GA-based solutions comparison for storage strategies optimization for an automated warehouse

ISDA 2009 - 9th International Conference on Intelligent Systems Design and Applications

Volumn , Issue , 2009, Pages 976-981

  Colla, Valentina ^a   Nastasi, Gianluca ^a   Matarese, Nicola ^a   Reyneri, Leonardo M ^b  

^a SCUOLA SUPERIORE SANT ANNA   (Italy)

^b POLITECNICO DI TORINO   (Italy)

Author keywords

Genetic algorithms; Logistic; Multi objective optimisation; Warehouse

Indexed keywords

AUTOMATED WAREHOUSE; CHROMOSOME STRUCTURE; CROSSOVER AND MUTATION; MULTIOBJECTIVE OPTIMISATION; OBJECTIVE FUNCTIONS; STEEL-MAKING INDUSTRIES; STRENGTH PARETO GENETIC ALGORITHMS; WEIGHTING FUNCTIONS;

FUZZY LOGIC; GENETIC ALGORITHMS; INTELLIGENT SYSTEMS; MATHEMATICAL OPERATORS; WAREHOUSES;

MULTIOBJECTIVE OPTIMIZATION;

EID: 77949494057     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISDA.2009.201     Document Type: Conference Paper

References (25)

1. J. van den Berg and W. Zijm, "Models for warehouse management: Classification and examples," Internationa Journal of Production Economics, vol. 59, pp. 519-528.
2. M. Pang, G. He, and L. Xie, "Optimal number and sites of regional logistics centers by genetic algorithm and fuzzy c-mean clustering," International Conference on Service Systems and Service Management, 2007.
3. L. Taoshen and W. Jingli, "An improved genetic algorithm on logistics delivery in e-business," in Proceedings of the Third International Conference on Natural Computation, 2007, pp. 765-769.
4. L. Meijuan, C. Xuebo, and Z. Meifeng, "Optimal scheduling approach of storage/retrieval equipments based on genetic algorithm," IEEE Intelligent Control and Automation, vol. 1, pp. 3345-3348, 2006.
5. P. Poulos, G. Rigatos, S. Tzafestas, and A. Koukos, "A pareto-optimal genetic algorithm for warehouse multi-objective optimization," Engineering Applications of Artificial Intelligence, vol. 14, pp. 737-749, 2001.
6. T. Imai, "Production and technology of iron and steel in japan during 1998," ISIJ International, vol. 39, pp. 509-523, 1999.
7. V. Colla, G. Nastasi, N. Matarese, and A. Ucci, "Simulation of an automated warehouse for steel tubes," in Proceedings of the 10th International Conference on Computer Modeling and Simulation. Los Alamitos, CA, USA: IEEE Computer Society, 2008, pp. 150-155.
8. E. Krauth, H. Moonen, V. Popova, and M. Schut, "Key performance indicators in logistics service provision - a literature review and framework," in Proceedings of the European Operations Management Association International Conference on Operations and Global Competitiveness. EUROMA2005, 2005.
9. P. Ngatchou, A. Zarei, and M. El-Sharkawi, "Pareto multi objective optimization," in Intelligent Systems Application to Power Systems, 2005. Proceedings of the 13th International Conference on, Nov. 2005, pp. 84-91.
10. J. Gu, M. Goetschalckx, and L. McGinnis, "Research on warehouse operation: A comprehensive review," European Journal of Operational Research, vol. 177, pp. 1-21, 2007.
11. J. Holland, "Adaptation in natural and artificial systems," MIT Press, 1975.
12. H. Aytug, M. Khouja, and F. E. Vergara, "Use of genetic algorithms to solve production and operations management problems: a review," International Journal of Production Research, vol. 41, no. 17, pp. 3955 - 4009, November 2003.
13. B. Can, A. Beham, and C. Heavey, "A comparative study of genetic algorithm components in simulation-based optimisation," in Proceedings of the 40th Conference on Winter Simulation, 2008, pp. 1829-1837.
14. C. M. Fonseca and P. J. Fleming, "Genetic algorithms for multiobjective optimization: Formulation, discussion and generalization," in Genetic Algorithms: Proceedings of the Fifth International Conference. Morgan Kaufmann, 1993, pp. 416-423.
15. H. Pierreval and L. Tautou, "Using evolutionary algorithms and simulation for the optimization of manufacturing systems," IIE Transactions, vol. 29, no. 3, pp. 181-189, 1997.
16. E. Zitzler, K. Deb, and L. Thiele, "Multiobjective evolutionary algorithms; empirical results," Evolutionary Computation, vol. 8, no. 2, pp. 149-172, 2000.
17. D. Jones, S. Mirrazavi, and M. Tamiz, "Multi-objective metaheuristics - an overview of the current state-of-the-art," European Journal of Operational Research, vol. 137, no. 1, pp. 1-9, Feb. 2002.
18. C. A. C. Coello, "A comprehensive survey of evolutionary-based multiobjective optimization techniques," Knowledge and Information Systems, vol. 1, pp. 269-308, 1998.
19. A. Konak, D. W. Coit, and A. E. Smith, "Multi-objective optimization using genetic algorithms: A tutorial," Reliability Engineering & System Safety, vol. 91, no. 9, pp. 992-1007, September 2006.
20. C. M. Fonseca and P. J. Fleming, "An overview of evolutionary algorithms in multiobjective optimization," Evolutionary Computation, vol. 3, pp. 1-16, 1995.
21. M. Farina and P. Amato, Fuzzy optimality and evolutionary multiobjective optimization, ser. Lecture Notes in Computer Science. Springer, 2003, vol. 2632.
22. L. Zadeh, "Fuzzy sets," Information and Control, vol. 8, pp. 338-353, 1965.
23. E. Zitzler and L. Thiele, "An evolutionary algorithm for multiobjective optimization: The strength pareto approach," 1998.
24. -, "Multiobjective evolutionary algorithms: A comparative case study and the strength pareto approach," 1999.
25. M. Abido, "Environmental/economic power dispatch using multiobjective evolutionary algorithms," Power Systems, IEEE Transactions on, vol. 18, no. 4, pp. 1529-1537, Nov. 2003.