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[https://doi.org/10.1155/2022/7918323](https://doi.org/10.1155/2022/7918323)  \nResearch Article  \nAnalysis of College Course Scheduling Problem Based on Ant Colony Algorithm  \nRuqun Ge  and Jingyi Chen  \nHoHai University, Nanjing 211100, China  \nCorrespondence should be addressed to Ruqun Ge; [geruqun@163.com](geruqun@163.com)  \nReceived 14 June 2022; Revised 2 July 2022; Accepted 7 July 2022; Published 25 August 2022  \nAcademic Editor: D. Plewczynski  \nCopyright © 2022 Ruqun Ge and Jingyi Chen. ,is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.  \nAnt colony algorithm is a new evolutionary algorithm, which is gradually applied due to its easy robustness with other methods and excellent distributed computing mechanism. Currently, the application field ofant colony algorithm has been infiltrated by a single TSP problem. Ant colony algorithm moves the algorithm toward the optimal solution through the combination of positive feedback and negative feedback. ,is paper briefly analyzes the basic characteristics of the basic idea and principle of the ant colony algorithm to apply it to the ant colony problem. Abstract the course scheduling problem, transform the course arrangement problem into the maximum matching problem of solving the bipartite diagram, and discharge the high-quality curriculum that basically meet the needs.  \n1. Introduction  \n1.1. Background. Class scheduling problem is a typical multiobjective combination optimization problem involving a variety of factors [1–4] . We should not only consider the learning effect of students, but also take care of the reasonable work arrangement of teachers and make full use of teaching equipment [5] . Scheduling the class schedule is a very important and very complicated task for the university academic affairs office. Due to the large amount of courses in each school, manual scheduling will inevitably appear all kinds of conflicts, and its shortcomings are more and more prominent. With the development of computer science and technology, the use of computer scheduling will solve the disadvantages of manual scheduling [1, 6, 7] . It is the computer method of simulating the human brain with the computer, discussing the thinking law and the choice method of arranging the class schedule. Automatic class scheduling has the advantages of short class scheduling time, high quality, and manpower saving [8] . At present, the methods to solve the scheduling problem include genetic algorithm, expert system, binary graph and coloring theory, simulated annealing algorithm, backtracking method, and so on.  \nHowever, from the actual use situation, the developed class scheduling software is not generally practical. On the one hand, the class scheduling system is a very complex system, and it is very difficult to solve all the constraints and aspects. On the other hand, because every kind of school or even every school has its own particularity, it is difficult to use the class scheduling software widely. ,erefore, the current practice is still to develop a different class scheduling software for different types of schools and then take a separate manual adjustment method for inappropriate scheduling methods.  \n1.2. Analysis of Class Scheduling Problems  \n1.2.1. Five Elements of the Lesson Scheduling Problem.,e scheduling process involves the five elements of curriculum, teacher, class, classroom, and time, which are defined as the following set [9, 10]:  \n(1) Curriculum collection: O 􀂈 {O 1, O2, O3, . . ., OL}, where L is the number of courses offered.  \n(2) Teaching teacher collection: T 􀂈 {T1, T2, T3, . . ., TK}, where Kis the number of teachers taught throughout the school.  \n2 Computational Intelligence and Neuroscience  \n(3) Class collection: L 􀂈 {L 1, L2,","cbCaih5FberoiQtA","https://ap.wps.com/l/cbCaih5FberoiQtA","pdf",445409,"English","# Introduction\n## Background\n## Analysis of Class Scheduling Problems\n### Five Elements of the Lesson Scheduling Problem\n### Constraints for Class Scheduling Problems\n# An Overview of the Colony Algorithm\n## Basic Idea of the Algorithm","[{\"question\":\"Why is ant colony algorithm suitable for the college course scheduling problem?\",\"answer\":\"It is described as robust, easy to apply with other methods, and supported by an excellent distributed computing mechanism that helps guide the search toward optimal solutions.\"},{\"question\":\"How does the paper model the course scheduling problem?\",\"answer\":\"It transforms course arrangement into a maximum matching problem using a bipartite diagram representation.\"},{\"question\":\"What kinds of constraints are considered in the class scheduling formulation?\",\"answer\":\"The formulation includes hard constraints (e.g., one course per classroom at a time, teacher availability) and soft constraints (e.g., distributing classes across a week and arranging course types by time).\"}]","Analysis of College Course Scheduling Problem Based on Ant Colony Algorithm | PDF",23]