Multicriteria optimization of a high yield pulping process with rough sets

Abstract

The optimization of complex processes usually involves many competing objectives; in this case there is typically no solution that yields optimal values for all of the objective criteria and the decision-maker must therefore find a reasonable compromise. In recent years, new multicriteria methods have been developed to assist the practitioner in achieving a judicious compromise among the various competing objectives. One method, the rough set method (RSM), is able to encapsulate the preferences of an expert within a simple set of logical rules that are used to rank a large number of feasible solutions according to these preferences. The RSM was used in this investigation to determine the optimal operating region of a high yield pulping process. This pulping process has seven input variables that can be manipulated to optimize four objective criteria characterizing the product: brightness, specific refining energy, extractive content, and rupture length. Results show that an optimal solution zone can be easily defined and zones of decreasing preference can be drawn. This information is very useful to the practitioner for choosing the desired operating conditions and for analyzing the robustness of the preferred operating scenarios from a process control point of view.