Abstract
Flow-shop scheduling problem (FSP) deals with the scheduling of a set of jobs that visit a set of machines in the same order. The FSP is NP-hard, which means that there is no efficient algorithm to reach the optimal solution of the problem. To minimize the make-span of large permutation flow-shop scheduling problems in which there are sequence-dependent setup times on each machine, this paper develops one novel hybrid genetic algorithms (HGA). Proposed HGA apply a modified approach to generate the population of initial chromosomes and also use an improved heuristic called the iterated swap procedure to improve them. Also the author uses three genetic operators to make good new offspring. The results are compared to some recently developed heuristics and computational experimental results show that the proposed HGA performs very competitively with respect to accuracy and efficiency of the solutions.
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References
Ekşioğlu B, Ekşioğlu SD, Jain P (2008) A tabu search algorithm for the flow-shop scheduling problem with changing neighborhoods. Comput Ind Eng 54:1–11
Allahverdi A, Ng CT, Cheng TCE, Kovalyov MY (2008) A survey of scheduling problems with setup times or costs. Eur J Oper Res 187:985–1032
Eren T, Güner TE (2006) A bicriteria scheduling with sequence-dependent setup times. Appl Math Comput 179:378–385
Gupta JND (1986) Flow-shop schedules with sequence-dependent setup times. J Oper Res Soc Jpn 29:206–219
Gupta JND, Darrow WP (1986) The two-machine sequence-dependent flow-shop scheduling problem. Eur J Oper Res 24:439–446
Johnson SM (1954) Optimal two- and three-stage production schedules with setup times included. Nav Res Logist Q 1:61–68
Garey MR, Johnson DS, Sethi R (1976) The complexity of flow-shop and job-shop scheduling. Math Oper Res 1:117–129
Campbell HG, Dudek RA, Smith ML (1970) A heuristic algorithm for the n job, m machine sequencing problem. Manag Sci 16:B630–B637
Nawaz M, Enscore EE, Ham I (1983) A heuristic algorithm for the m-machine, n-job flow-shop sequencing problem. OMEGA Int J Manag Sci 11:91–95
Osman IH, Potts CN (1989) Simulated annealing for permutation flow-shop scheduling. OMEGA Int J Manag Sci 17:551–557
Widmer M, Hertz A (1989) A new heuristic method for the flow shop sequencing problem. Eur J Oper Res 41:186–193
Reeves CR (1995) A genetic algorithm for flow-shop sequencing. Comput Oper Res 22:5–13
Norman BA (1999) Scheduling flow-shops with finite buffers and sequence-dependent setup times. Comput Ind Eng 36:163–177
Ruiz R, Maroto C, Alcaraz J (2005) Solving the flow-shop scheduling problem with sequence-dependent setup times using advanced meta-heuristics. Eur J Oper Res 165:34–54
Ruiz R, Stutzle T (2008) An iterated greedy heuristic for the sequence-dependent setup times flow-shop with make-span and weighted tardiness objectives. Eur J Oper Res 87:1143–1159
Tseng FT, Gupta JND, Stafford EF (2005) A penalty-based heuristic algorithm for the permutation flow-shop scheduling problem with sequence-dependent set-up times. J Oper Res Soc 57:541–551
Sun JU, Hwang H (2001) Scheduling problem in a two machine flow line with the N-step prior-job-dependent set-up times. Int J Syst Sci 32:375–385
Chaari T, Chaabane S, Loukil T, Loukil D (2011) A genetic algorithm for robust hybrid flow shop scheduling. Int J Comput Integr Manuf 24:821–833
Tseng L, Lin Y (2010) A hybrid genetic algorithm for no-wait flow-shop scheduling problem. Int J Prod Econ 128:144–152
Jarboui B, Edadly M, Siarry P (2011) A hybrid genetic algorithm for solving no-wait flow-shop scheduling problems. Int J Adv Manuf Technol 54:1129–1143
Huang K, (2010) Hybrid genetic algorithms for flow-shop scheduling with synchronous material movement. Computer and industrial engineering (CIE), 40th international conference: 1–6
Li X, Wang Y, Wu C (2004) Heuristic algorithms for large flow-shop scheduling problems. Intell Control Autom 4:2999–3003
Laha D, Chakraborty UK (2007) An efficient stochastic hybrid heuristic for flow-shop scheduling. Eng Appl Artif Intell 20:851–856
Araújo DC, Nagano MS New heuristics for the no-wait flow shop with sequence-dependent setup times problem. Journal of the Brazilian Society of Mechanical Sciences and Engineering, http://dx.doi.org/10.1007/s40430-013-0064-4
Nagano MS, da Silva AA, Nogueira Lorena LA (2012) A new evolutionary clustering search for a no-wait flow shop problem with set-up times. Eng Appl Artif Intell 25:1114–1120
Moccellin JV, Nagano MS (2011) Heuristic for flow shop sequencing with separated and sequence-independent setup times. J Braz Soc Mech Sci Eng 33:74–78
Sheibani K (2010) A fuzzy greedy heuristic for permutation flow-shop scheduling. J Oper Res Soc 61:813–818
Ho W, Ji P (2003) Component scheduling for chip shooter machines: a hybrid genetic algorithm approach. Comput Oper Res 30:2175–2189
Ho W, Ji P (2004) A hybrid genetic algorithm for component sequencing and feeder arrangement. J Intell Manuf 15:307–315
Goldberg DE (1989) Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley, New York
Gen M, Cheng R (1997) Genetic Algorithms and Engineering Design. Wiley, New York
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Mirabi, M. A novel hybrid genetic algorithm to solve the sequence-dependent permutation flow-shop scheduling problem. Int J Adv Manuf Technol 71, 429–437 (2014). https://doi.org/10.1007/s00170-013-5489-5
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DOI: https://doi.org/10.1007/s00170-013-5489-5