Linear Programming Processivity and Structural Optimisation of Intelligent Systems

Abstract

The factor space theory of causal analysis and factor manifolds is essentially an optimisation problem in the application of intelligent systems and is closely related to linear programming. In this paper, based on the organic combination of factor space theory and the linear programming prism cut algorithm, we propose a procedural expansion model of linear programming, which proceduralises the solution method of linear programming by transforming the background relations or conceptual backgrounds with convexity into a set of restricted surfaces with the continuity method of the factor phase domain. The one-time solution is turned into an approximate optimisation-seeking process, and then this processisation is transferred to the framework of the factor space so that the processisation algorithm of linear programming can become a computational tool for the restructuring of intelligent systems.

Keywords

• factor space
• linear programming
• non-optimal theory
• intelligent optimisation
• structural adjustment