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Design And Implementation Of Automatic Timetabling System

Posted on:2011-05-29Degree:MasterType:Thesis
Country:ChinaCandidate:F X LiFull Text:PDF
GTID:2178330332988235Subject:Software engineering
Abstract/Summary:PDF Full Text Request
With the rapid development of higher education, course arranging in the teaching affairs management system is playing a more and more importantly role. Scientific and effective automatic course arranging with computers is of the pressing requirement of colleges and universities, and meanwhile of vital theoretical importance.This thesis applies GA into course arranging system in the credit mode. Thorough analyzing the factors and constraints of course arranging, the thesis draws up the optimization·objective of course arranging, designs the encoding model which is suitable for genetic operation, and works out the calculation methods of rational fitness value. Moreover, an optimized course table is worked out through the constant evolution of selecting, recombining and mutating the initial colony. In designing the course arranging system, the thesis designs the classroom attempter algorithm, genetic filling algorithm, and detecting algorithm in arranging school schedule with object-oriented method, which achieves the final realization of course arrangement, implements the system testing with real data, and analyzes each parameter's effect on the genetic operation and its results.The testing results of the thesis based the real data and solving the target interval made of classroom utilization frequency, timetable goodness, curriculum time distribution uniformity degree, time-slice availability, and curriculum day combination goodness are both satisfactory. Aiming at the problems, the thesis intentionally explores the database design, accurately adjusts the system architecture and module division, and designs human-oriented menu. Customer-made, complete function and reasonable structure of the design embodies the planning of the system.
Keywords/Search Tags:Credit Mode, Course Arranging System, Genetic Algorithm, Multi-objective Optimization, Combination Optimization
PDF Full Text Request
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