Feasible Region Contraction Interior-Point Algorithm (FERCIPA) Solver for Multi-Objective Linear Programming Problems


Authors : Edwin F. Nsien, Ubon A. Abasiekwere, Paul J. Udoh.

Volume/Issue : Volume 4 - 2019, Issue 3 - March

Google Scholar : https://goo.gl/DF9R4u

Scribd : https://bit.ly/2JYXOr2

Abstract : This paper presents FERCIPA solver for linear programming problems. The solver which can handle both single objective and multi-objective linear programming problems of large scales generates a sequence of interior feasible points that converge at the optimal solution for single objective linear programming problems and an optimal compromise solution for multi-objective linear programming problems. The solver is validated by its application to handle single objective linear programming problems and multi-objective linear programming problems involving up to six bounded variables and functional constraints. The solution obtained by FERCIPA solver is seen to compare favourably with those of other software like the Feasible Region Contraction Algorithm (FRCA) and MATLAB.

Keywords : FERCIPA Solver, Multi-objective linear programming, Interior feasible point, Optimal compromise solution.

This paper presents FERCIPA solver for linear programming problems. The solver which can handle both single objective and multi-objective linear programming problems of large scales generates a sequence of interior feasible points that converge at the optimal solution for single objective linear programming problems and an optimal compromise solution for multi-objective linear programming problems. The solver is validated by its application to handle single objective linear programming problems and multi-objective linear programming problems involving up to six bounded variables and functional constraints. The solution obtained by FERCIPA solver is seen to compare favourably with those of other software like the Feasible Region Contraction Algorithm (FRCA) and MATLAB.

Keywords : FERCIPA Solver, Multi-objective linear programming, Interior feasible point, Optimal compromise solution.

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