(untitled) (The Lumbini Journal of Business and Economics, 2025)
Purpose: In a typical investment problem, the investor wants to maximize the profit or revenue associated with it while simultaneously he desires to minimize time and risks associated with his investments. The fulfilment of this obligation creates a concept of multiobjective problems in which all the associated constraints need to be fulfilled along with the desired obligations associated with it (Revenue, Time and Risk). Conflict may arise in multi-objectives and can be best handled by fuzzy sets. We construct membership functions for the objective functions and formulate a fuzzy optimization problem for allocation of investments. Methods: A comparative approach in solving a Fuzzy approach to multi-objective investment problem (MO-IP) using hyperbolic and S-curve membership functions. Results: The results from this study indicated that optimization through the S-Curve function outperformed the hyperbolic Functions. Using S-curve membership function is one of the most idealistic approaches. Conclusion: From an investor’s perspective, this model emerged as a valuable tool for making more informed decisions amid the uncertainties that precede such decisions. Indeed, the presented demonstration serves as a simplified illustration of a real-world financial problem