Linear programming in machine buildingbased on KarmarKar
improvement algorithm in the context of new engineering
Lina Liu1 Liqing Su2* Sumin
Feng3
1Department of Aeronautical Engineering, Shijiazhuang
Engineering Vocational College, Shijiazhuang, Hebei 050061, China
2Department of Aeronautical Engineering, Shijiazhuang
Engineering Vocational College, Shijiazhuang, Hebei 050061, China
3Department of Aeronautical Engineering, Shijiazhuang
Engineering Vocational College, Shijiazhuang, Hebei 050061, China
Abstract: In the context of new engineering, the cultivation of
scientific and technological talents should fully consider new technical
qualities such as service to the country, innovation and progress,
formation of environmental awareness, and formation of international
vision. With the rapid development and progress of socialist market
economy, the scope of application of scientific and technological
revolution has been gradually expanded. The application of mechanical
engineering is getting wider and wider. Under the background of new
engineering education, in mechanical engineering, many linear
programming models can be transformed into standard models using some
mathematical methods, which can be used to solve them. In mechanical
engineering, there exist not only linear optimization problems with
continuous variables, but also linear optimization problems with all or
some variables as a set of deterministic values. Linear optimization
problems in mechanical engineering often manifest themselves as mixed
discrete optimization due to constraints of standardization,
serialization, standardization, design, assembly and verification, and
objective requirements. This thesis introduces the KarmarKar improvement
algorithm and extends the application of the KarmarKar improvement
algorithm in mechanical engineering with the example of hybrid linear
optimization in mechanical engineering.
Keywords: New Engineering; Mechanical Engineering; Linear
Programming; KarmarKar Improved Algorithm; Mechanical Engineering;
Linear Optimization; Planning Models