Post optimality analysis of Pareto optimal set through weights robustness

Traditional multi-objective optimization attempts to And Pareto optimal solutions. Since a Pareto optimal set can be huge, the problem of selecting one or few solutions occurs. Post optimality analysis in multi-objective optimization requires incorporation of decision makers' preferences in the form of weights. In this paper the concept of robustness with regards to weights is introduced. The different types of weights robustness show how sensitive a solution is to variation in weights' coefficients. An approach for analysis of Pareto optimal sets through weights robustness is then devised. The suggested approach can be of special interest in the presence of conflicting preferences among decision makers or when preference information is unavailable. In conclusion, managerial usage it in the different strategies for negotiation provides possibility to thoroughly weigh all alternatives before settling on an agreement.