MULTIOBJECTIVE OPTIMIZATION CONSIDERING ECONOMICS AND ENVIRONMENTAL IMPACT

This paper is devoted to an application of MOOP (multi-objective optimization programming) concept to the practical field of chemical engineering for taking the trade-off between economics and pollution with appropriate analysis method. To analyze the bi-objective optimization system, non-inferior solution curve is formed in using SWOF (Summation of Weighted Objective Functions), GP (Goal Programming) and PSI (Parameter Space Investigation) methods within chemical process simulator. We can find the ideal compromise solution set based on Pareto curve. Multiobjective problem is then interpreted by sensitivity and elasticity analyses of the Pareto curve.