Hybrid multi-objective differential evolution for multi-objective optimization of industrial polymeric materials

Ashish M. Gujarathi, B. V. Babu

Chemical Engineering Department,Birla Institute of Tehnology and Science,Pilani – 333031 Rajasthan, India.

DOI:

https://doi.org/10.7494/cmms.2011.3.0370

Abstract:

MOO of industrial case studies involving process design decisions [namely, styrene reactor, polyethylene terephthalate (PET) reactor, and low density polyethylene (LDPE) tubular reactor] is carried out using the newly developed algorithms. The performance of newly developed algorithms is checked with respect to the effects of dominant decision variables on the Pareto front. The Pareto fronts obtained using the algorithms developed in this study are compared among themselves, with the industrial data, and the data reported in the literature. The newly developed strategies of MODE algorithm are able to converge to a better Pareto front as compared to the Pareto fronts obtained using MODE and NSGA for styrene reactor. For PET reactor, where NSGA algorithm gave a single point solution, the strategies of MODE algorithm resulted in a Pareto front (consisting of setoff solutions). For LDPE tubular reactor, the results obtained in this study show that MODE III algorithm is able to give a wide range of solutions on the Pareto front as compared to those obtained using other strategies of MODE. The points on the Pareto front are of interest to the decision makers (plant engineers) involved in process design decisions.

Cite as:

Gujarathi, A., & Babu, B. (2011). Hybrid multi-objective differential evolution for multi-objective optimization of industrial polymeric materials. Computer Methods in Materials Science, 11(3), 463 – 468. https://doi.org/10.7494/cmms.2011.3.0370

Article (PDF):

Keywords:

Multi-objective optimization, Evolutionary algorithms, Multi-objective differential evolution, Hybrid algorithms, Pareto front, Industrial problems

References: