论文信息 - A new methodology for solving multi-objective stochastic optimization problems with independent objective functions

A new methodology for solving multi-objective stochastic optimization problems with independent objective functions

For multi-objective optimization problems, a common solution methodology is to determine a Pareto optimal set. However, the Pareto optimal set only pertains to deterministic results. Our research aims to introduce Pareto Uncertainty Index which reflects the stochastic nature of the problem in the results. The proposed method is applied to a simplified Generation Expansion Planning problem to test the Pareto Uncertainty Index idea.

[1] Ozgu Turgut,et al. Generating Pareto Surface for Multi Objective Integer Programming Problems with Stochastic Objective Coefficients , 2011, Complex Adaptive Systems.

[2] Rafael Caballero,et al. Stochastic approach versus multiobjective approach for obtaining efficient solutions in stochastic multiobjective programming problems , 2002, Eur. J. Oper. Res..

[3] Jacques Teghem,et al. Multi-Objective Decision Making under Uncertainty: An Example for Power System , 1985 .

[4] J. Teghem,et al. STRANGE: an interactive method for multi-objective linear programming under uncertainty , 1986 .

[5] Raymond Nadeau,et al. Multiobjective Stochastic Linear Programming with Incomplete Information: A General Methodology , 1990 .

[6] P. Lang,et al. Dominance and Efficiency in Multicriteria Decision under Uncertainty , 1999 .

[7] George Mavrotas,et al. Effective implementation of the epsilon-constraint method in Multi-Objective Mathematical Programming problems , 2009, Appl. Math. Comput..

[8] Fouad Ben Abdelaziz,et al. Solution approaches for the multiobjective stochastic programming , 2012, Eur. J. Oper. Res..

[9] Fouad Ben Abdelaziz,et al. Decision-maker's preferences modeling in the stochastic goal programming , 2005, Eur. J. Oper. Res..