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All Journal Jurnal Teknoin OPSI Seminar Nasional Teknik Kimia Kejuangan Heuristic Jurnal Sistem dan Manajemen Industri Jurnal Teknik Industri : Jurnal Hasil Penelitian dan Karya Ilmiah dalam Bidang Teknik Industri INTECOMS: Journal of Information Technology and Computer Science Journal of Appropriate Technology for Community Services Enrichment : Journal of Management International Journal of Industrial Optimization (IJIO) Dinamika Kerajinan dan Batik : MAJALAH ILMIAH International Journal of Computer and Information System (IJCIS) International Journal of Multidisciplinary Research and Literature (IJOMRAL)
Muhammad Ridwan Andi Purnomo
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Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Journal : OPSI

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Intelligent products pricing in dynamic competition based-on Stackelberg game theory Purnomo, Muhammad Ridwan Andi
OPSI Vol 18 No 1 (2025): OPSI - June 2025
Publisher : Jurusan Teknik Industri, Fakultas Teknologi Industri UPN "Veteran" Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/opsi.v18i1.14284

Abstract

Optimising product price is essential in dynamic competitive markets to maximise the total profit of all players and secure their survival in the market. This study addresses the intelligent optimisation of product prices in a competitive environment using Stackelberg game theory (SGT), where both a leader and follower player are considered. The objective is to determine the optimum selling prices for five main products to maximise the profits of all the players. Novel aspects of this study are the integration of optimisation models of all of the players and incorporation demand prediction accuracy into the optimisation process, ensuring that the predicted demand resulting from optimised prices aligns with historical demand data—a factor that has been disregarded by prior studies. Genetic Algorithm (GA) is employed for the optimisation algorithm due to the complexity of the model that involves numerous parameters and decision variables. The results demonstrate that the proposed products selling prices not only enhances the total profits of all of the players but also ensures that the predicted demand pattern closely fits the historical demand data pattern, validating the effectiveness of the approach.
Co-Authors Agham Satria Pristiwaji Agus Haerudin Agus Haerudin Agus Agus Mansur, Agus Alhabsyi, Feni Silvani P Ali Parkhan Apriani, Ratna Agil Basuki, Demas Emirbuwono Dhuha Khanif Rizky Dian Janari Digdoyo Oktapriandi Febriani, Atik Imam Djati Widodo Kirana, Nabila Lintang Mei Andrianto Meilinda Fitriani Nur Maghfiroh Nashrullah Setiawan Novrianty Rizky Rifa'i Rifa'i Rosyid, Yaqub Kasuma Saputra, Rafly Galih Saputro, Iswoyo Seno Sholeh Ma’mun Sri Indrawati Taufiq Immawan, Taufiq Wahyu Sidiq Saputra Widodo, Imam Djati Zainudin Zukhri