Multiobjective particles swarm optimization and multicriteria decision making of improved cumene production process including economic, environmental, and safety criteria

Abstract

AbstractCumene is one of the five chemicals with the highest production in the world. In this work, the design by Flegiel was improved to increase the production rate of the cumene process by adding a trans‐alkylation reactor, then multi‐objective optimization (MOO) using the particles swarm optimization (PSO) algorithm is used to improve the process design. Furthermore, seven multicriteria decision‐making (MCDM) methods for selecting an optimal solution from the Pareto‐optimal front related to two MOO problems were performed. In this optimization, conflicting objectives such as total capital cost (TCC), energy cost, wastage rate, and safety target are simultaneously minimized in the format of trade‐offs. Finally, the results of this work were compared with those reported designs. The optimal solution chosen by MCDM methods is at TCC = 5589, damage index (DI) = 0.044, and material loss = 0.0005.