Situation Based Fuzzy Multi Objective Optimization Techniques By The Utility Of Diverse Fuzzy Numbers

Abstract

newline Multi-objective linear programming problems (MOLPP) are a decision-making tool in many real-world disciplines, such as distribution, production, economics, and ecology. Uncertainty in data makes optimization problems more challenging to resolve since they become fuzzy optimization problems. In this thesis, we look at how well different approaches work in different situations when it comes to addressing fuzzy multi-objective linear programming problems (FMOLPPs).