Robust optimization method for the economic term in chemical process design and planning

This paper presents a framework for robust optimization of the economic term in chemical process design and planning. Robust optimization models are considered as a multiobjective optimization problem whose objectives are the expected performance and the robustness. The Pareto-optimal subset condition for robust economic optimization is developed. Various types of robustness measures are discussed from the point of view of the Pareto-optimal subset condition and numerical implementation. As a result, the cost of the worst-case scenario is proposed as the robustness measure for cost-minimization problems. A decision-making procedure is proposed to select the best robust design among the robust design alternatives obtained by the proposed robust model. Examples illustrate the adequateness of the proposed robustness measure and the efficacy of the proposed decision-making procedure.