Intelligent Timetabling System Based On The Linear Programming Models And Ant Colony Optimization

College Intelligent Timetabling System has its inherent complexity, its essence is a resource constraints and more assignment problem, need careful thought, study and constantly practice process. University Timetabling is one of the important link of the Teaching Operating Management, including five elements, those are teachers, classrooms, resources, class, and the time, and these resources are limited, how to layout good schedule with accurately reasonably, and fast, it has become a hotspot and difficulty problem in the University Management .This paper, starting from the universities themselves, and analyzed in the principles and Constraint Conditions, make sure that Timetabling System is more perfect and hummization. Through the design system Logical Model, analysis and provide System Function Module, to combined the Information Datum, define Difficulty Values to identify priority level of the course, so as to ensure that the system is Good Operation, meanwhile, design the system Database, and the Database information between various resources, facilitate the structure of the system application and the database information use efficiently.This paper introduces the design of system structure and module, by Unified Modeling Language to build Mathematic Modeling, analysis relationship between the five resources in order to Resources Settings, establish Linear Programming Model with Space Model auxiliary, make the model is more image and specific. On this basis, through the Variables and the Decision Variables of the choice, using Ant Colony Algorithm to a random search, according to the Objective Function of Linear Programming Model, place artificially ants, choose n Variables come into n level Decision Variables to Course Arrangement, and analysis the algorithm; At the same time, puts forward the ideological of Timetabling Template, to reduce unnecessary repetitive tasks, and improve the system operation speed; Through introducing the Fitness Function, provide the standard of judging system, and more efficient methods of handling problems. Experimental results show that the model can well expressed, Timetabling results show that the algorithm is effective.