A Multi-Objective Model for Thesis Defence Scheduling

TL;DR

This paper introduces a comprehensive multi-objective mixed-integer linear programming model and a two-stage solution approach for thesis defence scheduling, addressing a less-studied but critical academic problem with real-world applicability.

Contribution

It presents a novel general model, new decision variables, and a two-stage solution method, including an augmented e-constraint approach and a new instance generator for thesis scheduling.

Findings

Successfully solved 96 instances of varying sizes.

The method finds optimal schedulable defences within time limits.

Provides diverse non-dominated solutions for decision-makers.

Abstract

We address the thesis defence scheduling problem, a critical academic scheduling management process, which has been overshadowed in the literature by its counterparts, course timetabling and exam scheduling. Specifically, the single defence assignment type of thesis defence scheduling problems, where each committee is assigned to a single defence, scheduled for a specific day, hour and room. We formulate a multi-objective mixed-integer linear programming model, which aims to be a general representation of the problem mentioned above, and that can, therefore, be applied to a broader set of cases than other models present in the literature, which have a focus on the characteristics of their universities. We introduce a new decision variable, propose constraint formulations that are not policy specific, and offer new takes on the more common objectives seen in the literature. We also include new objective functions based on our experience with the problem at our university. We also propose a two-stage solution approach. The first stage is employed to find the number of schedulable defences, enabling the optimisation of instances with unschedulable defences. The second stage is an implementation of the augmented e-constraint method, which allows for the search of a set of different and non-dominated solutions while skipping redundant iterations. A novel instance generator for thesis scheduling problems is presented. Its main benefit is the generation of the availability of committee members and rooms in availability and unavailability blocks, resembling their real-world counterparts. A set of 96 randomly generated instances of varying sizes is solved and analysed. The proposed method can find the optimal number of schedulable defences and present non-dominated solutions within the set time limits for every tested instance.