony for interval job shop scheduling with flexible maintenance,” Int. J. Adv. Manuf. Tech., vol. 66, no. 9–12, pp. 1835–1843, 2013. doi: 10.1007/s00170-012-4463-y
    [92]
    X. X Li, Z. Peng, B. G. Du, J. Guo, W. X. Xu, K. J. Zhuang, " Hybrid artificial bee colony algorithm with a rescheduling strategy for solving flexible job shop scheduling problems,” Comput. Ind. Eng., vol. 113, pp. 10–26, 2017. doi: 10.1016/j.cie.2017.09.005
    [93]
    T. Meng, Q.K. Pan, H.Y. Sang, " A hybrid artificial bee colony algorithm for a flexible job shop scheduling problem with overlapping in operations,” Int J. Prod. Res, vol. 56, no. 16, pp. 5278–5292, 2018. doi: 10.1080/00207543.2018.1467575
    [94]
    K. Z. Gao, P. N. Suganthan, Q. K. Pan, T. J. Chua, T. X. Cai, C. S. Chong, " Pareto-based grouping discrete harmony search algorithm for multi-objective flexible job shop scheduling,” Inform. Sci., vol. 289, pp. 76–90, 2014. doi: 10.1016/j.ins.2014.07.039
    [95]
    Y. Yuan, H. Xu, J.D. Yang, " A hybrid harmony search algorithm for the flexible job shop scheduling problem,” Appl. Soft Comput., vol. 13, no. 7, pp. 3259–3272, 3259.
    [96]
    K. Z. Gao, P. N. Suganthan, Q. K. Pan, T. J. Chua, T. X. Cai, C. S. Chong, " Discrete harmony search algorithm for flexible job shop scheduling problem with multiple objectives,” J. Intel. Manuf., vol. 27, no. 2, pp. 363–374, 2016. doi: 10.1007/s10845-014-0869-8
    [97]
    K. Z. Gao, P. N. Suganthan, Q. K. Pan, M. F. Tasgetiren, " An effective discrete harmony search algorithm for flexible job shop scheduling problem with fuzzy processing time,” Int. J. Prod. Res, vol. 53, no. 19, pp. 5896–5911, 2015. doi: 10.1080/00207543.2015.1020174
    [98]
    A. Maroosi, R. C. Muniyandi, E. Sundararajan, A.M. Zin, " A parallel membrane inspired harmony search for optimization problems: A case study based on a flexible job shop scheduling problem,” Appl. Soft Comput., vol. 49, pp. 120–136, 2016. doi: 10.1016/j.asoc.2016.08.007
    [99]
    M. Gaham, B. Bouzouia, N. Achour, " An effective operations permutation-based discrete harmony search approach for the flexible job shop scheduling problem with makespan criterion,” Appl. Intel., vol. 48, no. 6, pp. 1423–1441, 2018. doi: 10.1007/s10489-017-0993-1
    [100]
    Y. Yuan, H. Xu, " Multiobjective flexible job shop scheduling using memetic algorithms,” IEEE Trans. Auto. Sci. Eng., vol. 12, no. 1, pp. 336–353, 2015. doi: 10.1109/TASE.2013.2274517
    [101]
    M. Frutos, O. A. Carolina, F. Tohme, " A memetic algorithm based on a NSGAII scheme for the flexible job-shop scheduling problem,” Ann. Oper. Res., vol. 181, no. 1, pp. 745–765, 2010. doi: 10.1007/s10479-010-0751-9
    [102]
    W. C. Yi, X. Y. Li, B. L. Pan, " Solving flexible job shop scheduling using an effective memetic algorithm,” Int. J. Comput. Appl. Tech., vol. 53, no. 2, pp. 157–163, 2016. doi: 10.1504/IJCAT.2016.074454
    [103]
    H. Farughi, B.Y. Yegane, M. Fathian, " A new critical path method and a memetic algorithm for flexible job shop scheduling with overlapping operations,” Simul-T Soc. Mod. Sim., vol. 89, no. 3, pp. 264–277, 2013.
    [104]
    C. Wang, N. Tian, Z.C. Ji, Y. Wang, " Multi-objective fuzzy flexible job shop scheduling using memetic algorithm,” J. Stat. Comput. Sim., vol. 87, no. 14, pp. 2828–2846, 2017. doi: 10.1080/00949655.2017.1344846
    [105]
    A. Phu-ang, A. Thammano, " Memetic algorithm based on marriage in honey bees optimization for flexible job shop scheduling problem,” Memetic Comput., vol. 9, no. 4, pp. 295–309, 2017. doi: 10.1007/s12293-017-0230-9
    [106]
    T. C. Chiang, H. J. Lin, " A simple and effective evolutionary algorithm for multiobjective flexible job shop scheduling,” Int. J. Prod. Econ., vol. 141, no. 1, pp. 87–98, 2013. doi: 10.1016/j.ijpe.2012.03.034
    [107]
    I. T. Tanev, T. Uozumi, Y. Morotome, " Hybrid evolutionary algorithm-based real-world flexible job shop scheduling problem: application service provider approach,” Appl. Soft Comput., vol. 5, no. 1, pp. 87–100, 2004. doi: 10.1016/j.asoc.2004.03.013
    [108]
    X. N. Shen, X. Yao, " Mathematical modeling and multi-objective evolutionary algorithms applied to dynamic flexible job shop scheduling problems,” Inform. Sci., vol. 298, pp. 198–224, 2015. doi: 10.1016/j.ins.2014.11.036
    [109]
    R. Zarrouk, I.E. Bennour, A. Hemai, " A two-level particle swarm optimization algorithm for the flexible job shop scheduling problem,” Swarm Intell., vol. 13, no. 2, pp. 145–168, 2019. doi: 10.1007/s11721-019-00167-w
    [110]
    S. H. A. Rahmati, M. Zandieh, M. Yazdani, " Developing two multi-objective evolutionary algorithms for the multi-objective flexible job shop scheduling problem,” Int. J. Adv. Manuf. Tech., vol. 64, no. 5–8, pp. 915–932, 2013. doi: 10.1007/s00170-012-4051-1
    [111]
    E. Ahmadi, M. Zandieh, M. Farrokh, S.M. Emami, " A multi objective optimization approach for flexible job shop scheduling problem under random machine breakdown by evolutionary algorithms,” Comput. Oper Res., vol. 73, pp. 56–66, 2016. doi: 10.1016/j.cor.2016.03.009
    [112]
    X. L. Wu, S. M. Wu, " An elitist quantum-inspired evolutionary algorithm for the flexible job-shop scheduling problem,” J. Intel. Manuf., vol. 28, no. 6, pp. 1441–1457, 2017. doi: 10.1007/s10845-015-1060-6
    [113]
    A. Rossi, G. Dini, " An evolutionary approach to complex job-shop and flexible manufacturing system scheduling,” P. I. Mech. Eng. J-J Eng., vol. 215, no. 2, pp. 233–245, 2001.
    [114]
    I. Kacem, S. Hammadi, P. Borne, " Correction to ‘Approach by localization and multiobjective evolutionary optimization for flexible job-shop scheduling problems (vol 32, pg 1, 2002),” IEEE Trans. Syst. Man Cybrn. C Appl. Rev, vol. 32, no. 2, pp. 172–172, 2002. doi: 10.1109/TSMCC.2002.804307
    [115]
    M. B. S. S Reddy, C. Ratnam, G. Rajyalakshmi, V. K. Manupati, " An effective hybrid multi objective evolutionary algorithm for solving real time event in flexible job shop scheduling problem,” Measurement, vol. 114, pp. 78–90, 2018. doi: 10.1016/j.measurement.2017.09.022
    [116]
    C. Wang, Z. C. Ji, W. Yan, " Multi-objective flexible job shop scheduling problem using variable neighborhood evolutionary algorithm,” Mod. Phys. Lett B, vol. 31, pp. 19–21, 2017.
    [117]
    T. K. Liu, Y. P. Chen, J. H. Chou, " Evolutionary scheduling system using a universal encoding operator in a distributed and flexible job-shop manufacturing environment,” J. Chin Soc. Mech. Eng., vol. 36, no. 3, pp. 221–232, 2015.
    [118]
    M. Yazdani, M. Amiri, M. Zandieh, " Flexible job-shop scheduling with parallel variable neighborhood search algorithm,” Expert Syst. Appl., vol. 37, no. 1, pp. 678–687, 2010. doi: 10.1016/j.eswa.2009.06.007
    [119]
    A. Ishigaki, Y. Matsui, " Effective neighborhood generation method in search algorithm for flexible job shop scheduling problem,” Int. J. Autom. Tech., vol. 13, no. 3, pp. 389–296, 2019. doi: 10.20965/ijat.2019.p0389
    [120]
    M. Amiri, M. Zandieh, M. Yazdani, A. Bagheri, " A variable neighbourhood search algorithm for the flexible job-shop scheduling problem,” Int. J. Prod. Res., vol. 48, no. 19, pp. 5671–5689, 2010. doi: 10.1080/00207540903055743
    [121]
    A. Bagheri, M. Zandieh, " Bi-criteria flexible job-shop scheduling with sequence-dependent setup times-Variable neighborhood search approach,” J. Manuf. Syst., vol. 30, no. 1, pp. 8–15, 2011. doi: 10.1016/j.jmsy.2011.02.004
    [122]
    D. M. Lei, X. P. Guo, " Variable neighbourhood search for dual-resource constrained flexible job shop scheduling,” Int. J. Prod. Res., vol. 52, no. 9, pp. 2519–2529, 2014. doi: 10.1080/00207543.2013.849822
    [123]
    D. M. Lei, X. P. Guo, " Swarm-based neighbourhood search algorithm for fuzzy flexible job shop scheduling,” Int. J. Prod. Res., vol. 50, no. 6, pp. 1639–1649, 2012. doi: 10.1080/00207543.2011.575412
    [124]
    Y. L. Zheng, Y. X. Li, D. M. Lei, " Multi-objective swarm-based neighborhood search for fuzzy flexible job shop scheduling,” Int. J. Adv. Manuf. Tech., vol. 60, no. 9–12, pp. 1063–1069, 2012. doi: 10.1007/s00170-011-3646-2
    [125]
    T. F. Abdelmaguid, " A neighborhood search function for flexible job shop scheduling with separable sequence-dependent setup times,” Appl. Math. Comput., vol. 260, pp. 188–203, 2015.
    [126]
    S. Huang, N. Tian, Z. C. Ji, " Particle swarm optimization with variable neighborhood search for multiobjective flexible job shop scheduling problem,” Int. J. Model. Simul. Sci. Comput., vol. 7, no. 3, UNSP 1650024, 2016. doi: 10.1142/S1793962316500240
    [127]
    A. Baykasoglu, " Linguistic-based meta-heuristic optimization model for flexible job shop scheduling,” Int. J. Prod. Res., vol. 40, no. 17, pp. 4523–4543, 2002. doi: 10.1080/00207540210147043
    [128]
    N. Shahsavari-Pour, B. Ghasemishabankareh, " A novel hybrid meta-heuristic algorithm for solving multi objective flexible job shop scheduling,” J. Manuf. Syst., vol. 32, no. 4, pp. 771–780, 2013. doi: 10.1016/j.jmsy.2013.04.015
    [129]
    V. Roshanaei, A. Azab, H. ElMaraghy, " Mathematical modelling and a meta-heuristic for flexible job shop scheduling,” Int. J. Prod. Res., vol. 51, no. 20, pp. 6247–6274, 2013. doi: 10.1080/00207543.2013.827806
    [130]
    V. M. Dalfard, G. Mohammadi, " Two meta-heuristic algorithms for solving multi-objective flexible job-shop scheduling with parallel machine and maintenance constraints,” Comput. Math. Appl., vol. 64, no. 6, pp. 2111–2117, 2012. doi: 10.1016/j.camwa.2012.04.007
    [131]
    M. E. T Araghi, F. Jolai, M. Rabiee, " Incorporating learning effect and deterioration for solving a SDST flexible job-shop scheduling problem with a hybrid meta-heuristic approach,” Int. J. Comput. Integ. Manuf., vol. 27, no. 8, pp. 733–746, 2014. doi: 10.1080/0951192X.2013.834465
    [132]
    M. Yazdani, M. Zandieh, R. Tavakkoli-Moghaddam,, F. Jolai, " Two meta-heuristic algorithms for the dual-resource constrained flexible job-shop scheduling problem,” Sci. Iran, vol. 22, no. 3, pp. 1242–1257, 2015.
    [133]
    R. Wu, Y. B. Li, S. S. Guo, X. X. Li, " An efficient meta-heuristic for multi-objective flexible job shop inverse scheduling problem,” IEEE Access, vol. 6, pp. 59515–59527, 2018. doi: 10.1109/ACCESS.2018.2875176
    [134]
    S.H.A. Rahmati, M. Zandieh, " A new biogeography-based optimization (BBO) algorithm for the flexible job shop scheduling problem,” Int. J. Adv. Manuf. Tech., vol. 58, no. 9–12, pp. 1115–1129, 2012. doi: 10.1007/s00170-011-3437-9
    [135]
    J. Lin, " A hybrid biogeography-based optimization for the fuzzy flexible job-shop scheduling problem,” Knowl-Based Syst., vol. 78, pp. 59–74, 2015. doi: 10.1016/j.knosys.2015.01.017
    [136]
    L. Wang, S.Y. Wang, Y. Xu, G. Zhou, M. Liu, " A bi-population based estimation of distribution algorithm for the flexible job-shop scheduling problem,” Comput. Ind. Eng., vol. 62, no. 4, pp. 917–926, 2012. doi: 10.1016/j.cie.2011.12.014
    [137]
    S.Y. Wang, L. Wang, Y. Xu, M. Liu, " An effective estimation of distribution algorithm for the flexible job-shop scheduling problem with fuzzy processing time,” Int. J. Prod. Res., vol. 51, no. 12, pp. 3778–3793, 2013. doi: 10.1080/00207543.2013.765077
    [138]
    L. Wang, S.Y. Wang, M. Liu, " A Pareto-based estimation of distribution algorithm for the multi-objective flexible job-shop scheduling problem,” Int. J. Prod. Res., vol. 51, no. 12, pp. 3574–3592, 2013. doi: 10.1080/00207543.2012.752588
    [139]
    B. J. Liu, Y. S. Fan, Y. Liu, " A fast estimation of distribution algorithm for dynamic fuzzy flexible job-shop scheduling problem,” Comput. Ind. Eng., vol. 87, pp. 193–201, 2015. doi: 10.1016/j.cie.2015.04.029
    [140]
    R. Perez-Rodriguez, A. Hernandez-Aguirre, " A hybrid estimation of distribution algorithm for flexible job-shop scheduling problems with process plan flexibility,” Appl. Intel., vol. 48, no. 10, pp. 3707–3734, 2018. doi: 10.1007/s10489-018-1160-z
    [141]
    H. W. Ge, L. Sun, X. Chen, Y. C. Liang, " An efficient artificial fish swarm model with estimation of distribution for flexible job shop scheduling,” Int. J. Comput. Intel. Syst., vol. 9, no. 5, pp. 917–931, 2016. doi: 10.1080/18756891.2016.1237190
    [142]
    X. J. Wang, L. Gao, C. Y. Zhang, X. Y. Shao, " A multi-objective genetic algorithm based on immune and entropy principle for flexible job-shop scheduling problem,” Int. J. Adv. Manuf. Tech., vol. 51, no. 5–8, pp. 757–767, 2010. doi: 10.1007/s00170-010-2642-2
    [143]
    N. Shivasankaran, P. S Kumar, K. V. Raja, " Hybrid sorting immune simulated annealing algorithm for flexible job shop scheduling,” Int. J. Comput. Intel. Syst., vol. 8, no. 3, pp. 455–466, 2015. doi: 10.1080/18756891.2015.1017383
    [144]
    W. Xiong, D. M. Fu, " A new immune multi-agent system for the flexible job shop scheduling problem,” J. Intel. Manuf., vol. 29, no. 4, pp. 857–873, 2018. doi: 10.1007/s10845-015-1137-2
    [145]
    X. Liang, M. Huang, T. Ning, " Flexible job shop scheduling based on improved hybrid immune algorithm,” J. Amb. Intel. Hum. Comput., vol. 9, no. 1, pp. 165–171, 2018. doi: 10.1007/s12652-016-0425-9
    [146]
    J. Q. Li, Q. K. Pan, " Chemical-reaction optimization for flexible job-shop scheduling problems with maintenance activity,” Appl. Soft Comput., vol. 12, no. 9, pp. 2896–2912, 2012. doi: 10.1016/j.asoc.2012.04.012
    [147]
    J. Q. Li, Q. K. Pan, " Chemical-reaction optimization for solving fuzzy job-shop scheduling problem with flexible maintenance activities,” Int. J. Prod. Econ., vol. 145, no. 1, pp. 4–17, 2013. doi: 10.1016/j.ijpe.2012.11.005
    [148]
    Z.C. Li, B. Qian, R. Hu, L.L. Chang, J.B. Yang, " An elitist nondominated sorting hybrid algorithm for multi-objective flexible job-shop scheduling problem with sequence-dependent setups,” Knowl-Based Syst., vol. 27, no. 5, pp. 1008–1022, 2019.
    [149]
    L. Gao, Q. K. Pan, " A shuffled multi-swarm micro-migrating birds optimizer for a multi-resource-constrained flexible job shop scheduling problem,” Inform. Sci., vol. 372, pp. 655–676, 2016. doi: 10.1016/j.ins.2016.08.046
    [150]
    Y. Yuan, H. Xu, " Flexible job shop scheduling using hybrid differential evolution algorithms,” Comput. Ind. Eng., vol. 65, no. 2, pp. 246–260, 2013. doi: 10.1016/j.cie.2013.02.022
    [151]
    D. Y. Ma, C. H. He, S. Q. Wang, X. M. Han, X. H. Shi, " Solving fuzzy flexible job shop scheduling problem based on fuzzy satisfaction rate and differential evolution,” Adv. Prod. Eng. Manag., vol. 13, no. 1, pp. 44–56, 2018.
    [152]
    H. J. Zhang, Q. Yan, G. H. Zhang, Z. Q. Jiang, " A chaotic differential evolution algorithm for flexible job shop scheduling,” Theory,Methodology,Tools and Applications for Modeling and Simulation of complex systems,II, vol. 644, pp. 79–88, 2016. doi: 10.1007/978-981-10-2666-9
    [153]
    X. L. Zheng, L. Wang, " A knowledge-guided fruit fly optimization algorithm for dual resource constrained flexible job-shop scheduling problem,” Int. J. Prod. Res., vol. 54, no. 18, pp. 5554–5566, 2016. doi: 10.1080/00207543.2016.1170226
    [154]
    Q. Liu, M. M. Zhan, F. O. Chekem, X. Y. Shao, B. S. Ying, J. W. Sutherland, " A hybrid fruit fly algorithm for solving flexible job-shop scheduling to reduce manufacturing carbon footprint,” J. Clean. Prod., vol. 168, pp. 668–678, 2017. doi: 10.1016/j.jclepro.2017.09.037
    [155]
    M. Zandieh, A. R. Khatami, S. H. A. Rahmati, " Flexible job shop scheduling under condition-based maintenance: Improved version of imperialist competitive algorithm,” Appl. Soft Comput., vol. 58, pp. 449–464, 2017. doi: 10.1016/j.asoc.2017.04.060
    [156]
    S. Karimi, Z. Ardalan, B. Naderi, M. Mohammadi, " Scheduling flexible job-shops with transportation times: Mathematical models and a hybrid imperialist competitive algorithm,” Appl. Math. Model, vol. 41, pp. 667–682, 2017. doi: 10.1016/j.apm.2016.09.022
    [157]
    J. Q. Li, Q. K. Pan, S. X. Xie, " An effective shuffled frog-leaping algorithm for multi-objective flexible job shop scheduling problems,” Appl. Math. Comput., vol. 218, no. 18, pp. 9353–9371, 2012.
    [158]
    D. M. Lei, Y. L. Zheng, X. P. Guo, " A shuffled frog-leaping algorithm for flexible job shop scheduling with the consideration of energy consumption,” Int. J. Prod. Res., vol. 55, no. 11, pp. 3126–3140, 2017. doi: 10.1080/00207543.2016.1262082
    [159]
    W. Teekeng, A. Thammano, " A combination of shuffled frog leaping and fuzzy logic for flexible job-shop scheduling problems,” Procedia Computer Science, vol. 6, pp. 69–75, 2011. doi: 10.1016/j.procs.2011.08.015
    [160]
    H.T. Tang, R. Chen, Y.B. Li, et al, " Flexible job-shop scheduling with tolerated time interval and limited starting time interval based on hybrid discrete PSO-SA: An application from a casting workshop,” Appl. Soft Comput., vol. 78, pp. 176–194, 2019. doi: 10.1016/j.asoc.2019.02.011
    [161]
    M. A. Cruz-Chavez, M. G. Martinez-Rangel, M. H. Cruz-Rosales, " Accelerated simulated annealing algorithm applied to the flexible job shop scheduling problem,” Int. Trans. Oper. Res., vol. 24, no. 5, pp. 1119–1137, 2017. doi: 10.1111/itor.2017.24.issue-5
    [162]
    R. Zeng, Y.Y. Wang, " A chaotic simulated annealing and particle swarm improved artificial immune algorithm for flexible job shop scheduling problem,” Eursip J. Wirel. Comm., vol. 2018, no. 101, 2018. doi: 10.1186/s13638-018-1109-2
    [163]
    S. Kavitha, P. Venkumar, N. Rajini, P. Pitchipoo, " An efficient social spider optimization for flexible job shop scheduling problem,” J. Adv. Manuf. Syst., vol. 17, no. 2, pp. 181–196, 2018. doi: 10.1142/S0219686718500117
    [164]
    C. Lu, X.Y Li, L. Gao, W. Liao, Y. Jin, " An effective multi-objective discrete virus optimization algorithm for flexible job-shop scheduling problem with controllable processing times,” Comput. Ind. Eng., vol. 104, pp. 156–174, 2017. doi: 10.1016/j.cie.2016.12.020
    [165]
    I Kacem, "Genetic algorithm for the flexible job-shop scheduling problem," in Proc. IEEE-SMC, Washington, DC, USA, 2003, pp. 3464–3469.
    [166]
    K. F. Guimaraes, M. A. Fernandes, " An approach for flexible job-shop scheduling with separable sequence-dependent setup time,” in Proc. IEEE-SMC, Taipei, China, 2006, pp. 3727–3731.
    [167]
    J. Q. Li, Q. K. Pan, S. X. Xie, " Flexible job shop scheduling problems by a hybrid artificial bee colony algorithm,” in Proc. IEEE-CEC, New Orleans, LA, USA, 2011, pp. 78–83.
    [168]
    W. P. Ma, Y. Zuo, J. L. Zeng, S. Liang, L. C. Jiao, " A memetic algorithm for solving flexible job-shop scheduling problems,” in Proc. IEEE-CEC, Beijing, China, 2014, pp. 66–73.
    [169]
    L. C. F. Carvalho, M.A. Fernandes, "Multi-objective flexible job-shop scheduling problem with DIPSO: more diversity, greater efficiency," in Proc. IEEE-CEC, Beijing, 2014, pp. 282–289.
    [170]
    N. B. Ho, J. C. Tay, " LEGA: An architecture for learning and evolving flexible job-shop schedules,” in Proc. IEEE-CEC, Edinburgh, Scotland, 2005, pp. 1380–1387.
    [171]
    X. N. Shen, Y. Sun, M. Zhang, " An improved MOEA/D for multi-objective flexible job shop scheduling with release time uncertainties,” in Proc. IEEE-CEC, Vancouver, Canada, 2016, pp. 2950–2957.
    [172]
    J. J. Ma, Y. Lei, Z. Wang, L.C. Jiao, R.C. Liu, " A memetic algorithm based on immune multi-objective optimization for flexible job-shop scheduling problems,” in Proc. IEEE-CEC, Beijing, China, 2014, pp. 58–65.
    [173]
    H. W. Ge, L. Sun, " Intelligent scheduling in flexible job shop environments based on artificial fish swarm algorithm with estimation of distribution,” in Proc. IEEE-CEC, Vancouver, Canada, 2016, pp. 3230–3237.
    [174]
    X. Y. Li, L. Gao, " A collaborative evolutionary algorithm for multi-objective flexible job shop scheduling problem,” in Proc. IEEE-SMC, Anchorage, AK, USA, 2011, pp. 997–1002.
    [175]
    Y. Mati, N. Rezg, X. L. Xie, " An integrated greedy heuristic for a flexible job shop scheduling problem,” in Proc. IEEE-SMC, Tucson, AZ, 2001, pp. 2534–2539.
    [176]
    I. Kacem, S. Hammadi, P. Borne, " Approach by localization and genetic manipulation algorithm for flexible job-shop scheduling problem,” in Proc. IEEE-SMC, Tucson, AZ, USA, 2001, pp. 2599–2604.
    [177]
    H. X. Chen, J. Ihlow, C. Lehmann, " A genetic algorithm for flexible job shop scheduling,” in Proc. ICRA, Detroit, MI, USA, 1999, pp. 1120–1125.
    [178]
    T. H. Jiang, G.L. Deng, " Optimizing the low-carbon flexible job shop scheduling problem considering energy consumption,” IEEE Access, vol. 6, pp. 46346–46355, 2018.
    [179]
    X. L. Wu, Y. J. Sun, " A green scheduling algorithm for flexible job shop with energy-saving measures,” J. Clean. Prod., vol. 172, pp. 3249–3264, 2017.
    [180]
    H. Wang, Z.G. Jiang, Y. Wang, H. Zhang, Y.H. Wang, " A two-stage optimization method for energy-saving flexible job shop scheduling based on energy dynamic characterization,” J. Clean. Prod., vol. 188, pp. 575–588, 2018. doi: 10.1016/j.jclepro.2018.03.254
    [181]
    X. Gong, T. D. Pessemier, L. Martens, W. Joseph, " Energy-and labor-aware flexible job shop scheduling under dynamic electricity pricing: a many-objective optimization investigation,” J. Clean. Prod., vol. 209, pp. 1078–1094, 2019. doi: 10.1016/j.jclepro.2018.10.289
    [182]
    J. Lin, " Backtracking search based hyper-heuristic for the flexible job shop scheduling problem with fuzzy processing time,” Eng. Appl. Artif. Intel., vol. 77, pp. 186–196, 2019. doi: 10.1016/j.engappai.2018.10.008
    [183]
    K. Z. Gao, F. J. Yang, M. C. Zhou, Q. K. Pan, P. N. Suganthan, " Flexible job shop rescheduling for new job insertion by using discrete Jaya algorithm,” IEEE Trans. Cybern.,to be published, . doi: 10.1109/TCYB.2018.2817240
    [184]
    D. M. Lei, M. Li, L. Wang, " A two-phase meta-heuristics for multi-objective flexible job shop scheduling problem with total energy consumption,” IEEE Trans. Cybern.,to be published, . doi: 10.1109/TCYB.2018.2796119
    [185]
    P. Brandimarte, " Routing and scheduling in a flexible job shop by tabu search,” Ann. Oper. Res., vol. 41, pp. 157–183, 1993. doi: 10.1007/BF02023073
    [186]
    K. Z. Gao, P. N. Suganthan, Q. K. Pan, M. F. Tasgetiren, " Effective ensembles of heuristics for scheduling multi-objective flexible job shop problem with new job insertion,” Comput. Ind. Eng., vol. 90, pp. 107–117, 2015. doi: 10.1016/j.cie.2015.09.005
    [187]
    S. Jun, S. Lee, H. Chun, " Learning dispatching rules using random forest in flexible job shop scheduling problems,” Int. J. Prod. Res., vol. 57, no. 10, pp. 3290–3310, 2019. doi: 10.1080/00207543.2019.1581954
    [188]
    X.Y. Li, C. Lu, L. Gao, S.Q. Xiao, L. Wen, " An Effective Multi-Objective Algorithm for Energy Efficient Scheduling in a Real-Life Welding Shop,” IEEE Trans. Ind. Inform., vol. 14, no. 12, pp. 5400–5409, 2018. doi: 10.1109/TII.2018.2843441
    [189]
    Y.P. Fu, G.D. Tian, A.M. Fathollahi-Fard, A. Ahmadi, C.Y, " Zhang. Stochastic multi-objective modelling and optimization of an energy-conscious distributed permutation flow shop scheduling problem with the total tardiness constraint,” J. Clean. Prod., 2019. doi: 10.1016/j.jclepro.2019.04.046

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      沈阳化工大学材料科学与工程学院 沈阳 110142

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