Parametric approach for multi-objective enhanced interval linear fractional programming problem

The design (decision) variables in the presented article of a multi-objective interval fractional optimization problem based on a linear function are assumed to take the form of a closed interval using the concept of the parametric form of an interval. The original problem is initially changed into equivalent multi-objective interval linear programming with the design variables as closed intervals. Further, it is made free from interval uncertainty by changing into a classical single-objective problem using the weighted-sum method. The solutions of the model are theoretically justified by its existence. Finally, a numerical example and a case study on the agricultural planting structure optimization problem with hypothetical data are presented to support the recommended technique for the model.

Automated summary

The presented article focuses on a multi-objective interval fractional optimization problem based on a linear function. The design variables are assumed to be closed intervals using the parametric form of an interval. The original problem is transformed into an equivalent multi-objective interval linear programming problem with closed interval design variables. By utilizing the weighted-sum method, the problem is further converted into a classical single-objective problem without interval uncertainty. The model's solutions are theoretically justified by proving their existence. Finally, a numerical example and a case study on agricultural planting structure optimization problem with hypothetical data are provided to support the recommended technique for the model.