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All Journal Rekayasa Mesin Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control
Irfan Bahiuddin
Universitas Gadjah Mada
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Mechanical Engineering

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Application of Ant Colony Optimization for the Shortest Path Problem of Waste Collection Process Andhi Akhmad Ismail; Radhian Krisnaputra; Irfan Bahiuddin
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vo. 6, No. 3, August 2021
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v6i3.1307

Abstract

The search for the shortest path of the waste collection process is an interesting topic that can be applied to various cases, from a very practical basic problem to a complex automation system development. In a dense settlement, the waste collection system can be a challenging process, especially to determine the most optimized path. The obstacles can be circling streets, impassable roads, and dead-end roads. A wrong choice of method can result in wasteful consumption of energy. A possible method to solve the problem is the traveling salesman problem using ant colony search optimization, considering its relatively fast optimization process. Therefore, this paper proposes an application of ant colony and traveling salesperson problem in determining the shortest path of the waste collection process. The case study for the optimization algorithm application is the path UGM Sekip Lecturer Housing is considering. Firstly, the data was collected by measuring the distance between points. Then, the paths were modeled and then compared with the actual route used by waste transport vehicles. The last step is implementing the ant colony optimization and traveling salesman problem by determining the cost function and the parameters. The optimization process was conducted several times, considering the random generator within the algorithm. The simulation results show the probable shortest path with a value of about 752 meters so that the use of fossil fuels in waste transport vehicles can be more efficient. The results show that the algorithm can automatically recommend the minimized path length to collect waste.
PERMODELAN INVERSI PEREDAM MAGNET-REOLOGI BERBASIS JARINGAN SARAF TIRUAN UNTUK SISTEM KENDALI Rafly Asprilla Alwi; Irfan Bahiuddin; Ryandhi Rofifu Chazim; Agustinus Winarno; Fitrian Imaduddin
Jurnal Rekayasa Mesin Vol. 13 No. 2 (2022)
Publisher : Jurusan Teknik Mesin, Fakultas Teknik, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/jrm.v13i2.962

Abstract

The application of artificial neural network (ANN) models in magnet-rheological damper modeling is of great interest in recently challenges. Therefore, this study aims to propose a solution to overcome this problem by conducting inverse modeling using an artificial neural network. This inverse model is applied to a meandering magnet-rheological valve damper to predict the current to produce the appropriate damping force. The simulation scheme is selected with current as output and damping force, velocity, and displacement as input. The best model is formulated by varying the architecture of the artificial neural network. The best artificial neural network architecture is obtained after doing these variations. The data is divided into 80% training data, 10% validation data, and 10% test data. The activation function used is a logsig function using three hidden layers with the number of neurons in each layer [30-20-30]. The algorithm used in the chosen architecture is Levenberg-Marquardt. The regression value of 0.991 and the MSE value of 0.001 were obtained from the modeling results. The required damping force is ensured that it can be predicted well using the selected artificial neural network. The test proves that the results of the regression constant are 0.999 and the MSE value is 0.0005 when the current output value is inverted to the damper artificial neural network.
Co-Authors Agustinus Winarno Andhi Akhmad Ismail Fitrian Imaduddin Radhian Krisnaputra Rafly Asprilla Alwi Ryandhi Rofifu Chazim