Abstract
In this paper, a new multi-objective particle swarm optimization (MOPSO) procedure, based on the Pareto dominance hybrid algorithm, is proposed and applied in a naphtha industrial cracking furnace for the first time. Pareto dominance is incorporated into particle swarm optimization (PSO). Our algorithm takes the Pareto set as a repository of particles that is later used by other particles to guide their own flight. In addition, an MOPSO and artificial neural network (ANN) hybrid model is applied in the operation optimization of a naphtha industrial cracking furnace. Therein, sensitivity analysis is investigated and taken as the basis on which decision variables of multi-objective problem base. From both theoretical computation and practical application, the validity and reliability of proposed algorithm are verified by two test functions studied, and actual application example of the optimization of operation parameter of cracking process. Moreover, the yields of ethylene and propylene are improved.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
