Pareto Optimization of Low‐Density Polyethylene in a Tubular Reactor Using a Hybrid Strategy

Abstract

Multi‐objective optimization (MOO) to produce low‐density polyethylene (LDPE) in a tubular reactor is performed for three different purposes, namely, maximizing the monomer exchange rate, lowering operational costs, and increasing the productivity. The ASPEN simulator is used to resolve optimization problems. Here, MOO of particle swamp optimization (MOPSO), non‐dominated sorting genetic algorithm (NSGA‐II), and a hybrid strategy of NSGA II‐MOPSO are employed as a model‐based optimization for LDPE production in a tubular reactor. The results demonstrated that the hybrid strategy of NSGA II‐MOPSO is the most effective MOO strategy. Using the hybrid strategy, the discovered solution set provides the utmost precision and diversity along the Pareto front.