Göç eden kuşlar optimizasyon algoritması ve akıllı su damlaları optimizasyon algoritması verimlilik analizi
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Date
2020
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Düzce Üniversitesi
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info:eu-repo/semantics/openAccess
Abstract
Literatürde birçok arama ve optimizasyon algoritması bulunmaktadır. Ancak tüm arama ve optimizasyon problemleri için en iyi sonucu veren algoritma henüz tasarlanmadı. Bu çalışmada doğadan esinlenerek geliştirilmiş iki algoritma olan Göç Eden Kuşlar Optimizasyon Algoritması ve Akıllı Su Damlaları Optimizasyon Algoritması kullanılarak verimlilik analizi yapılmıştır. Göç Eden Kuşlar Optimizasyon Algoritması, tabiattaki göçmen kuş sürülerinin davranışlarından esinlenerek önerilmiş bir metasezgisel algoritmadır. Bazı optimizasyon probleminin çözümünde en iyi sonucu verdiği yapılan çalışmalar ile kanıtlanmıştır. Göç Eden Kuşlar incelendiğinde "V" şeklinde hareket ettikleri tespit edilmiştir. Kuşların bu hareketi onlara kaynaktan hedefe doğru giden yolda daha az enerji harcamaları ve hedefe daha kısa sürede varmalarını sağlamaktadır. Akıllı Su Damlaları Optimizasyon Algoritması doğal bir nehirdeki su damlalarının kaynaktan hedefe giderlerken her zaman daha kısa bir yol bulduğunu gözlemlenerek gerçekleştirilmiş bir algoritmadır. Nehirler, denizler gibi doğal su kaynakları incelendiğinde su damlalarının kaynaktan hedefe giden yolda her zaman daha kolay yolu (toprak miktarı diğer yollardan az olan bir yol) seçtikleri görülmüştür. Su damlaları sıfır olmayan bir hıza sahiptirler ve üzerlerinde toprak taşırlar. Literatürde metasezgisel algoritmalar ve metasezgisel olmayan algoritmalar bulunmaktadır. Bu çalışmada metasezgisel algoritmalardan olan Göç Eden Kuşlar Optimizasyon Algoritmasındaki adımlarda rastgele seçimli olan adımları, rastgele olarak değil, literatürdeki metasezgisel algoritmalardan olan Akıllı Su Damlaları Optimizasyon Algoritması ile belirleyip problem çözme verimliliğini iyileştirmek hedeflenmiştir. Bu amacın gerçekleştiğini göstermek için örnek problemler üzerinde çözümler uygulanıp karşılaştırmalı olarak sunulmuştur.
There are many search and optimization algorithms in the literature. However, the algorithm that gives the best results for all search and optimization problems have not been designed yet. In this study, efficiency analysis was performed by using Migrating Birds Optimization Algorithm and Intelligent Water Drops Optimization Algorithm, which are two algorithms developed inspired by nature. The Migrating Birds Optimization Algorithm is a proposed metaheuristic algorithm inspired by the behavior of migratory bird flocks in nature. It has been proven with the studies that it gives the best result in solving some optimization problem. When migrating birds were examined, it was found that they acted as "V". This movement of birds enables them to spend less energy on the road from source to the destination and to reach the destination in a shorter time. Intelligent Water Drops Optimization Algorithm is an algorithm created by observing that water drops in a natural river always find a shorter path from the source to the destination. When natural water sources such as rivers and seas were examined, it was seen that water drops always chose the easier way (a road with less than other roads) on the road from the source to the destination. Water drops have a non-zero speed and carry soil on them. In the literature, there are metaheuristic and non-metaheuristic algorithms. In this study, it was aimed to improve the problem solving efficiency by determining the randomly selected steps in the steps in the Migrating Birds Optimization Algorithm, which is one of the meteheuristic algorithms in the literature. In order to show that this goal has been achieved on sample problems and presented comparatively.
There are many search and optimization algorithms in the literature. However, the algorithm that gives the best results for all search and optimization problems have not been designed yet. In this study, efficiency analysis was performed by using Migrating Birds Optimization Algorithm and Intelligent Water Drops Optimization Algorithm, which are two algorithms developed inspired by nature. The Migrating Birds Optimization Algorithm is a proposed metaheuristic algorithm inspired by the behavior of migratory bird flocks in nature. It has been proven with the studies that it gives the best result in solving some optimization problem. When migrating birds were examined, it was found that they acted as "V". This movement of birds enables them to spend less energy on the road from source to the destination and to reach the destination in a shorter time. Intelligent Water Drops Optimization Algorithm is an algorithm created by observing that water drops in a natural river always find a shorter path from the source to the destination. When natural water sources such as rivers and seas were examined, it was seen that water drops always chose the easier way (a road with less than other roads) on the road from the source to the destination. Water drops have a non-zero speed and carry soil on them. In the literature, there are metaheuristic and non-metaheuristic algorithms. In this study, it was aimed to improve the problem solving efficiency by determining the randomly selected steps in the steps in the Migrating Birds Optimization Algorithm, which is one of the meteheuristic algorithms in the literature. In order to show that this goal has been achieved on sample problems and presented comparatively.
Description
YÖK Tez No: 641346
Keywords
Bilgisayar Mühendisliği Bilimleri-Bilgisayar ve Kontrol, Computer Engineering and Computer Science and Control
