Job scheduling with forbidden setups and two objectives using genetic algorithms and penalties

Central European Journal of Operations Research

Volumn 19, Issue 3, 2011, Pages 285-298

  Hentsch, Karsten ^a   Köchel, Peter ^a  

^a CHEMNITZ UNIVERSITY OF TECHNOLOGY   (Germany)

Author keywords

Constraints; Forbidden setups; Genetic algorithm; Penalties; Scheduling

Indexed keywords

EID: 79960615049     PISSN: 1435246X     EISSN: 16139178     Source Type: Journal    
DOI: 10.1007/s10100-010-0162-7     Document Type: Article

References (19)

1. Brucker P (2007) Scheduling algorithms. Springer, Berlin, Heidelberg.
2. Chen CL, Xiao CL, Feng D, Shao HH (2002) Optimal shortterm scheduling of multiproduct single-stage batch plants with parallel lines. Ind Eng Chem Res 41: 1249-1260. doi: 10. 1021/ie010465d.
3. Cicirello VA (2006) Non-wrapping order crossover: an order preserving crossover operator that respects absolute position. Proceedings of the 8th annual conference on Genetic and evolutionary computation, ACM, New York, pp 1125-1132. doi: 10. 1145/1143997. 1144177.
4. Coello Coello CA (1999) A survey of constraint handling techniques used with evolutionary algorithms. Technical Report, Lania-RI-99-04, Laboratorio Nacional de Inforḿdftica Avanzada, Xalapa, Veracruz, México.
5. Coello Coello CA, Lamont GB, van Veldhuizen DA (2007) Evolutionary algorithms for solving multi-objective problems. Springer, New York.
6. Kämpf M (2009) Software-Framework zur Simulationsbasierten Optimierung mit Anwendung auf Produktions- und Lagerhaltungssysteme. Dissertation, Chemnitz University of Technology.
7. Köchel P, Nieländer NU (2002) Kanban optimization by simulation and evolution. Prod Plan Control 13: 725-734. doi: 10. 1080/0953728031000057334.
8. Köchel P, Nieländer NU (2005) Simulation-based optimisation of multi-echelon inventory systems. Int J Prod Econ 93-94: 505-513. doi: 10. 1016/j. ijpe. 2004. 06. 046.
9. Kopanos GM, Lanez JM, Puigjaner L (2009) An efficient mixed-integer linear programming scheduling framework for addressing sequence-dependent setup issues in batch plants. Ind Eng Chem Res 48: 6346-6357. doi: 10. 1021/ie801127t.
10. Nieländer NU (2009) CHEOPS: Das Chemnitzer hybrid-evolutionäre Optimierungssystem. Dissertation, Chemnitz University of Technology.
11. Relvas S, Matos HA, Barbosa-Póvoa APFD, Fialho J (2007) Reactive scheduling framework for a multiproduct pipeline with inventory management. Ind Eng Chem Res 46: 5659-5672. doi: 10. 1021/ie070214q.
12. Richardson JT, Palmer MR, Liepins G, Hilliard M (1989) Some guidelines for genetic algorithms with penalty functions. In: Schaffer JD (ed) Proceedings of the 3rd international conference on genetic algorithms. Morgan Kaufmann, San Francisco, pp 191-197.
13. Runarsson TP, Xin Yao (2000) Stochastic ranking for constrained evolutionary optimization. IEEE Trans Evol Comput 4: 284-294. doi: 10. 1109/4235. 873238.
14. Smith AE, Coit DW (1997) Constraint handling techniques-penalty functions. In: Bäck T, Fogel DB, Michalewicz Z (eds) Handbook of evolutionary computation. IOP Publishing Ltd., Bristol, UK. ISBN: 0750303921.
15. Smith AE, Tate DM (1993) Genetic optimization using a penalty function. In: Forrest S (ed) Proceedings of the 5th international conference on genetic algorithms, Morgan Kaufmann, San Francisco, pp 499-503.
16. T'kindt V, Billaut JC (2006) Multicriteria scheduling. Springer, Berlin, Heidelberg.
17. Xhafa F, Abraham A (2008) Metaheuristics for scheduling in industrial and manufacturing applications. Springer, Berlin, Heidelberg.
18. Zitzler E, Thiele L (1999) Multiobjective evolutionary algorithms: a comparative study and the strength pareto approach. IEEE Trans Evol Comput 3: 257-271.
19. Zitzler E, Thiele L, Laumanns M, Fonseca CM, da Fonseca VG (2003) Performance assessment of multiobjective optimizers: an analysis and review. IEEE Trans Evol Comput 7: 117-132.