Optimizing Iraq's Oil Transportation System Using Fuzzy Nonagonal Membership Functions

Abstract

In linear programming problems, scheduling, production, inventory control, investment, and many other situations require the transportation problem (TP) to be handled. Oil transportation is one of the areas that needs optimization to address the uncertainties in supply and demand. The approach of fuzzy optimization is used to manage the uncertainties associated with oil transportation in Iraq. The nonagonal membership function handles this problem. It can model transportation problem parameters, for example, varying costs, uncertain supply, and fluctuating demand. This function aims to solve this important issue based on its nine vertices, which help represent these fuzzy parameters. Our work presents a new application of this approach to oil transportation in Iraq. Its proven impact optimizes the parameter's value and improves decision-making. The fuzzy approach is compared with the conventional method for solving transportation problems to show its effectiveness in handling uncertainty and its efficiency in optimizing the oil transportation problem.