\ Global Optimizasyon

Global Optimizasyon

Araştırma grubumuz, özellikle içbükey olmayan kısıtsız ve kısıtlı global optimizasyon problemlerinde böl ve yönet prensiplerini kullanan metotlar geliştirmektedir. Metasezgisel çalışmaların yanında aralık matematiğini içeren bütünsel yaklaşımlar, kısıtlı, kısıtsız, karmaşık tam sayılı global optimizasyon problemleri için geliştirilmiştir.

Araştırma Grubu Üyeleri

  • Prof. Dr. Linet Özdamar (Yeditepe Ü.)
  • Prof. Dr. Melek Başak Demirhan (Yeditepe Ü.)
  • Yard. Doç. Dr. Esin Onbaşıoğlu (Yeditepe Ü.)
  • Prof. Tibor Csendes (Szeged University, Hungary)
  • Prof. Martine Ceberio (University of Texas El Paso, USA)
  • Prof. Arun Kumar (RMIT, Melbourne, Australia)

Tez Öğrencileri

  • Levent Helvacıoğlu (Yüksek Lisans, Yeditepe Ü.)
  • Prof. Dr. Şevket İlker Birbil  (Yüksek Lisans, Yeditepe Ü., Sabancı Üniversitesi)
  • Dr. Chandra S. Pedamallu (Doktora, Nanyang Tech. Singapore, MIT-Harvard Dana-Farber Cancer Institute, USA)
  • Prof. Dr. Tomas Vinkó (Doktora, Szeged University-Hungary, Croatia)
  • Prof. Yong Wu (Doktora, Nanyang Tech. - Singapore, Griffith University, Australia)
  • Biket Ergüneş (Doktora, Yeditepe Ü.)
  • Nur Gülcan (Doktora, Yeditepe Ü.)

Projeler

Yayınlar

  • B. Ergunes, L. Ozdamar, O. Demir and N. Gülcan, “Hierarchical variable subdivision rules for the MINLP”, to appear in Int. J. of Operations Research.

  • B. Ergünes, L. Özdamar, N. Gülcan, and O. Demir, “Interval partitioning methods for mixed integer nonlinear problems”, in Engineering Optimization IV, ed. A. Araujo et al., pp 63-67, CRC Press, Sep 2014.

  • C.S. Pedamallu, L. Özdamar, “Solving kinematics problems by efficient interval partitioning”, Optimization and Engineering, Volume 12(3), 459-476, 2011.

  • C. S. Pedamallu, L. Ozdamar, A Symbolic Interval Inference Approach for Constraint Satisfaction: Implementation on Kinematics Applications, International Journal of Operations Research, 8 (2), 127-149, 2010.
  • L. Özdamar, C. S. Pedamallu, “New Simulated Annealing Algorithms for Constrained Optimization”, 27 (3), 347-367, Asia Pacific Journal of Operations Research, 2010, DOI No: 10.1142/S0217595910002740.

  • C. S. Pedamallu, L. Özdamar, M. Ceberio, “Efficient interval partitioning-local search collaboration for constraint satisfaction”, Computers & Operations Research, 35, 1412 – 1435, 2008.

  • C. S. Pedamallu, L. Özdamar, “Investigating a Hybrid Simulated Annealing and local search algorithm for Constrained Optimization”, European Journal of Operations Research, 185, 1230-1245, 2008.

  • C. S. Pedamallu, L. Özdamar, T. Csendes, T. Vinkó, “Efficient interval partitioning for global optimisation”, JOGO, 42, 369-384, 2008.

  • C. S. Pedamallu, L. Özdamar, T. Csendes, “Symbolic Interval Inference Approach for Subdivision Direction Selection in Interval Partitioning Algorithms”, J. of Global Optimization, 37 (2), 177-194, 2007.

  • C. S. Pedamallu, L. Özdamar, “Simulated Annealing, Interval Partitioning and Local Search Collaboration in Constrained Global Optimization”, Springer Natural Computing Series: Eds. Z. Michalewicz and P. Siarry, Advances in Metaheuristics for Hard Optimization, Springer-Verlag, 2007.

  • C. S. Pedamallu, L. Özdamar, “A collaborative solution Methodology for Inverse position problem”. In: Global Optimization: Scientific and Engineering Case Studies, Series: Nonconvex Optimization and Its Applications, Vol. 85 ed: J. Pinter, Springer, The Netherlands, 2006.

  • C. S. Pedamallu, L. Özdamar, Csendes T., “Interval partitioning approach for continuous constrained optimisation”, to appear in Models and Algorithms for Global Optimization, Springer series on Nonconvex Optimization and its Applications, eds. A. Torn and J. Zilinskas, 2006.

  • Y. Wu, L. Ozdamar, A. Kumar, Parallel triangulated partitioning for black box optimization. In:  Global Optimization: Scientific and Engineering Case Studies, Series: Nonconvex Optimization and Its Applications, Vol. 85, ed: J. Pinter, Springer, The Netherlands.

  • Y. Wu, L. Özdamar, A. Kumar, “TRIOPT: A triangulation based partitioning algorithm for global optimization”, Journal of Computational and Applied Mathematics, 177(1), 35-53, 2005.

  • L. Özdamar, M. Demirhan, E. Onbasioglu, Pre-search Screening: A Technique to Improve Search Efficiency in Global Optimization, Frontiers in Global Optimization, pp. 437-457, Kluwer Academic Pub., 2004, The Netherlands.

  • E. Onbasioglu, L. Özdamar, “Optimization of Data Distribution and Processor Allocation Problem Using Simulated Annealing”, The Journal of Supercomputing, 25, 237-253, 2003. M. Demirhan, A. Özpinar, L. Özdamar, Performance evaluation of spatial interpolation methods in the presence of noise, Int. J. on Remote Sensing, 24(6), 1237-1258, 2002.

  • E. Onbasioglu, L. Özdamar, “Parallel Simulated Annealing in Global Optimization”, Journal of Global Optimization, 19(1), 27-50, 2001.

  • L. Özdamar, M. Demirhan, “Comparison of Partition Evaluation Measures in an Adaptive Partitioning Algorithm for Global Optimization”,  Fuzzy Sets and Systems, 117/1,  47-60, 2001.

  • L. Özdamar, M. Demirhan, “Experiments with new probabilistic search methods in global optimization”, Computers and Operations Research, 27, 841-865,  2000.

  • M. Demirhan, L. Özdamar, “A note on the use of a fuzzy approach in adaptive partitioning algorithms for global optimization”, IEEE Transactions on Fuzzy Systems, 7 (4), 468-475, 1999.

  • M. Demirhan, L. Özdamar, L. Helvacioglu, S. I. Birbil, “FRACTOP: A Geometric partitioning metaheuristic for global optimization”, Journal of Global Optimization, 14, 415-436, 1999.

global optimization research group

Yeditepe Üniversitesi, Endüstri ve Sistem Mühendisliği
26 Ağustos Yerleşimi, Kayışdağı Cad. 34755 Ataşehir, İstanbul

(216) 578 04 50 info@sye.yeditepe.edu.tr