Robustness analysis methodology for multi-objective combinatorial optimization problems and application to project selection

George Mavrotas, José Rui Figueira, Eleftherios Siskos
2015 Omega : The International Journal of Management Science  
Multi-objective combinatorial optimization (MOCO) problems, apart from being notoriously difficult and complex to solve in reasonable computational time, they also exhibit high levels of instability in their results in case of uncertainty, which often deviate far from optimality. In this work we propose an integrated methodology to measure and analyze the robustness of MOCO problems, and more specifically multi-objective integer programming ones, given the imperfect knowledge of their
more » ... . We propose measures to assess the robustness of each specific Pareto optimal solution (POS), as well as the robustness of the entire Pareto set (PS) as a whole. The approach builds upon a synergy of Monte Carlo simulation and multi-objective optimization, using the augmented ε-constraint method to
doi:10.1016/ fatcat:bo22xeglovhnzk7vrwkljfjazi