A new polynomial-time algorithm for linear programming
Combinatorica
An extension of the Munkres algorithm for the assignment problem to rectangular matrices
Communications of the ACM
The Latex Companion
Selected topics on assignment problems
Discrete Applied Mathematics
Personnel assignment problem with hierarchical ordering constraints
Computers and Industrial Engineering
Balanced optimization problems
Operations Research Letters
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Students learn more effectively with personally meaningful tasks. Thus, students learn more if they have a say in deciding what specific topics and examples are being discussed in class. Naturally, the instructor knows what topics are important to cover in a course and which ones might be optional. Finding the right balance between students' preferences and the instructor's requirements is not so easy and thus may prevent this kind of shared control of the classroom from being realized. This article describes how the instructor's and students' interests can be used to generate a list of course topics that satisfies both parties. However, instead of adding technology to the classroom, technology is used to improve the classroom experiences. Specifically, it is shown how course topics can be assigned to specific students maximizing what is meaningful to the students and satisfies the course parameters as defined by the instructor. This problem can be formulated as a variation of the linear assignment problem and solved with a binary linear program. Results from actual and simulated courses are discussed and generalizations of the topic assignment problem presented.