基于JAVA的教务排课系统毕业设计英文文献翻译.docx

中北大学2014届毕业设计英文文献译文The Usage of Java Technology on Course Arrangement SystemComputer management system is an advanced modern management model, which aims to improve management efficiency and management level, the integration of resources, achieve economies. At home and abroad, computers have been widely used in various aspects, making the production, life more convenient, greatly improving the work efficiency, and gradually form a computer work-based, supplemented by relevant personnel work situation. With the development of computer technology, computer applications have penetrated into all walks of life, various industries differ only in the development and application of computer software for the degree.  Back in the late 1950s, people began to study abroad curriculum scheduling problem. In 1963, Gotlieb has proposed a mathematical model of curriculum issues, but because of course scheduling problems susceptible to practical problems, solving the result is not satisfactory. In the 1970s, as evidenced by the Americans S.Even etc. Scheduling problem is NP-complete problems, the time complexity of the algorithm grows exponentially. S.Even argument formalized academic status Timetable problem, the people arranging to raise awareness of the problem of theory. In addition, some literature attempts from the perspective of graph theory problem solving curriculum, but chromosome problem graph is NP-complete problem, only in very simple cases can be organized into a curriculum bipartite graph matching problem. At home, in the early 1980s, Chinese scholars began Timetable from analog hand, there are also constructed artificial intelligence expert systems, etc., representative are: Nanjing workers UTSS (A University Timetable Seheduling System) system, Dalian Intelligent teaching organization management and course scheduling system Polytechnic University. These systems are mostly handmade Timetable simulation process to "class" as a unit, the use of heuristic functions to choreography. But these Timetable Planning systems often rely on various teaching institutions, should not be a lot of promotion in.  University information along with the development of modern information technology, higher education according to their own development needs, through the use of advanced information technology to build digital campus, thereby improving management efficiency, strengthen the quality of teaching and promoting scientific research, improve service levels. "Education" is to ensure our long-term, stable and rapid development of strategic policy, education, information technology is an important means to achieve the strategic national policyThe main purpose of this project is to develop a Java-based Educational System Timetable, Timetable effectively improve the efficiency of the Registry. This issue requires the development of advanced technologies, to achieve one or more of the class curriculum management, generate class curriculum. System requirements have sufficient information, such as curriculum and classroom teachers related information, as well as class information class, classroom information. The main interface design concise, easy to operate. For different users set the appropriate permissions, users need to log in before they can carry out the appropriate action by login user name and password needed to ensure the management of safety. Set two levels of users, administrators and ordinary users, system administrators can operate the relevant data, while ordinary users can query information.The system will use java language to write, use MyEclipse as a development environment. JavaEE MyEclipse is a powerful integrated development environment, including a complete coding, debugging, testing, and publishing capabilities, you can take advantage of it in the database and JavaEE development, release, and integration advantages of the application server, greatly improve work efficiency .System is the most important thing is to process and manipulate data, and therefore the difficulty of dynamic website database connection is the most important part is the software design.The research is based on java Timetable academic system, in the design process, to be in the presentation layer to the Web page as a major client. Due to the advantages of the framework itself, making the system easy to maintain, strong scalability. Container is Apache Tomcat, threads solve the problem, making it possible to accommodate multiple users at the same time. Web layer which is mainly used as a user interface to access the system, providing a Web page server while connecting with the backend server, the client requests the transmission of information to the business layer, while the feedback information will be sent back to the client. View section using JSP.Background using SQL server as a database, it is more powerful features, in addition to handling included running on various platforms database management system kernel, but also includes data replication, database management systems, Internet gateways support, online analytical processing, multimedia support and a variety of parallel processing capabilities.With the popularization of information technology, computer technology has entered our educational administration departments at all levels, the traditional manual-type educational administration has been unable to meet the educational administrators, teachers and students needs. The endless variety of network applications, computer applications and influence in all spheres of society have already penetrated into every aspect of people's work and life. Web services have become a powerful tool in our work is indispensable, therefore, the effective use of the network to provide better service for students and teachers, is the bounden duty of the school. Using computer software system the curriculum tedious work, both to improve the quality and efficiency, but also reduce the burden for schools to make the modernization of educational management to a new level.University teachers arrangement system is a combination of problems, which consist of scheduling a set of courses within a given number of rooms and time periods. Solving a real world timetabling problem manually often requires a significant amount of time, sometimes several days or even weeks. Therefore, a lot of research has been invested in order to provide automated support for human timetablers. Contributions come from the fields of operations research and artificial Intelligence. This paper refers to terms and methods from constraint satisfaction. The methods presented were developed using constraint logic programming. Constraint logic programming combines the declarativity of logic programming with the efficiency of methods from operations research and artificial intelligence. It has recently become a promising approach for solving timetabling problems. Applying classical methods from constraint satisfaction requires to model the problem as a constraint satisfaction problem, a set of variables, each associated with a domain of values it can take on, and a set of constraints among the variables. Constraints are relations that specify the space of solutions by forbidding combinations of values.Methods include search, heuristics, and constraint propagation. Typically, systematic search assigns values to variables sequentially following some search order. If the procedure fails to extend a partial solution, decisions are undone and alternatives explored. Systematic search often relies on heuristics, which define the order in which variables and values are chosen. Constraint propagation is complementary; it simplifies a problem by identifying values that cannot participate in a solution. This way the search space gets pruned and search becomes easier. In practice, most constraint-based timetabling systems either do not support soft constraints or use a branch and bound search instead of chronological backtracking. Branch and bound starts out from a solution and requires the next solution to be better. Quality is measured by a suitable cost function that depends on the set of violated soft constraints. With this approach, however, soft constraints play no role in selecting variables and values.After collecting wishes of teacher and information on the new courses, a first proposal is developed with the timetable of the previous year as a starting point. This is done by using free slots in the timetable left by courses not taking place again for new courses offered by the same people, whereas wishes of teachers take precedence over the timetable of the previous year. After handing out the proposal to all teachers, evaluations and new wishes are collected. With the current proposal as a starting point, a new proposal is developed incorporating the responses on the current proposal, again changing as little as possible, and so on. Creating a new timetable is thus a multistage, incremental process. Relying on the timetable of the previous year and changing as little as possible by incremental scheduling drastically reduces the amount of work necessary for creating a new timetable and ensures acceptance of the new timetable by keeping the weekly course of events people are accustomed to. Note that the assignment of rooms is done elsewhere. Nevertheless, conflicting requirements for space or certain equipment may be a cause for changing the timetable. The general constraints are due to physical laws, academic reasons, and personal preferences of teachers: A teacher cannot be in two places at the same time, so avoid clashing the courses of a teacher. There should be at least a one hour break between two courses of a teacher.Some teachers prefer certain times or days for teaching.Monday afternoon is reserved for professors meetings: Do not schedule professors courses for Monday afternoon. The department consists of five units, each dedicated to a certain area of research. Most courses are held by members of a single unit while only a few courses are held by members of different units. Courses held by members of a certain unit must not clash with courses held by other members of the same unit.An offering typically consists of two lectures and a tutorial per week. There should be a day break between the lectures of an offering. The tutorial should not take place on a day, on which a lecture of the same offering takes place. All courses should be scheduled between9 a.m.and6 p.m. No lectures should be scheduled for Friday afternoon. No tutorials should be scheduled for late Friday afternoon.Only few of the courses are mandatory for and dedicated to students of a certain term, while most courses are optional and open to all students. For each term of the undergraduate studies there is a set of mandatory courses, the attendance of which is highly recommended. Courses of the graduate studies only rely on the knowledge provided by courses of the undergraduate studies. There is no recommended order of attendance. Undergraduate courses of a term must not clash, while undergraduate courses of different terms are allowed to clash. Graduate courses should not clash. First observations made clear that existing timetables do not meet the requirements stated, e.g., courses of a unit or graduate courses clash or a lecture of an offering and a tutorial of the same offering are scheduled for the same day. Furthermore, considering the number of graduate courses offered over the years, it became clear that there is too little space to schedule all graduate courses without clashes. This is due to the following reason. As mentioned before, undergraduate courses are mandatory and there is a recommended order of attendance. This way it is possible to distinguish students of the first term from students of the third term and students of the second term from students of the fourth term, which makes it possible to allow clashing of undergraduate courses of different terms. The graduate courses only rely on the knowledge provided by the undergraduate courses. There is no recommended order of attendance, thus making it impossible to distinguish students of the fifth term from students of the seventh term, which makes it necessary to disallow clashing of graduate courses in some way. So we faced two problems: The demand for incremental scheduling by basing the new timetable on the timetable of the previous year and changing as little as possible made it necessary to handle old timetables, which do not meet the requirements stated. From a schedulers point of view, the graduate studies lack structure taking freedom and leading to over constrained timetable specifications.Tackling the second problem by removing selected no-clash constraints turned out to be laborious and time-consuming and, therefore, impractical. Classifying graduate courses by contents and expected number of students and allowing clashing of courses of different categories won back some freedom, but it was not possible to identify enough categories in such a way that courses spread evenly over categories, which would have been necessary to prevent conflicts. It became clear that we were in need of some kind of weighted constraints able to express weak and strong constraints that are not mandatory.A Constraint Satisfaction Problem(CSP)consists of a finite set of variables, each associated with a finite domain and a finite set of constraints. A solution of a CSP maps each variable to a value of its domain such that all the constraints are satisfied. A partial constraint satisfaction problem(PCSP) is a CSP where each constraint is associated with a weight. A weight of a constraint expresses the importance of its fulfillment, allowing one to distinguish hard constraints from soft constraints. Hard constraints stand out due to infinite weights. The finite weights of soft constraints allow for the specification of preferences among constraints. A solution of a PCSP maps each variable to a value of its domain such that all hard constraints are satisfied and the total weight of the violated soft constraints is minimal.Clearly, we only need one variable for each course holding the period, the starting time point, it has been scheduled for. Each variables domain consists of the whole week, the periods being numbered from0 to 167, for example,9 denotes 9 a.m. on Monday, and so on. Requirements, wishes, and recommendations can be expressed with a small set of specialized constraints.No-clash constraints demand that a course must not clash with another one.Preassignment constraints and availability constraints are used to express teachers preferences and that a course must take place at a certain time.Distribution constraints make sure that there is at least one day between a course and another, or that two courses are scheduled for different days.Compactness constraints make sure that one course