An Integer Linear Program for Periodic Scheduling in Universities
Sina Moradi

TL;DR
This paper introduces an Integer Linear Programming model for efficient, equitable, and practical scheduling of periodic meetings in universities, which can be adapted to various service scheduling scenarios.
Contribution
It develops a novel ILP model that incorporates real-world constraints for periodic scheduling, validated through numerical examples and a case study.
Findings
The model produces optimal schedules efficiently.
It accommodates diverse constraints like emergency slots.
Applicable to various service scheduling contexts.
Abstract
Efficient scheduling of periodic meetings is a critical challenge in various service-oriented domains, including academic settings, healthcare, and legal consultancy. This study presents a robust Integer Linear Programming (ILP) model to optimize the scheduling of faculty-student meetings. The proposed model incorporates practical constraints such as minimum intervals between consecutive meetings, differing time requirements for undergraduate, masters, and PhD students, and dedicated emergency time slots for unplanned visits. The objective function aims to achieve an equitable distribution of meetings throughout the planning period while prioritizing earlier time slots and seamlessly integrating emergency appointments. To validate the effectiveness of the model, both numerical examples and a case study are examined. The results highlight the ability of the model ability to generate…
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Taxonomy
TopicsScheduling and Timetabling Solutions · Scheduling and Optimization Algorithms
