caa a22 4500 605470472 CHVBK 20210128100328.0 cr unu---uuuuu 210128e20150501xx s 000 0 eng 10.1007/s00500-014-1349-y doi (NATIONALLICENCE)springer-10.1007/s00500-014-1349-y Differential evolution algorithm with self-adaptive strategy and control parameters for P -xylene oxidation process optimization [Elektronische Daten] [Qinqin Fan, Xuefeng Yan] Considering that the model of the $$p$$ p -Xylene (PX) oxidation reaction process is a hybrid and highly nonlinear model, a differential evolution algorithm with self-adaptive mutation strategy and control parameters (SSCPDE) was proposed to optimize the operating conditions. In SSCPDE, each individual has its own control parameters and mutation strategies that can be self-adaptively adjusted to different evolution phases and various optimization problems. SSCPDE was compared with 6 state-of-the-art DE variants by 38 different types of benchmark functions. Simulation results show that the average performance of SSCPDE is better than the six famous self-adaptive DE algorithms. Finally, the SSCPDE algorithm was used to optimize the five main operating conditions of the PX oxidation reaction process. Optimization results indicate that the production cost, loss of acetic acid and PX combustion of the PX oxidation reaction process are greatly reduced and that SSCPDE performs better than JADE, EPSDE, SaDE, and the optimizer of Aspen Plus and similar to jDE and CoDE. Springer-Verlag Berlin Heidelberg, 2014 Process optimization nationallicence $$p$$ p -Xylene oxidation process nationallicence Differential evolution algorithm nationallicence Parameter adaptation nationallicence Mutation strategy adaptation nationallicence Fan Qinqin Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology, MeiLong Road NO. 130, P.O. BOX 293, 200237, Shanghai, People's Republic of China aut Yan Xuefeng Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology, MeiLong Road NO. 130, P.O. BOX 293, 200237, Shanghai, People's Republic of China aut Soft Computing Springer Berlin Heidelberg 19/5(2015-05-01), 1363-1391 1432-7643 19:5<1363 2015 19 500 https://doi.org/10.1007/s00500-014-1349-y text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00500-014-1349-y text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Fan Qinqin Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology, MeiLong Road NO. 130, P.O. BOX 293, 200237, Shanghai, People's Republic of China aut NATIONALLICENCE 700 1- Yan Xuefeng Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology, MeiLong Road NO. 130, P.O. BOX 293, 200237, Shanghai, People's Republic of China aut NATIONALLICENCE 773 0- Soft Computing Springer Berlin Heidelberg 19/5(2015-05-01), 1363-1391 1432-7643 19:5<1363 2015 19 500