Multi-objective Optimization for Synthesis of Mass Exchange Networks using a fuzzy approach

Abstract

This paper introduces a novel multi-objective optimization method for synthesizing Mass Exchange Networks (MENs), which aims to integrate process streams containing pollutants with simpler or target streams to meet environmental standards. The core research problem addressed is the challenge of simultaneously minimizing operational costs and ensuring efficient pollutant removal, which is not fully addressed by traditional MEN design methods. The proposed approach combines recent advances in pinch technology with fuzzy logic to determine the optimal network configuration. A multi-objective function is developed that considers critical factors such as the surplus capacity of the mass separation agent, the load removal by external separation agents, and the number of plates required in the process. The optimization method is designed to provide more balanced solutions, taking into account both environmental compliance and cost efficiency. To validate the effectiveness of this method, two well-known case studies were conducted: coke-oven gas (COG) sweetening and phenol removal. The results demonstrate that the fuzzy logic-based optimization approach outperforms existing methods, offering more precise, cost-effective solutions while ensuring adherence to environmental standards. In conclusion, this study presents a modern and efficient strategy for synthesizing MENs. The fuzzy logic-based optimization method offers engineers a practical tool to design systems that are both environmentally compliant and economically viable, marking a significant advancement in the field of process optimization for sustainable industrial applications.

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