Genetic algorithms in polymeric material production, design, processing and other applications: a review

摘要

Genetic algorithms (GAs) belong to the broader family of generic population based metaheuristic optimisation algorithms called evolutionary algorithms. These are one of the biology inspired computing techniques that emulate the basic Darwinian concept of natural selection. Because of their many positive attributes such as ease of use, versatility and robustness, GAs have become important in materials research very rapidly since their inception. Though going through a major stage of theoretical development, GAs have been successfully applied in many fields such as polymer production, polymer design, polymer processing, polymer laminates and other polymers, as well as non-polymer applications in recent times. The present review attempts to present the state of the art in this area. The review is broadly divided into three sections: fundamentals of GAs, the use of GAs in polymeric materials and the use of GAs in non-polymer applications. First, the fundamentals of GAs are presented to provide some glimpse of the technique; this is followed by presentations on applications of GAs in various polymeric fields, such as in polymer production, polymer scheduling, polymer design, polymer laminates and other polymer related applications and non-polymeric fields, e.g. metallic laminates and other metallic material applications. A thorough literature review and critical analysis of the review is provided and attempts have been made to portray how evolutionary optimisation techniques, GAs in particular, are used across a variety of applications.