Glass container production scheduling through hybrid multi-population based evolutionary algorithm

Applied Soft Computing Journal

Volumn 13, Issue 3, 2013, Pages 1352-1364

  Motta Toledo, Claudio Fabiano ^a   Da Silva Arantes, Márcio ^a   De Oliveira, Renato Resende Ribeiro ^b   Almada Lobo, Bernardo ^c  

^a UNIVERSITY OF SÃO PAULO   (Brazil)

^b FEDERAL UNIVERSITY OF LAVRAS   (Brazil)

^c UNIVERSITY OF PORTO   (Portugal)

Author keywords

Cross fertilization; Lotsizing and scheduling; Multi population; Production losses; Ternary tree

Indexed keywords

CONTAINERS; COST EFFECTIVENESS; GENETIC ALGORITHMS; GLASS; GLASS INDUSTRY; PRODUCTION CONTROL; SCHEDULING; SIMULATED ANNEALING; STRUCTURED PROGRAMMING;

CROSS FERTILIZATION; LOT-SIZING AND SCHEDULING; MULTI POPULATION; PRODUCTION LOSS; TERNARY TREE;

EVOLUTIONARY ALGORITHMS;

EID: 84881223802     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2012.03.074     Document Type: Article

References (24)

1. R. Jans, Solving lot-sizing problems on parallel identical machines using symmetry-breaking constraints, INFORMS Journal on Computing 21 (1)(2009) 123-136.
2. A. Clark, B. Almada-Lobo, C. Almeder, Lot sizing and scheduling: industrial extensions and research opportunities, International Journal of Production Research 49 (9) (2011) 2457-2461.
3. B. Almada-Lobo, D. Klabjan, M.A. Carravilla, J.F. Oliveira, Multiple machine continuous setup lotsizing with sequence-dependent setups, Computational Optimization and Applications 47 (3) (2010) 529-552.
4. R. Jans, Z. Degraeve, Meta-heuristics for dynamic lot sizing: a review and comparison of solution approaches, European Journal of Operational Research 177 (2007)1855-1875.
5. H.G. Goren, S. Tunali, R. Jans, A review of applications of genetic algorithms in lot sizing, Journal of Intelligent Manufacturing 21 (4) (2010) 575-590.
6. M. Khouja, Z. Michalewicz, M. Wilmot, The use of genetic algorithms to solve the economic lot size scheduling problem, European Journal of Operational Research 110 (3) (1998) 509-524.
7. D.E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, Reading, MA, 1989.
8. Z. Michalewicz, Genetic Algorithms + Data Structure = Evolution Programs, Springer-Verlag, 1996.
9. M. Gen, L. Lin, H. Zhang, Evolutionary techniques for optimization problems in integrated manufacturing system: state-of-the-art-survey, Computers & Industrial Engineering 56 (3) (2009) 779-808.
10. G.R. Raidl, A unified view on hybrid metaheuristics. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4030 LNCS, 2006, 1-12.
11. S. Guan, M. Nakamura, T. Shikanai, T. Okazaki, Resource assignment and scheduling based on a two-phase metaheuristic for cropping system, Computers and Electronics in Agriculture 66 (2) (2009) 181-190.
12. X. Li, X. Shao, L. Gao, W. Qian, An effective hybrid algorithm for integrated process planning and scheduling, International Journal of Production Economics 126 (2)(2010)289-298.
13. I. Fister, M. Mernik, B. Filipia, A hybrid self-adaptive evolutionary algorithm for marker optimization in the clothing industry, Applied Soft Computing 10 (2) (2010)409-422.
14. A. Rossi, E. Boschi, A hybrid heuristic to solve the parallel machines job-shop scheduling problem, Advances in Engineering Software 40 (2) (2009) 118-127.
15. J.C. Vidal, M. Mucientes, A. Bugara, M. Lama, Machine scheduling in custom furniture industry through neuro-evolutionary hybridization, Applied Soft Computing 11 (2) (2011) 1600-1613.
16. X. Li, L. Gao, W. Li, Application of game theory based hybrid algorithm for multi-objective integrated process planning and scheduling, Expert Systems with Applications 39 (1) (2012) 288-297.
17. S. Fallah-Jamshidi, N. Karimi, M. Zandieh, A hybrid multi-objective genetic algorithm for planning order release date in two-level assembly system with random lead times, Expert Systems with Applications 38 (11) (2011) 13549-13554.
18. Hsueh-Chien Cheng, Tsung-Che Chiang, Li-Chen Fu, A two-stage hybrid memetic algorithm for multiobjective job shop scheduling, Expert Systems with Applications 38 (9) (2011) 10983-10998.
19. P.M. Franca, A.S. Mendes, P. Moscato, A memetic algorithm for the total tardiness single machine scheduling problem, European Journal of Operational Research 132 (2001) 224-242.
20. P.M. Franca, J.N.D. Gupta, A.S. Mendes, P. Moscato, K.J. Veltinky, Evolutionary algorithms for scheduling a flowshop manufacturing cell with sequence dependent family setups, Computers & Industrial Engineering 48 (3) (2005) 491-506.
21. R. Moghaddam, Y. Kanani, R. Cheraghalizadeh, A genetic algorithm and memetic algorithm to sequencing and scheduling of cellular manufacturing systems, International Journal of Management Science and Engineering Management 3 (2) (2008) 119-130.
22. C.F.M. Toledo, P.M. Franca, A. Kimms, R. Morabito, A multi-population genetic algorithm approach to solve the synchronized and integrated two-level lot sizing and scheduling problem, International Journal of Production Research 47 (2009)3097-3119.
23. A. Drexl, A. Kimms, Lot-sizing and scheduling-survey and extensions, European Journal of Operational Research 99 (1997) 221-235.
24. S. Kirkpatrick, CD. Gelatt, M.P. Vecchi, Optimization by simulated annealing, Science 220 (1983) 671-680.