5 CONCLUSION
Machine manufacturing is increasingly being used. In the new context of
mechanical engineering, many linear programming models can be
mathematically converted into standard models and can be used to solve
problems. In engineering, there is not only linear optimization with
continuous variables, but also linear optimization where all or some of
the variables are fixed. Due to standardization, serialization,
standardization, design, assembly and certification as well as objective
requirements, linear optimization problems are usually characterized by
hybrid discrete optimization. In this paper, we propose an improved
KarmarKar algorithm for linear optimization of hybrid machine technology
as an example, and extend the application of the improved KarmarKar
algorithm in in mechanical engineering. The continuous and rapid
development of information technology not only provides a broad
strategic platform and development prospects for countries around the
world, but also the wide application and development of mechanical
automation systems in the global machinery industry has undoubtedly
brought new vitality and valuable blood to them. Promote the competition
and cooperation of the whole manufacturing industry in the field of
machinery manufacturing and intelligent manufacturing.