Linear Programming as a Mathematical Model in Solving Realistic Optimization Problems: A Theoretical Study
DOI:
https://doi.org/10.24252/msa.v14i1.67450Keywords:
Linear Programming, Optimization, Mathematical Modeling, Realistic Problems, Applied MathematicsAbstract
This article aims to theoretically examine the implementation of Linear Programming learning based on the Realistic Mathematics Education (RME) approach in mathematics instruction. Linear Programming is a fundamental topic in mathematics that is closely related to optimization problems encountered in real-life situations. However, in practice, this material is often presented in an abstract manner, leading to students’ difficulties in understanding both the underlying concepts and their applications. Therefore, an instructional approach that connects mathematical concepts with real-life contexts is essential. This study employs a literature review method by analyzing various relevant sources, including textbooks and scholarly journal articles related to Linear Programming and the RME approach. The findings indicate that RME possesses key characteristics that support the learning of Linear Programming, such as the use of real-world contexts, the process of mathematization, interactive learning, and the development of mathematical models. Through this approach, students are able to construct a more meaningful understanding of Linear Programming concepts, as learning begins with contextual problems that are closely related to their daily lives. Therefore, the Realistic Mathematics Education approach can be considered an effective alternative for developing more contextual and meaningful Linear Programming instruction.
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