Abstract
In this paper, a hybrid algorithm combining particle swarm optimization (PSO) and tabu search (TS) is proposed to solve the job shop scheduling problem with fuzzy processing time. The object is to minimize the maximum fuzzy completion time, i.e., the fuzzy makespan. In the proposed algorithm, PSO performs the global search, i.e., the exploration phase, while TS conducts the local search, i.e., the exploitation process. The global best particle is used to direct other particles to optimal search space. Therefore, in the proposed algorithm, TS-based local search approach is applied to the global best particle to conduct find-grained exploitation. In order to share information among particles, one-point crossover operator is embedded in the hybrid algorithm. The proposed algorithm is tested on sets of the well-known benchmark instances. Through the analysis of experimental results, the highly effective performance of the proposed algorithm is shown against the best performing algorithms from the literature.
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References
Wang L, Zheng DZ (2002) A modified genetic algorithm for job shop scheduling. Int J Adv Manuf Technol 20:72–76
Kuroda M, Wang Z (1996) Fuzzy job shop scheduling. Int J Prod Econ 44(1):45–51
Sakawa M, Mori T (1999) An efficient genetic algorithm for job shop scheduling problems with fuzzy processing time and fuzzy due date. Comput Ind Eng 36(2):325–341
Sakawa M, Kubota R (2000) Fuzzy programming for multi-objective job shop scheduling with fuzzy processing time and fuzzy due date through genetic algorithm. Eur J Oper Res 120(2):393–407
Song XY, Zhu YL, Yin CW, Li FM (2006) Study on the combination of genetic algorithms and ant colony algorithms for solving fuzzy job shop scheduling. In: Proceedings of the IMACS multi-conferences on computational engineering in systems application. Beijing, pp 1904–1909
Wu CS, Li DC, Tsai TI (2006) Applying the fuzzy ranking method to the shifting bottleneck procedure to solve scheduling problems of uncertainty. Int J Adv Manuf Technol 31(1–2):98–106
Lei DM (2007) Pareto archive particle swarm optimization for multi-objective fuzzy job shop scheduling problems. Int J Adv Manuf Technol 37(1–2):157–165
Niu Q, Jiao B, Gu XS (2008) Particle swarm optimization combined with genetic operators for job shop scheduling problem with fuzzy processing time. Appl Math Comput 205:148–158
Tavakkoli-Moghaddam R, Safaei N, Kah MMO (2008) Accessing feasible space in a generalized job shop scheduling problem with the fuzzy processing times: a fuzzy-neural approach. J Oper Res Soc 59:431–442
Inés GR, Camino RV, Jorge P (2010) A genetic solution based on lexicographical goal programming for a multiobjective job shop with uncertainty. J Intell Manuf 21:65–73
Lei (2010) Solving fuzzy job shop scheduling problems using random key genetic algorithm. Int J Adv Manuf Technol 49:253–262
Niu Q, Zeng TT, Zhou Z (2011) A novel cultural algorithm based on differential evolution for hybrid flow shop scheduling problems with fuzzy processing time. Lect Notes Comput Sci 2011(7027/2011):121–132. doi:10.1007/978-3-642-24918-1_15
Hu YM, Yin MH, Li XT (2011) A novel objective function for job-shop scheduling problem with fuzzy processing time and fuzzy due date using differential evolution algorithm. Int J Adv Manuf Technol 56(9–12):1125–1138
Eberhart RC, Kennedy J (1995) A new optimizer using particle swarm theory. Proceedings of the Sixth International Symposium on Micro Machine and Human Science, Nagoya, Japan, 39–43. Piscataway: IEEE Service Center
Pan QK, Tasgetiren MF, Liang YC (2008) A discrete particle swarm optimization algorithm for the no-wait flowshop scheduling problem. Comput Oper Res 35(9):2807–2839
Liang JJ, Pan QK, Chen TJ, Wang L (2011) Solving the blocking flow shop scheduling problem by a dynamic multi-swarm particle swarm optimizer. Int J Adv Manuf Technol 55(5–8):755–762
Moslehi G, Mahnam M (2011) A Pareto approach to multi-objective flexible job-shop scheduling problem using particle swarm optimization and local search. Int J Prod Econ 129(1):14–22
Liao CJ, Tjandradjaja E, Chung TP (2012) An approach using particle swarm optimization and bottleneck heuristic to solve hybrid flow shop scheduling problem. Appl Soft Comput 12(6):1755–1764
Shiau DF, Huang YM (2012) A hybrid two-phase encoding particle swarm optimization for total weighted completion time minimization in proportionate flexible flow shop scheduling. Int J Adv Manuf Technol 58(1–4):339–357
Damodaran P, Rao AG, Mestry S (2012) Particle swarm optimization for scheduling batch processing machines in a permutation flowshop. Int J Adv Manuf Technol 2012. doi:10.1007/s00170-012-4037-z
Glover F (1990) Tabu search: a tutorial. Interfaces 20(4):74–94
Li JQ, Pan QK, Liang YC (2010) An effective hybrid tabu search algorithm for multi-objective flexible job shop scheduling problems. Comput Ind Eng 59(4):647–662
Li JQ, Pan QK, Suganthan PN, Chua TJ (2011) A hybrid tabu search algorithm with an efficient neighborhood structure for the flexible job shop scheduling problem. Int J Adv Manuf Technol 52(5–8):683–697
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Li, Jq., Pan, Yx. A hybrid discrete particle swarm optimization algorithm for solving fuzzy job shop scheduling problem. Int J Adv Manuf Technol 66, 583–596 (2013). https://doi.org/10.1007/s00170-012-4337-3
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DOI: https://doi.org/10.1007/s00170-012-4337-3