INVESTIGATION OF TRANSFER FUNCTIONS ON A NOVEL BINARY DRIVING TRAINING-BASED ALGORITHM

Year 2023, Volume: 11 Issue: 2, 433 - 448, 28.06.2023

İsmail Koç

https://doi.org/10.21923/jesd.1176741

Abstract

Uncapacitated Facility Location Problem (UFLP) is an NP-hard problem that determines the optimal location of facilities. Since UFLP is from the NP-Hard problem group, using exact methods to solve large instances of these problems can be seriously problematic due to the high computation time required to obtain the optimal solution. In this study, the swarm intelligence algorithm was preferred due to the complexity of the problem. Driving training-based (DTBO) algorithm, which is a population-based algorithm developed based on driving training principles in recent years, has been used to solve the UFLP problem. Since the basic version of DTBO deals with the solution of continuous problems, the corresponding algorithm needs to be adapted to the solution of binary problems. For this, the DTBO algorithm was designed in accordance with the solution of binary problems with the help of nine different transfer functions used in the literature. Experimental studies were carried out under equal conditions for fair comparison of transfer functions. In the experimental studies carried out, it is seen that the binary Mode-DTBO algorithm is the most successful algorithm among the nine transfer functions. According to these results, it is seen that the binary Mode-based DTBO algorithm is very successful in all small, medium and large scaled problem sets, both in terms of solution quality and time. In addition, the DTBO algorithm was compared with 3 different transfer functions (Mode, Sigmoid and Tanh) of the IWO (Invasive Weed Optimization) algorithm. When the comparative results were examined, it was seen that the Mode-DTBO approach was much more successful than all 3 different approaches of IWO in 8 of the 12 problems (medium and large-scale problems). On the other hand, it has been observed that both algorithms using the Mode function on 4 small-sized problems achieved the optimal value. As a result, it can be said that the binary Mode-DTBO method will be able to offer a very effective alternative in solving binary problems.

Keywords

UFLP, Binary Optimization, DTBO, Transfer Function

YENİ BİR İKİLİ SÜRÜŞ EĞİTİM TABANLI ALGORİTMA ÜZERİNDE TRANSFER FONKSİYONLARININ İNCELENMESİ

Abstract

Kapasitesiz Tesis Yerleşim Problemi (UFLP), tesislerin optimal yerleşimini belirleyen NP-zor bir problemdir. UFLP, NP-Zor problem grubundan olduğu için, bu problemlerin büyük örneklerini çözmek için kesin yöntemlerin kullanılması, optimal çözümü elde etmek için gereken yüksek hesaplama süreleri nedeniyle ciddi şekilde sorun teşkil edebilir. Bu çalışmada, problemin karmaşıklığından dolayı sürü zekası algoritması tercih edilmiştir. Son yıllarda sürüş eğitimi ilkelerine dayalı olarak geliştirilen popülasyon tabanlı bir algoritma olan Sürüş eğitim tabanlı (DTBO) algoritması UFLP probleminin çözümünde kullanılmıştır. DTBO’nun temel versiyonu sürekli problemlerin çözümünü ele aldığından söz konusu algoritmanın ikili problemlerin çözümüne uyarlanması gerekmektedir. Bunun için literatürde kullanılan dokuz farklı transfer fonksiyonu yardımıyla DTBO algoritması ikili problemlerin çözümüne uygun olarak tasarlanmıştır. Deneysel çalışmalar transfer fonksiyonlarının adil kıyaslanabilmesi için eşit koşullarda altında gerçekleştirilmiştir. Gerçekleştirilen deneysel çalışmalarda dokuz transfer fonksiyonu içerisinden ikili Mode-DTBO algoritmasının en başarılı algoritma olduğu görülmektedir. Bu sonuçlara göre Mode tabanlı DTBO algoritmasının küçük, orta ve büyük ölçekli tüm problem setlerinde hem çözüm kalitesi açısından hem de zaman açısından çok başarılı olduğu görülmektedir. Ayrıca DTBO algoritması IWO (Yabani Ot Algoritması – Invasive Weed Optimization) algoritmasına ait 3 farklı transfer fonksiyonuyla (Mode, Sigmoid ve Tanh) da kıyaslanmıştır. Karşılaştırmalı sonuçlar incelendiğinde 12 problemin 8’inde (orta ve büyük ölçekli problem) Mode-DTBO yaklaşımının IWO’ya ait 3 farklı yaklaşımın hepsinden çok daha başarılı olduğu görülmüştür. Bununla beraber, küçük boyutlu 4 problem üzerinde ise Mode fonksiyonunu kullanan her iki algoritmanın da optimal değeri yakaladığı görülmüştür. Sonuç olarak, Mode-DTBO yönteminin ikili problemlerin çözümünde çok etkili bir alternatif sunacağı söylenebilir.

Keywords

UFLP, İkili Optimizasyon, DTBO, Transfer Fonksiyonu

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