Solving Uncertain Online Shopping Problem With Discounts Using Robust Counterpart Methodology
Online Shopping is a phenomenon that is growing rapidly at this time and consumers are an important element in the buying and selling competition in the market and consumers who make a difffference in determining the profifits of the sellers. This research discusses the problem of online shopping u...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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LPPM of Narotama University Surabaya
2021-04-01
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| Series: | IJEBD (International Journal of Entrepreneurship and Business Development) |
| Subjects: | |
| Online Access: | https://jurnal.narotama.ac.id/index.php/ijebd/article/view/1367 |
| Summary: | Online Shopping is a phenomenon that is growing rapidly at this time and consumers are an important element in the buying and selling competition in the market and consumers who make a difffference in determining the profifits of the sellers. This research discusses the problem of online shopping using the Robust Optimization method. Robust Optimization Method is a process to get optimal results with an uncertainty. Based on the demand model to optimize the buying price, an Integer Linear Programming model with discount functions is built which will be converted into Robust Optimization. In this study also used a tool that is the Maple application in the numerical calculation process.
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| ISSN: | 2597-4750 2597-4785 |