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Journal : Knowledge Engineering and Data Science

The Effect of the Number of Hidden Layers on The Performance of Deep Q-Network for Traveling Salesman Problem Hanif, Benzfica; Larasati, Aisyah; Nurdiansyah, Rudi; Le, Trung
Knowledge Engineering and Data Science Vol 6, No 2 (2023)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um018v6i22023p188-198

Abstract

The Traveling Salesman Problem (TSP) effectively represents the complex distribution issues encountered by couriers, who must carefully plan a route that includes all customer addresses while minimizing the distance traveled. As the magnitude of deliveries and the range of destinations expand, the courier's responsibility becomes progressively challenging. In this particular context, the objective of our research is to expand the existing knowledge and explore the complete capabilities of Deep Q-Network (DQN) models in order to achieve the most efficient route determination. This endeavor can potentially bring about significant changes in the courier and delivery service sector. The foundation of our unique methodology relies on an empirical inquiry, utilizing a comprehensive dataset including 178 observations obtained from motorcycle-based package delivery agents. Our research is carefully planned and executed using a comprehensive factorial experimental design. This design incorporates three crucial factors: the number of hidden layers, episodes, and epochs. The hidden layer parameter is set to a singular level, while the episode parameter is configured to explore five levels, and the epoch parameter is designed to travel four levels. The evaluation of our DQN models' performance is conducted utilizing the MSE metric as a measure. This assessment is carried out at every iterative cycle, ensuring thorough scrutiny. The central focus of our research centers on the intricate connection between episodes and epochs, and their influence on MSE. The findings of our study reveal that the association between episodes, epochs, and errors is not statistically significant although different level of episodes and epochs produces slightly different level of error.
Co-Authors Abdul Muid Abdul Muid Abdul Rahman, Azrul Abdul Rahman, Soufhwee Adithya Sudiarno Afridasari, Mayang Fikri Agus Rachmad Purnama Ahmad Murtaja Dzaky Ma’arij Amanda Eka Putri Aminnudin, Aminnudin Apif M. Hajji Apif Miptahul Hajji Azrul Abdul Rahman Azzahra, Prestika Dilla Benzfica Hanif Alfi Al Idrus Chen, Yuh-Wen Dewi Hardiningtyas Diva Odilia Shafitri Dwiastuti, Anik Effendi Bin Mohamad Eridani Budi Darmawan, Vertic Erwin Komara Mindarta Fathullah, Muhammad Fatimatuzzahro, Adelia Fauziah, Taznim Hajji, Apif M. Hanif, Benzfica Haque, Salma Ayu Hary Suswanto Heru Setiyo Cahyono Heru Suryanto Huang Yue Ihwan Hamdala Imam Alfianto Indra, Sofiandi Dwi Indrawan, Yogi Fradika Ishardita Pambudi Tama Issutarti Issutarti Issutarti Issutarti, Issutarti Ito, Teruaki Jibril Maulana Khaznahar, Vitmaya khusnul khotimah Laili Hidayati Le, Trung Lucia Andriani Pranita Mahsuli, Taufiq Malta R, Viola Marsono Marsono Michael P. Lewis Michael P. Lewis Moekti, M. Rhessal Chandra Mohamad Yogi Hertanto Mohamad, Effendi Mohamad, Effendi Bin Muhamad Muhajir Mu’id, Abdul Nikmatus Sholikha, Nikmatus Nugraha, Cahya Nurdiansyah Rudi Nurismalatri Nurismalatri Oktavia, Andiny Trie Prabawati, Lucky Pramudya, Henang Duta Puji Rahmawati Purnomo Hadi Susilo, Purnomo Hadi Putra, Ryan Syahriel Maulana Putranto, Akhsana Naufal Putro, Dilla Praditya Hutomo Rina Rifqie Mariana Rinawan, Rangga Bayu Rizqi Prayoga Editya Rosa Putri Pertiwi Sahal, Ahmad Salsabila, Titalia Trias Santoso, Gilang Aditya Setiyono Setiyono Siregar, Ivana Maretha Soufhwee Abdul Rahman Suci Qolbiah Supawi Pawenang supawi pawenang Susanto, Yohana Ruth Wulan Natalia Syah, Yasifun Ardian Teruaki Ito Titi Mutiara Kiranawati Trias Salsabila, Titalia Tuwoso Vania, Nur Izza Vertic Eridani Vertic Eridani Budi Darmawan Widi Rimastuti Widowati, Tamara Rahma Yudistira, Febrina Dzuldah