Fuzzy Linear Programming for Economic Planning and Optimization: A Quantitative Approach

Fuzzy Linear Programming (FLP) has the potential to be used in optimizing economic planning and making decisions under uncertainty. FLP incorporates fuzzy logic into linear programming to represent and manage economic parameters that are uncertain, e.g., costs, profits, and availability of inputs. Practical applications in Economic resource allocation illustrate the effectiveness of FLP, as demonstrated by the study. ISMC-based FLP has been shown to offer a flexible solution that is more adaptable and realistic than classical linear programming models. This research reiterates practical economic scenarios through fuzzy data, considering uncertainties and vagueness in risk measures, helping to make better and effective decision-making. Future research directions involve combining FLP with Artificial Intelligence (AI) and Big Data in finance to improve its utility in complex and dynamically changing economic systems, allowing easier and automatic decision making. FLP moves beyond the deterministic nature of traditional modelling by integrating fuzzy data, allowing the model to reach more flexible and realistic results and providing better decision-making.