Applications of Genetic Algorithm in Polymer Science and Engineering

Abstract

In the last several years, genetic algorithm (GA) has gained wide acceptance as a robust optimization algorithm in almost all areas of science and engineering. Polymer science and engineering is no exception. Researchers in this field have devoted considerable attention to the optimization of polymer production using objective functions and constraints that lead to products having desired material properties. Multiple-objective functions have been optimized simultaneously. An example is the minimization of the reaction time in a reactor (lower costs) while simultaneously minimizing the concentration of side products (that affect the properties of the product adversely). Several end-point constraints (equality or inequality) may also be present, as, e.g., obtaining polymer of a desired molecular weight. Again, this requirement stems from producing polymer having desired strength. Solving such problems usually result in Pareto sets. A variety of adaptations of GA have been developed to obtain optimal solutions for such complex problems. These adaptations can be used to advantage in other fields too. The applications of GA in areas of polymer science and engineering other than polymerization systems are few and far between, but this field is now maturing, and it is hoped that the future will see several newer applications.

Simulation and Optimization of Wiped-Film Poly-Ethylene Terephthalate (PET) Reactor Using Multiobjective Differential Evolution (MODE)

“…Pareto sets of nondominated solutions are generated in all cases. Several researchers extended their study in the filed of polymer development [18][19][20][21][22][23][24][25].…”

Mass balance calculations in copper flash smelting by means of genetic algorithms

“…3 They have been extensively used as optimization techniques 4 in a number of engineering processes such as steelmaking, polymer production, design of pharmaceutical formulations, hydrocyclone design and performance, preparation of concrete mixtures, and cathodic protection. [5][6][7][8][9][10] The genetic algorithm method used in this work takes into consideration the raw elemental analysis of the concentrates and computes the corresponding mineralogical composition of the feed. Such a composition is further used in the mass balance equations to predict the amounts and compositions of matte, slag, and the off-gas stream.…”

Group Contribution Method-based Multi-objective Evolutionary Molecular Design

“…Lin et al studied the design of metal catalysts [15], numerous articles can be found for the design of drugs [5,[16][17][18], Perdomo et al designed and improved biodiesel fuel blends [3] and Kasat et al summarized the applications of genetic algorithms in polymer science including polymer design [2].…”

“…(1) from N 1 until N max as is given by Eq. (2) (N 1 is practically equal to at least 2, as no molecules consist of only one fragment). The sum of candidates is equal to…”

“…The search for compounds exhibiting the desired physical and chemical properties is of significant industrial importance in the search for different chemicals and materials such as polymers [1,2], blends [3], coatings, solvents, inert agents, heat transfer media [4], and drugs [5]. In the well-known technologies of the chemical, petrochemical, and pharmaceutical industries, the used medium for the given tasks has been developed via practical experience.…”