Abstract
The Blocking Job Shop Scheduling (BJSS) is an NP-hard scheduling problem. It is obtained from the classical job shop scheduling problem by replacing the infinite buffer capacity constraint by a zero buffer capacity which introduces the blocking constraint. This constraint affects deeply the ability of meta-heuristics to find good solutions due to the low ratio of feasible to explored solutions. In this paper, we discuss the parallelization of the Tabu Search algorithm (TS) which represents one of the most widely used heuristics. Applying the classical TS neighborhood to the BJSS problem produces infeasible solutions in 98% of cases which leads to waste a valuable time in exploring infeasible solutions. For this reason, the use of a feasibility recovery strategy is unavoidable; however, the recovery step slows down considerably the TS algorithm. Therefore, incurring a huge time to explore a small area in the search space. To overcome this drawback and to accelerate the TS algorithm, we propose in this paper parallel multi-start TS approaches where several processes explore simultaneously the search space. Our parallelization exploits a cluster-based architecture with 512 CPU-cores. The obtained results show the positive impact of our proposed parallelization on the solution quality. Moreover, combining both the parallelism and the recovery strategy allowed us to improve the best result in the literature for a large number of known benchmarks.
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References
AitZai A, Benmedjdoub B, Boudhar M (2012) A branch and bound and parallel genetic algorithm for the job shop scheduling problem with blocking. Int J Oper Res 14(3):343–365
Crainic TG, Toulouse M, Gendreau M (1997) Toward a taxonomy of parallel tabu search heuristics. INFORMS J Comput 9(1):61–72
Dabah A, Bendjoudi A, AitZai A (2016a) Efficient parallel b&b method for the blocking job shop scheduling problem. In: 2016 International conference on high performance computing & simulation (HPCS), IEEE, pp 784–791
Dabah A, Bendjoudi A, AitZai A, El-Baz D, Taboudjemat NN (2016b) Multi and many-core parallel b&b approaches for the blocking job shop scheduling problem. In: 2016 International conference on high performance computing & simulation (HPCS), IEEE, pp 705–712
Dabah A, El-Baz D, Aitzai A, et al. (2016c) Gpu-based two level parallel b&b for the blocking job shop scheduling problem. In: 2016 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), IEEE, pp 747–755
Dabah A, Bendjoudi A, AitZai A (2017) An efficient tabu search neighborhood based on reconstruction strategy to solve the blocking job shop scheduling problem. J Ind Manag Optim 13(4):2015–2031
Dabah A, Bendjoudi A, AitZai A, El-Baz D, Taboudjemat NN (2018) Hybrid multi-core cpu and gpu-based b&b approaches for the blocking job shop scheduling problem. J Parallel Distrib. Comput. 117:73–86
Glover F (1986) Future paths for integer programming and links to artificial intelligence. Comput Oper Res 13(5):533–549
Glover F (1989) Tabu search-part i. ORSA J Comput 1(3):190–206
Glover F (1990) Tabu search-part ii. ORSA J Comput 2(1):4–32
Gröflin H, Klinkert A (2009) A new neighborhood and tabu search for the blocking job shop. Discrete Appl Math 157(17):3643–3655
Gröflin H, Pham DN, Reinhard B (2011) The flexible blocking job shop with transfer and set-up times. J Comb Optim 22(2):121–144
Hall NG, Sriskandarajah C (1996) A survey of machine scheduling problems with blocking and no-wait in process. Oper Res 44(3):510–525
Lawrence S (1984) Resource constrained project scheduling: an experimental investigation of heuristic scheduling techniques (supplement). Graduate School of Industrial Administration
Mascis A, Pacciarelli D (2002) Job-shop scheduling with blocking and no-wait constraints. Eur J Oper Res 143(3):498–517
Mati Y, Xie X (2011) Multiresource shop scheduling with resource flexibility and blocking. IEEE Trans Autom Sci Eng 8(1):175–189
Mati Y, Rezg N, Xie X (2001) A taboo search approach for deadlock-free scheduling of automated manufacturing systems. J Intell Manuf 12(5–6):535–552
Meloni C, Pacciarelli D, Pranzo M (2004) A rollout metaheuristic for job shop scheduling problems. Anna Oper Res 131(1–4):215–235
Oddi A, Rasconi R, Cesta A, Smith SF (2012) Iterative improvement algorithms for the blocking job shop. In: International conference on automated planningand scheduling (ICAPS 2012). AAAI, pp 199–206
Pham Dg, Andreas K (2008) Surgical case scheduling as a generalized job shop scheduling problem. Eur J Oper Res 185(3):1011–1025
Pranzo M, Pacciarelli D (2015) An iterated greedy metaheuristic for the blocking job shop scheduling problem. J Heuristics 131:587–611
Roy B, Sussmann B (1964) Les problemes dordonnancement avec contraintes disjonctives. Note ds 9
Trienekens HWJM, de Bruin A (1992) Towards a taxonomy of parallel branch and bound algorithms
Van Laarhoven PJ, Aarts EH, Lenstra JK (1992) Job shop scheduling by simulated annealing. Operations research 40(1):113–125
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Dabah, A., Bendjoudi, A., AitZai, A. et al. Efficient parallel tabu search for the blocking job shop scheduling problem. Soft Comput 23, 13283–13295 (2019). https://doi.org/10.1007/s00500-019-03871-1
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DOI: https://doi.org/10.1007/s00500-019-03871-1