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YAPAY BAĞIŞIKLIK SİSTEMİNİN ÇOKLU ETMEN BENZETİM ORTAMINDA REALİZE EDİLMESİ VE GEZGİN SATICI PROBLEMİNE UYGULANMASI.

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Title: YAPAY BAĞIŞIKLIK SİSTEMİNİN ÇOKLU ETMEN BENZETİM ORTAMINDA REALİZE EDİLMESİ VE GEZGİN SATICI PROBLEMİNE UYGULANMASI.
Alternate Title: REALIZING ARTIFICIAL IMMUNE SYSTEM IN A MULTI AGENT SIMULATION ENVIRONMENT AND AN APPLICATION TO TRAVELLING SALESMEN PROBLEM.
Authors: BAYKASOĞLU, Adil1 adil.baykasoglu@deu.edu.tr, SALTABAŞ, Alper1 alper.saltabas@gmail.com, TAŞAN, A. Serdar1 serdar.tasan@deu.edu.tr, SUBULAN, Kemal1 kemal.subulan@deu.edu.tr
Source: Journal of the Faculty of Engineering & Architecture of Gazi University / Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi,. Dec2012, Vol. 27 Issue 4, p901-909. 9p. 6 Diagrams, 4 Charts.
Subjects: Computer simulation of immune system, Multiagent systems, Simulation methods & models, Traveling salesman problem, Algorithms, Combinatorial optimization
Abstract (English): Although many meta-heuristic algorithms were developed for solving combinatorial optimization problems, very few of them were realized in an agent based environment. Especially the algorithms which model dynamics of Artificial Immune Systems (AIS) are population based approaches with adaptability characteristics, therefore AIS can be better realized in an agent based modeling environment. For this purpose first time in the literature a clonal selection algorithm which is an AIS based algorithm is modeled in a multi-agent environment for solving the travelling salesmen problem which is a combinatorial optimization problem. In order to observe the behavior of the algorithm, simulation experiments are carried out on several test problems. Netlogo software is utilized for developing agent based models and simulation tests. Moreover, receptor change process and crossover mechanisms are integrated into the proposed model in order to improve the performance of the classical clonal selection algorithm. It is shown that there is a high potential to obtain good solution by making use of agent oriented approaches which more realistically model the natural phenomenon. [ABSTRACT FROM AUTHOR]
Abstract (Turkish): Kombinatoryal optimizasyon problemlerinin çözümü için geliştirilen birçok meta-sezgisel algoritma bulunmasına rağmen bu algoritmaları etmen tabanlı modelleme ortamında realize eden çalışmaların sayısı çok azdır. Özellikle Yapay Bağışıklık Sisteminin (YBS) dinamiklerini modelleyen algoritmaların adaptasyon yeteneğine sahip popülasyon tabanlı yaklaşımlar olması, YBS'nin etmen tabanlı modelleme ortamında gerçeğe daha yakın bir şekilde realize edilmesini sağlayacaktır. Bu amaçla ilk defa mevcut çalışmada, bir kombinatoryal optimizasyon problemi olan gezgin satıcı probleminin (GSP) modellenmesi ve çözümü için yapay bağışıklık sistemi algoritmalarından klonal seçim algoritması çoklu etmen benzetim ortamında modellenmiş ve algoritmanın gösterdiği davranışın incelenmesi için farklı GSP setleri üzerinde benzetim deneyleri gerçekleştirilmiştir. Etmen tabanlı modellerin geliştirilmesi ve benzetim testlerinin yapılabilmesi için Netlogo yazılımı kullanılmıştır. Ayrıca geleneksel klonal seçim algoritmasının performansını arttırmak için reseptör değişim süreci ve çaprazlama mekanizması önerilen modele entegre edilmiş ve doğal oluşları daha gerçekçi modelleyebilen etmen tabanlı yaklaşımlar ile de etkin çözümler elde edilebileceği gösterilmiştir. [ABSTRACT FROM AUTHOR]
Copyright of Journal of the Faculty of Engineering & Architecture of Gazi University / Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, is the property of Gazi University, Faculty of Engineering & Architecture and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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Abstract:Although many meta-heuristic algorithms were developed for solving combinatorial optimization problems, very few of them were realized in an agent based environment. Especially the algorithms which model dynamics of Artificial Immune Systems (AIS) are population based approaches with adaptability characteristics, therefore AIS can be better realized in an agent based modeling environment. For this purpose first time in the literature a clonal selection algorithm which is an AIS based algorithm is modeled in a multi-agent environment for solving the travelling salesmen problem which is a combinatorial optimization problem. In order to observe the behavior of the algorithm, simulation experiments are carried out on several test problems. Netlogo software is utilized for developing agent based models and simulation tests. Moreover, receptor change process and crossover mechanisms are integrated into the proposed model in order to improve the performance of the classical clonal selection algorithm. It is shown that there is a high potential to obtain good solution by making use of agent oriented approaches which more realistically model the natural phenomenon. [ABSTRACT FROM AUTHOR]
ISSN:13001884