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All Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika)
Fikri, Faiqul
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Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Transportation

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SOLUSI PENDEKATAN PERSAMAAN GELOMBANG FRAKSIONAL NON LINEAR MENGGUNAKAN NEW VERSION OF OPTIMAL HOMOTOPY ASYMPTOTIC METHOD Fikri, Faiqul; Djauhari, Eddy; Rusyaman, Endang
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 14 No 4 (2020): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (751.455 KB) | DOI: 10.30598/barekengvol14iss4pp523-534

Abstract

Non-linear differential equations with fractional derivative order are mathematical models that are widely used in modeling physical phenomena, one of the applications of these models is non-linear fractional wave equations. Many methods for solving non-linear fractional partial differential equations, one of which is the New Version of Optimal Homotopy Asymptotic Method which is developed by Liaqat Ali in 2016. The author will use this method to solve non-linear fractional wave equations predetermined, so that the convergence of function of the approximation solution non-linear fractional wave equation can be observed and it can be observed that the function of approximation solution of non-linear fractional wave equation solution using the New Version of Optimal Homotopy Asymptotic Method is simple and has a value error using Mean Absolute Percentage Error which is categorized very well
Robust Optimization of Vaccine Distribution Problem with Demand Uncertainty Fikri, Faiqul; Silalahi, Bib Paruhum; Jaharuddin, Jaharuddin
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 8, No 2 (2024): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v8i2.20035

Abstract

This study proposes a multi objective optimization model for vaccine distribution problems using the Maximum Covering Location Problem (MCLP) model. The objective function of the MCLP model in this study is to maximize the fulfillment of vaccine demand for each priority group at each demand point. In practice, the MCLP model requires data on the amount of demand at each demand point, which in reality can be influenced by many factors so that the value is uncertain. This problem makes the optimization model to be uncertain linear problem (ULP). The robust optimization approach converts ULP into a single deterministic problem called Robust Counterpart (RC) by assuming the demand quantity parameter in the constraint function is in the set of uncertainty boxes, so that a robust counterpart to the model is obtained. Numerical simulations are carried out using available data. It is found that the optimal value in the robust counterpart model is not better than the deterministic model but is more resistant to changes in parameter values. This causes the robust counterpart model to be more reliable in overcoming uncertain vaccine distribution problems in real life. This research is limited to solving the problem of vaccine distribution at a certain time and only assumes that the uncertainty of the number of requests is within a specified range so that it can be developed by assuming that the number of demand is dynamic.
Co-Authors Bib Paruhum Silalahi Eddy Djauhari Endang Rusyaman Jaharuddin