Multi-objective modeling and optimization for cleaner production processes

The paper presents a methodology for multi-objective modeling and optimization with environmental impacts and economics aspects simultaneously in the context of cleaner production. A generalized multi-objective process model is proposed based on a holistic concept of macro-structure. A hybrid multi-objective evolutionary algorithm is proposed to solve this multi-objective optimization problem. The Elitist Non-dominated Sorting Genetic Algorithm is used to obtain the Pareto-optimal set. The best compromised solution is determined by using the Technique for Order Preference by Similarity to the Ideal Solution. A simple reaction system is presented as a case study to illustrate the proposed methodology.