Abstract
Scheduling of flexible manufacturing systems is a well-known NP-hard problem which is very complex, due to additional considerations like material handling, alternative routing, and alternative machines. Improvement in the performance of a flexible manufacturing system can be expected by efficient utilization of its resources, by proper integration and synchronization of their scheduling. Differential evolution is a powerful tool which proved itself as a better alternative for solving optimization problems like scheduling. In this paper, the authors addressed simultaneous scheduling of both machines and material handling system with alternative machines for the makespan minimization objective. The authors proposed a machine selection heuristic and a vehicle assignment heuristic which are incorporated in the differential evolution approach to assign the tasks, to appropriate machine and vehicle, and to minimize cycle time.
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References
Che A, Chu C (2008) Optimal scheduling of material handling devices in a PCB production line: problem formulation and a polynomial algorithm. Mathematical Prob Eng 364279:1–21
Che A, Chu C (2007) Cyclic hoist scheduling in large real-life electroplating lines. OR Spectrum 29(3):445–470
Che A, Chu C (2005) Multi-degree cyclic scheduling of two robots in a no-wait flowshop. IEEE Trans Autom Sci Eng 2(2):173–183
Che A, Chu C (2005) A polynomial algorithm for no-wait cyclic hoist scheduling in an extended electroplating line. Oper Res Lett 33(3):274–284
Che A, Chu C, Chu F (2002) Multicyclic hoist scheduling with constant processing times. IEEE Trans Robot Autom 18(1):69–80
Ada Che CC (2009) Multi-degree cyclic scheduling of a no-wait robotic cell with multiple robots. Eur J Oper Res 199:77–88
Ram R, Stecke KE (1993) Classification and review of FMS scheduling procedures. Working paper No. 711, Division of Research, School of Business Administration, The University of Michigan
Babu BV, Jehan MML (2003) Differential evolution for multi-objective optimization in CEC' Canberra. Australia 4:2696–2703
Nearchou AC, Omirou SL (2006) Differential evolution for sequencing and scheduling optimization. J Heuristics 12:395–411
Wu SYD, Wysk RA (1989) An application of discrete-event simulation to on-line control and scheduling in flexible manufacturing. Int J Prod Res 27:1603–162
Ro I, Kim J (1990) Multi-criteria operational control rules in flexible manufacturing systems. Int J Prod Res 28:47–63
Sabuncuoglu I, Hommertzheim DL (1992) Dynamic dispatching algorithm for scheduling machines and automated guided vehicles in a flexible manufacturing system. Int J Prod Res 30:1059–1079
Sawik T (1993) Scheduling of machines and vehicles in an FMS: single-level versus multi-level approach. Automatyka 64:541–568
Karabuk S, SabunCuoglu I (1993) A beam search based algorithm for scheduling machines and AGVs in an FMS. In: Second Industrial Engineering Res Conf, pp 308-312
Ulusoy G, Bilge U (1993) Simultaneous Scheduling of machines and automated guided vehicles. Int J Prod Res 31(12):2857–2873
Sawik T (1995) A multilevel machine and vehicle scheduling in a flexible manufacturing system. Math1 Comput Model 23(7):45–57
Bilge U, Ulusoy G (1995) A time window approach to simultaneous scheduling of machines and material handling system in an FMS. J Opns Res 63(6):1058–1070
Ulusoy G, Srvnkaya-Serifogulg F, Bilge U (1997) A genetic algorithm approach to the simultaneous scheduling of machines and automated guided vehicles. Comput Oper Res 24(4):335–351
Abdelmaguid TF, Nasef AO, Kamal BA, Hassan MF (2004) A hybrid GA / heuristic approach to the simultaneous scheduling of machines and automated guided vehicles. Int J Prod Res 42(2):267–281
Lacomme P, Moukrim A, Tchernev N (2005) Simultaneous job input sequencing and vehicle dispatching in a single vehicle AGVS: a Heuristic branch and bound approach coupled with a discrete events simulation model. Int J Prod Res 43(9):1911–1942
Jerald J, Asokan P, Saravanan P, Rani DC (2006) Simultaneous scheduling of parts and automated guided vehicles in an FMS environment using adaptive genetic algorithm. Int J Adv Manuf Tech 29:584–589
Reddy BSP, Rao CSP (2006) A hybrid multi-objective GA for simultaneous scheduling of machines and AGVs in FMS. Int J Adv Manuf Technol 20:602–613
Wilhelm W, Shin H (1985) Effectiveness of alternative operations in a flexible manufacturing system. Int J Prod Res 23:65–79
Nasr N, Elsayed EA (1990) Job shop scheduling with alternative machines. Int J Prod Res 28(9):1595–1609
Ilkyeong M, Lee J (2000) Genetic Algorithm Application to the Job Shop Scheduling Problem with Alternative Routings. BK21 Logistics Team, Industrial Engineering, Pusan National University
Karboga D, Okdem S (2004) A simple and global optimization algorithm for engineering problems: differential evolution algorithm. Turk J Elec Eng 12(1):53–60
Quan-Ke Pan, Fatih Tasgetiren M, Liang Y-C (2007) A Discrete Differential Evolution Algorithm for the Permutation Flowshop Scheduling Problem. GECCO’07, London, England, United Kingdom, pp 126-133
Zhang J, Xu J (2007) A new differential evolution for discontinuous optimization problems. Third International Conference on Natural Computation (ICNC), IEEE, pp 5-9
Storn R, Price K (1995) Differential evolution—a simple and efficient adaptive scheme for global optimization over continuous spaces. International Computer Science Institute, Berkley, Technical Report TR-95012
Gen M, Cheng R (1997) Genetic algorithms and engineering design. Wiley, NewYork
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Kumar, M.V.S., Janardhana, R. & Rao, C.S.P. Simultaneous scheduling of machines and vehicles in an FMS environment with alternative routing. Int J Adv Manuf Technol 53, 339–351 (2011). https://doi.org/10.1007/s00170-010-2820-2
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DOI: https://doi.org/10.1007/s00170-010-2820-2