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Multi-objective modified differential evolution algorithm with archive-base mutation for solving multi-objective \(p\)-xylene oxidation process

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Abstract

Maximizing the diversity of the obtained objective vectors and increasing the convergence speed to the true Pareto front are two important issues in the design of multi-objective evolutionary algorithms (MOEAs). To solve complex multi-objective optimization problems (MOPs), a multi-objective modified differential evolution algorithm with archive-base mutation (MOMDE-AM) is proposed. In MOMDE-AM, with the purpose of reducing the loss of population evolution information, a modified mutation strategy with archive is introduced, which could utilize several useful inferior solutions and provide promising direction information toward the true Pareto front. The performance of MOMDE-AM is compared with five other MOEAs on five bi-objective and five tri-objective optimization problems. The simulation and statistical analysis results indicate that the overall performance of MOMDE-AM is better than those of the compared algorithms on these test functions. Finally, MOMDE-AM is used to optimize ten operation conditions of the \(p\)-xylene oxidation reaction process; the results show that MOMDE-AM is an effective and efficient optimization tool for solving actual MOPs.

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Acknowledgments

The authors gratefully acknowledge the support from the following foundations: 973 Project of China (2013CB733605), National Natural Science Foundation of China (21176073) and the Fundamental Research Funds for the Central Universities.

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  1. Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of Education, East China University of Science and Technology, P.O. BOX 293, MeiLong Road NO. 130, Shanghai, 200237, People’s Republic of China

    Qinqin Fan & Xuefeng Yan

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Correspondence to Xuefeng Yan.

Appendix

Appendix

See Table 11.

Table 11 Operation conditions of PX oxidation reaction process at 10 a.m. on 16 july 2009
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Fan, Q., Yan, X. Multi-objective modified differential evolution algorithm with archive-base mutation for solving multi-objective \(p\)-xylene oxidation process. J Intell Manuf 29, 35–49 (2018). https://doi.org/10.1007/s10845-015-1087-8

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