Efficient Implementation of the Normal Boundary Intersection (NBI) Method on Multiobjective Optimization Problems

Abstract

This study attempts to address efficient implementation of the normal boundary intersection (NBI) method for the tradeoff between economics and pollution prevention with appropriate analysis methods. For the multiobjective optimization problem (MOOP), a noninferior solution curve (or Pareto curve) is efficiently obtained by using an enhanced NBI method combined with the SWOF (summation of weighted objective functions) method within a chemical process simulator. Then, the Pareto curve is analyzed by the ideal compromise solution set, sensitivity and elasticity analyses that give the decision basis between the conflicting objectives to the decision maker. Through the combined use of the SWOF and NBI methods, the upper and lower values of the ideal compromise set are exactly located. The total calculation time for the entire Pareto curve can be reduced owing to evenly distributed Pareto points.