Course assignment problem with interval requested workload

Thipwiwatpotjana, Phantipa

doi:10.1109/norbert.2014.6893875

Cited by 4 publications

(5 citation statements)

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“…There have been some papers showing use of fuzzy preference in course assignment problem. A fuzzy example of membership for each preference description was presented in [1] and then [2] applied this fuzzy preference in the course assignment problem with interval workload data. Duan et al [3] used fuzzy synthetic decision making in genetic algorithm.…”

Section: Introductionmentioning

confidence: 99%

The Importance of Fuzzy Preference in Course Assignment Problem

Gorka¹,

Thipwiwatpotjana

2015

Mathematical Problems in Engineering

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This paper points out the importance of fuzzy preference by using a teaching course assignment problem as a case study. The model with fuzzy teaching preference provides a more satisfactory solution to a course assignment problem than assigning arbitrary weights. A method for improving a fuzzy membership function by using sensitivity analysis is devised. The method with fuzzy preferences is compared with a model using weighted probabilities.

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Section: Introductionmentioning

confidence: 99%

The Importance of Fuzzy Preference in Course Assignment Problem

Gorka¹,

Thipwiwatpotjana

2015

Mathematical Problems in Engineering

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“…The mentioned information in this section and the model study in the next section have cited from [18,17]. Firstly, we divide the teaching preference value into 6 ranks with different fuzzy values of ranks as presented in [18].…”

Section: Descriptions and Notation Of Course Assignment Problemmentioning

confidence: 99%

“…By following the idea of Leela-apiradee [16], we propose the characterization of these two solutions. By reviewing the research studies of Thipwiwatpotjana et al [17,18],…”

Section: Introductionmentioning

confidence: 99%

Tolerance-localized and control-localized solutions to system of interval linear equations

Burimas¹

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In this thesis, we are interested in a system of interval linear equations Ax=b whose coefficient A and right hand side b vary in some real intervals. We study two types of solutions called tolerance--localized and control--localized solutions of interval linear equations system. The characterizations of each solution are proposed in two main theorems. First, the proposed theorem is stated in terms of center and radius matrices which is directly proved by following their definitions. The other theorem is presented as magnitude sense with new notation. Based on the second theorem, the closed form of all solution sets is released. In addition, we apply the idea of tolerance--localized solution to deal with the course assignment problem. To optimize the preference and over/under workload of the instructors, we formulate the modified integer linear programming model to solve the problem. The obtained result is not significantly different from the original model. Moreover, we found that the obtained result gives higher overall preference of the instructors than actual course assignment in the 2nd semester of 2018.

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“…A. Odeniyi et al [13] Many researchers are interested in the university course schedule since there are many interesting points such as various constraints and objectives, and methods for finding the suitable solutions. Some research papers only deal with assigning courses to the suitable instructors such as [3], [14], and [16]. B. Domench and A. Lusa [3] present a mixed integer model for the instructor assignment problem by focusing on instructor's preferences.…”

Section: Literature Reviewsmentioning

confidence: 99%

“…B. Domench and A. Lusa [3] present a mixed integer model for the instructor assignment problem by focusing on instructor's preferences. P. Thipwiwatpotjana [14] concerns about an uncertainty information in term of interval requested workload. After that, [16] considers instructor fuzzy satisfaction in a teaching course assignment problem.…”

Section: Literature Reviewsmentioning

confidence: 99%

A two-stage model for balancing instructor workload and teaching preference in university course timetabling

Burana¹

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This thesis focuses on balancing instructor workload and maximizing preferences by using the data in the first semester of 2019 from Department of Mathematics and Computer Science, Faculty of Science, Chulalongkorn University as a case study. Since there are many instructors with over-workload in the department which directly affect their research qualities, balancing teaching workload is the main objective of this study. The proposed approach to balance workload is to split some basic courses into two parts: before midterm and after midterm and then assign each course to two instructors. Moreover, the preferences or the requests of teaching a course are important to maintain the instructor comfortable, and the preferences or the requests of teaching a course also help students to gain knowledge to their full potentials. The results show that our model is able to reduce both the number of instructors who have the high difference of requested workload and assigned workload, and the number of non-preferable courses for each instructor by comparing our results with the department timetable and the model without splitting courses.

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Course assignment problem with interval requested workload

Cited by 4 publications

References 5 publications

The Importance of Fuzzy Preference in Course Assignment Problem

The Importance of Fuzzy Preference in Course Assignment Problem

Tolerance-localized and control-localized solutions to system of interval linear equations

A two-stage model for balancing instructor workload and teaching preference in university course timetabling

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