Comparison of Different Approaches to the Cutting Plan Scheduling
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References
Bober, P (2007), “Optimization of cutting plans for more machines by searching of solution tree”, Journal “Quality Innovation Prosperity”, vol. 11, no. 2, p. 9-17 (In Slovak).
Bober, P (2008), “Optimization of Cutting Plans Using Genetic Algorithms”, Journal “Quality Innovation Prosperity”, vol. 12, no. 2, p. 1-10, (In Slovak).
Bubeník, P. (2004), “A scheduling system for minimizing the cost of productions”, Strojniški Vestnik - Journal of Mechanical Engineering, vol. 50, no. 5, ISSN 0039-2480, p. 291-297.
Cal'egaria P., Guideca, F., Kuonena, P., Nielsen, F. (2001), “Combinatorial optimization algorithms for radio network planning”, Theoretical Computer Science 263, p. 235–245.
Dhaenens, C., Lemesre, J., Talbi, E.G. (2010), “K-PPM: A new exact method to solve multi-objective combinatorial optimization problems”, European Journal of Operational Research, vol. 200, no. 1, p. 45-53, doi:10.1016/j.ejor.2008.12.034.
Duque, T., Goldberg, D. E., Sastry, K. (2008), “Enhancing the Efficiency of the ECGA”, TR No. 2008006, Retrieved on 3.11.2010 from http://www.illigal.uiuc.edu/pub/papers/IlliGALs/2008006.pdf.
Fabian, M., Spišák, E., Šeminský, J., Dovica, M. (2009), “Anticipation of Cutting Surface Quality from Pre-Set CAM Parameters”, Ovidius University Annual Scientific Journal, vol. 11, no. 1, p. 19-24.
Goldberg, D. E. (1989), Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, ISBN 0-201-15767-5.
Golomb, S. W., Baumert, L. D. (1965), “Backtrack Programming”, Jornal of the. ACM, vol. 12, no. 4, p. 516-524, DOI: 10.1145/321296.321300.
Grossmann, I. E., Heever, S. A., Harjunkoski, I. (2002), “Discrete Optimization Methods and their Role in the Integration of Planning and Scheduling”, AIChE Symposium Series, no. 326, vol. 98, p. 150-168.
Gutin, G., Vainshtein, A., Yeo, A. (2003), “Domination analysis of combinatorial optimization problems”. Discrete Applied Mathematics, vol. 129, no. 2-3, p. 513-520, DOI: 10.1016/S0166-218X(03)00359-7.
Hua, Q-S., Wang, Y., Yu, D., Lau, F. C. M. (2010), “Dynamic programming based algorithms for set multicover and multiset multicover problems”. Theoretical Computer Science, vol. 411, no. 26-28, p. 2467-2474, DOI: 10.1016/j.tcs.2010.02.016.
Jaszkiewicz, A. (2002), “Genetic local search for multi-objective combinatorial optimization”, European Journal of Operational Research, vol. 137, no. 1, p. 50-71, DOI: 10.1016/S0377-2217(01)00104-7.
Pentico, D. W. (2007), “Assignment problems: A golden anniversary survey”, European Journal of Operational Research, vol. 176, no. 2, p, 774-792, DOI: 10.1016/j.eor.2005.09.014.
Rajagopalan, S., Vazirani, V. V. (1993), “Primal-dual RNC approximation algorithms for (multi)-set (multi)-cover and covering integer programs”. In SFCS '93 Proceedings of the 1993 IEEE 34th Annual Foundations of Computer Science, Washington, DC, p. 322 – 331, DOI: 10.1109/SFCS.1993.366855.
Sergienko, I. V., Hulianytskyi, L. F., Sirenko, S. I. (2009), “Classification of applied methods of combinatorial optimization”, Cybernetics and Systems Analysis, vol. 45, no. 5, p. 732-741.
Slak, A., Tav?ar, J., Duhovnik, J. (2011), “Application of Genetic Algorithm into Multicriteria Batch Manufacturing Scheduling”, Strojniški vestnik - Journal of Mechanical Engineering, vol. 57, no. 2, p. 110-124, DOI:10.5545/sv-jme.2010.122.
Teghem, J., Tuyttens, D., Ulungu, E. L. (2000), “An interactive heuristic method for multi-objective combinatorial optimization”, Computers & Operations Research, vol. 27, no. 7-8, p. 621-634, DOI: 10.1016/S0305-0548(99)00109-4.
Zalzala, A. M. S., Fleming, P. J. (editors) (1997), Genetic algorithms in engineering systems, London: Institution of Electrical Engineers, ISBN 0 85296 902 3.
Zhang, H., Ishikawa, M. (2004), “A solution to combinatorial optimization with time-varying parameters by a hybrid genetic algorithm”, in International Congress Series, vol. 1269, Brain-Inspired IT I. Invited papers of the 1st Meeting entitled Brain IT 2004, August 2004, p. 149-152, DOI: 10.1016/j.ics.2004.05.019.
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