THEORETICAL ASPECTS REGARDING ARTIFICIAL INTELLIGENCE ALGORITHMS USED IN SERIAL PRODUCTION PROGRAMMING

Abstract

Artificial intelligence is a relatively new field of computer science that has evolved rapidly in recent years from the stage of laboratory research to that of the field with various spheres of applications. There is currently a whole set of techniques that allow the construction of programs and artificial intelligence systems, systems considered commercial products, successfully applied in the field of mass production. The purpose of this article is to provide a theoretical picture of the artificial intelligence algorithms used in serial production programming. Current research trends in mass production planning are oriented towards the adoption of hybrid techniques, based on specific algorithms of artificial intelligence, which try to combine the advantages of local search strategies (such as optimization by the ant colony model - Ant Colony Optimization, optimization by the particle set model - Particle Swarm Optimization , Genetic algorithms) with those of global search (such as Simulated annealing), in order to determine those optimal and efficient solutions in the case of mass production scheduling.