YAPAY BAĞIŞIKLIK SİSTEMİNİN ÇOKLU ETMEN BENZETİM ORTAMINDA REALİZE EDİLMESİ VE GEZGİN SATICI PROBLEMİNE UYGULANMASI
Öz
Kombinatoryal optimizasyon problemlerinin çözümü için geliştirilen birçok meta-sezgisel algoritmabulunmasına rağmen bu algoritmaları etmen tabanlı modelleme ortamında realize eden çalışmaların sayısı çokazdır. Özellikle Yapay Bağışıklık Sisteminin (YBS) dinamiklerini modelleyen algoritmaların adaptasyonyeteneğine sahip popülasyon tabanlı yaklaşımlar olması, YBS’nin etmen tabanlı modelleme ortamında gerçeğedaha yakın bir şekilde realize edilmesini sağlayacaktır. Bu amaçla ilk defa mevcut çalışmada, bir kombinatoryaloptimizasyon problemi olan gezgin satıcı probleminin (GSP) modellenmesi ve çözümü için yapay bağışıklıksistemi algoritmalarından klonal seçim algoritması çoklu etmen benzetim ortamında modellenmiş vealgoritmanın gösterdiği davranışın incelenmesi için farklı GSP setleri üzerinde benzetim deneylerigerçekleştirilmiştir. Etmen tabanlı modellerin geliştirilmesi ve benzetim testlerinin yapılabilmesi için Netlogoyazılımı kullanılmıştır. Ayrıca geleneksel klonal seçim algoritmasının performansını arttırmak için reseptördeğişim süreci ve çaprazlama mekanizması önerilen modele entegre edilmiş ve doğal oluşları daha gerçekçimodelleyebilen etmen tabanlı yaklaşımlar ile de etkin çözümler elde edilebileceği gösterilmiştir.
Anahtar Kelimeler
Etmen tabanlı modelleme ve benzetim yapay bağışıklık sistemi klonal seçim algoritması gezgin satıcı problemi.
Kaynakça
- De Castro, L. ve Von Zuben, F., “Learning and
- Optimization Using The Clonal Selection
- Principle”, Evolutionary Computation, Cilt 6,
- Sayı 3, 239-251, 2002.
- Gao, S., Dai, H., Yang, G. ve Tang, Z., “A Novel
- Clonal Selection Algorithm and Its Application to
- Traveling Salesman Problem”, IEICE Trans.
- Fundamentals, Cilt E90–A, No 10, 2007.
- Dai, H., Yang, Y. ve Li, C., “Improved Quantum
- Crossover Based Clonal Selection Algorithm”,
- Third International Conference on Intelligent
- Networks and Intelligent Systems, Shenyang -
- Çin, 366-369, 01-03 Kasım 2010.
- Dai, H., Yang, Y. ve Li, C., “Distance
- Maintaining Compact Quantum Crossover Based
- Clonal Selection Algorithm”, Journal of
- Convergence Information Technology, Cilt 5,
- No 10, 56-65, 2010.
- Machado, R.B., Boukerche, A., Sobral, J.B.M.,
- Juca, K.R.L. ve Notare, M.S.M.A., “A Hybrid
- Artificial Immune and Mobile Agent Intrusion
- Detection Based Model for Computer Network
- Operations”, 19th IEEE International Parallel
- and Distributed Processing Symposium,
- Denver – ABD, 04-08 Nisan 2005.
- Grilo, A., Caetano, A. ve Rosa, A., “Agent Based
- Artificial Immune System”, Genetic and
- Evolutionary Computation Congress (Proc.
- GECCO-01), San Francisco – ABD, Cilt LBP,
- -151, 07-11 Temmuz 2001.
- Ou, C.M. Wang, Y.T. ve Ou, C.R., “Intrusion
- Detection Systems Adapted From Agent-Based
- Artificial Immune Systems”, IEEE
- International Conference on Fuzzy Systems,
- Taipai – Tayvan, 115-122, 27-30 Haziran 2011.
- Mendao, M., Timmis, J., Andrews, P.S. ve
- Davies, M., “The Immune System in Pieces:
- Computational Lessons from Degeneracy in the
- Immune System”, IEEE Symposium on
- Foundations of Computational Intelligence,
- Havai, 394-400, 01-05 Nisan 2007.
- Sathyanath, S. ve Sahin, F., “Application of
- Artificial Immune System Based Intelligent Multi
- Agent Model to a Mine Detection Problem”,
- IEEE International Conference on Systems,
- Man and Cybernetics, Hammamet – Tunus, 06-
- Ekim 2002.
- Mamady, D., Tan, G., Toure, M.L. ve Alfawaer,
- Z.M., “An Artificial Immune System Based
- Multi-Agent Robotic Cooperation”, Novel
- Algorithms and Techniques in
- Telecommunications, Automation and
- Industrial Electronics, 60-67, 2008.
- Chingtham, T.S., Sahoo, G. ve Ghose, M.K., “An
- Artificial Immune System Model for Multi
- Agents Resource Sharing in Distributed
- Environments”, International Journal on
- Computer Sciences and Engineering, Cilt 2, No
- , 1813-1818, 2010.
- Singh, C.T. ve Nair, S.B., “An Artificial Immune
- System for a Multi-Agent Robotics System”,
- Word Academy of Science, Eng. and
- Technology, Cilt 11, Sayı 3, 6-9, 2005.
- Dasgupta, D. ve Nino, F., Immunological
- Computation: Theory and Applications,
- Auerbach Publications, 2008.
- Timmis. J., Hone, A., Stibor, T. ve Clark, E.,
- “Theoretical Advances in Artificial Immune
- Systems”, Theoretical Computer Science, Cilt
- , Sayı 1, 11-32, 2008.
- Dasgupta, D., “Information Processing
- Mechanisms of the Immune System”, New Ideas
- in Optimization, Corne, D., Dorigo, M. ve
- Glover, F., McGraw-Hill, ABD, 1999.
- De Castro, L. N. ve Timmis, J., Artificial
- Immune Systems: A New Computational
- Intelligence Approach, Springer, ABD, 2002.
- Macal, C.M. ve North, M.J.; “Agent-based
- Modeling and Simulation”, Winter Simulation
- Conference 2009, Austin – ABD, 86-98, 13-16
- Aralık 2009.
- Siebers, P.O. ve Aickelin, U., “Introduction to
- Multi Agent Simulation”, Encylopedia of
- Decision Making and Decision Support
- Technologies, Editör: Adam, F., Information
- Science Reference, ABD, 554-564, 2007.
- Siebers, P.O., “Lecture Notes”,
- http://www.cs.nott.ac.uk/~pos/index.html.
- Bradshaw, J.M., Software Agents, The MIT
- Press, ABD, 1997.
- Jennings, N., “On Agent-based Software
- Engineering”, Artificial Intelligence, Cilt 117,
- Sayı 2, 277-296, 2000.
- Pelta, D., Cruz C. ve Gonzalez, J.R., “A Study on
- Diversity and Cooperation in a Multiagent
- Strategy for Dynamic Optimization Problems”,
- International Journal of Intelligent Systems,
- Cilt 24, Sayı 7, 844–861, 2009.
- Terna P., “The epidemic of innovation – playing
- around with an agent-based model”, Economics
- of Innovation and New Technology, Cilt 18, No
- , 707–728, 2009.
- Sakellariou, I., Kefalas, P. ve Stamatopoulou, I.,
- “Enhancing NetLogo to Simulate BDI
- Communicating Agents”, SETN '08 Proceedings
- of the 5th Hellenic Conference on Artificial
- Intelligence: Theories, Models and App.,
- Syros, 263-275, 02-04,10, 2008.
- Tisue, S. ve Wilensky, U., “NetLogo: design and
- implementation of a multi-agent modeling
- environment”, Proceedings of Agent, Chicago –
- ABD, Ekim 2004.
- Somhom, S., Modares, A. ve Enkawa, T., “A
- Self-organizing Model for the Traveling
- Salesman Problem”, J. of the OR Society, Cilt
- , No 9, 919–928, 1997.
- Cochrane, E. M., ve Beasley, J. E., “The Coadaptive
- Neural Network Approach to the
- Euclidean Traveling Salesman Problem”, Neural
- Networks, Cilt 16,10, 1499–1525, 2003
Yıl 2012,
Cilt: 27 Sayı: 4, 0 - , 19.02.2013
Öz
Kaynakça
- De Castro, L. ve Von Zuben, F., “Learning and
- Optimization Using The Clonal Selection
- Principle”, Evolutionary Computation, Cilt 6,
- Sayı 3, 239-251, 2002.
- Gao, S., Dai, H., Yang, G. ve Tang, Z., “A Novel
- Clonal Selection Algorithm and Its Application to
- Traveling Salesman Problem”, IEICE Trans.
- Fundamentals, Cilt E90–A, No 10, 2007.
- Dai, H., Yang, Y. ve Li, C., “Improved Quantum
- Crossover Based Clonal Selection Algorithm”,
- Third International Conference on Intelligent
- Networks and Intelligent Systems, Shenyang -
- Çin, 366-369, 01-03 Kasım 2010.
- Dai, H., Yang, Y. ve Li, C., “Distance
- Maintaining Compact Quantum Crossover Based
- Clonal Selection Algorithm”, Journal of
- Convergence Information Technology, Cilt 5,
- No 10, 56-65, 2010.
- Machado, R.B., Boukerche, A., Sobral, J.B.M.,
- Juca, K.R.L. ve Notare, M.S.M.A., “A Hybrid
- Artificial Immune and Mobile Agent Intrusion
- Detection Based Model for Computer Network
- Operations”, 19th IEEE International Parallel
- and Distributed Processing Symposium,
- Denver – ABD, 04-08 Nisan 2005.
- Grilo, A., Caetano, A. ve Rosa, A., “Agent Based
- Artificial Immune System”, Genetic and
- Evolutionary Computation Congress (Proc.
- GECCO-01), San Francisco – ABD, Cilt LBP,
- -151, 07-11 Temmuz 2001.
- Ou, C.M. Wang, Y.T. ve Ou, C.R., “Intrusion
- Detection Systems Adapted From Agent-Based
- Artificial Immune Systems”, IEEE
- International Conference on Fuzzy Systems,
- Taipai – Tayvan, 115-122, 27-30 Haziran 2011.
- Mendao, M., Timmis, J., Andrews, P.S. ve
- Davies, M., “The Immune System in Pieces:
- Computational Lessons from Degeneracy in the
- Immune System”, IEEE Symposium on
- Foundations of Computational Intelligence,
- Havai, 394-400, 01-05 Nisan 2007.
- Sathyanath, S. ve Sahin, F., “Application of
- Artificial Immune System Based Intelligent Multi
- Agent Model to a Mine Detection Problem”,
- IEEE International Conference on Systems,
- Man and Cybernetics, Hammamet – Tunus, 06-
- Ekim 2002.
- Mamady, D., Tan, G., Toure, M.L. ve Alfawaer,
- Z.M., “An Artificial Immune System Based
- Multi-Agent Robotic Cooperation”, Novel
- Algorithms and Techniques in
- Telecommunications, Automation and
- Industrial Electronics, 60-67, 2008.
- Chingtham, T.S., Sahoo, G. ve Ghose, M.K., “An
- Artificial Immune System Model for Multi
- Agents Resource Sharing in Distributed
- Environments”, International Journal on
- Computer Sciences and Engineering, Cilt 2, No
- , 1813-1818, 2010.
- Singh, C.T. ve Nair, S.B., “An Artificial Immune
- System for a Multi-Agent Robotics System”,
- Word Academy of Science, Eng. and
- Technology, Cilt 11, Sayı 3, 6-9, 2005.
- Dasgupta, D. ve Nino, F., Immunological
- Computation: Theory and Applications,
- Auerbach Publications, 2008.
- Timmis. J., Hone, A., Stibor, T. ve Clark, E.,
- “Theoretical Advances in Artificial Immune
- Systems”, Theoretical Computer Science, Cilt
- , Sayı 1, 11-32, 2008.
- Dasgupta, D., “Information Processing
- Mechanisms of the Immune System”, New Ideas
- in Optimization, Corne, D., Dorigo, M. ve
- Glover, F., McGraw-Hill, ABD, 1999.
- De Castro, L. N. ve Timmis, J., Artificial
- Immune Systems: A New Computational
- Intelligence Approach, Springer, ABD, 2002.
- Macal, C.M. ve North, M.J.; “Agent-based
- Modeling and Simulation”, Winter Simulation
- Conference 2009, Austin – ABD, 86-98, 13-16
- Aralık 2009.
- Siebers, P.O. ve Aickelin, U., “Introduction to
- Multi Agent Simulation”, Encylopedia of
- Decision Making and Decision Support
- Technologies, Editör: Adam, F., Information
- Science Reference, ABD, 554-564, 2007.
- Siebers, P.O., “Lecture Notes”,
- http://www.cs.nott.ac.uk/~pos/index.html.
- Bradshaw, J.M., Software Agents, The MIT
- Press, ABD, 1997.
- Jennings, N., “On Agent-based Software
- Engineering”, Artificial Intelligence, Cilt 117,
- Sayı 2, 277-296, 2000.
- Pelta, D., Cruz C. ve Gonzalez, J.R., “A Study on
- Diversity and Cooperation in a Multiagent
- Strategy for Dynamic Optimization Problems”,
- International Journal of Intelligent Systems,
- Cilt 24, Sayı 7, 844–861, 2009.
- Terna P., “The epidemic of innovation – playing
- around with an agent-based model”, Economics
- of Innovation and New Technology, Cilt 18, No
- , 707–728, 2009.
- Sakellariou, I., Kefalas, P. ve Stamatopoulou, I.,
- “Enhancing NetLogo to Simulate BDI
- Communicating Agents”, SETN '08 Proceedings
- of the 5th Hellenic Conference on Artificial
- Intelligence: Theories, Models and App.,
- Syros, 263-275, 02-04,10, 2008.
- Tisue, S. ve Wilensky, U., “NetLogo: design and
- implementation of a multi-agent modeling
- environment”, Proceedings of Agent, Chicago –
- ABD, Ekim 2004.
- Somhom, S., Modares, A. ve Enkawa, T., “A
- Self-organizing Model for the Traveling
- Salesman Problem”, J. of the OR Society, Cilt
- , No 9, 919–928, 1997.
- Cochrane, E. M., ve Beasley, J. E., “The Coadaptive
- Neural Network Approach to the
- Euclidean Traveling Salesman Problem”, Neural
- Networks, Cilt 16,10, 1499–1525, 2003
Toplam 120 adet kaynakça vardır.
Ayrıntılar
| Birincil Dil | Türkçe |
|---|---|
| Bölüm | Makaleler |
| Yazarlar | |
| Yayımlanma Tarihi | 19 Şubat 2013 |
| Gönderilme Tarihi | 19 Şubat 2013 |
| Yayımlandığı Sayı | Yıl 2012 Cilt: 27 Sayı: 4 |