Multi-Industry Staff Scheduling Under Labor Law Constraints Using MILP, CP and Genetic Algorithms

Gawade, Shraddha Shailesh (2025) Multi-Industry Staff Scheduling Under Labor Law Constraints Using MILP, CP and Genetic Algorithms. Masters thesis, Dublin, National College of Ireland.

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Abstract

Staff scheduling is always a difficult problem in any sector due to fluctuating demand, different shift patterns, and strict labor laws. This research developed an optimization framework that generates weekly roasters for staff using three different models: Mixed Integer Linear Programming, Genetic algorithm, and Constraint programming. The research integrated demand forecasting, availability of employees, and constraint formulation based on industry. The output was evaluated using nine different metrics which gave result in MILP having a good staffing demand but also it included overstaffing, CP assigned very few shifts indicated understaffing and GA gave a balanced and realistic staff schedule. The study concluded GA was the most compliant and scalable method for large multi domain staff scheduling tasks, while MILP exceeds demand fulfilling and CP is not capable of handling large data.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Sahni, Anu UNSPECIFIED
Uncontrolled Keywords:	Staff scheduling; multi-industry; optimization; MILP; CP; Genetic Algorithm; labor regulations
Subjects:	Q Science > QH Natural history > QH301 Biology > Methods of research. Technique. Experimental biology > Data processing. Bioinformatics > Artificial intelligence Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Artificial intelligence H Social Sciences > HD Industries. Land use. Labor > Issues of Labour and Work > Hours of Labour H Social Sciences > HD Industries. Land use. Labor > Issues of Labour and Work
Divisions:	School of Computing > Master of Science in Artificial Intelligence
Depositing User:	Ciara O'Brien
Date Deposited:	02 Sep 2026 09:08
Last Modified:	02 Sep 2026 09:08
URI:	https://norma.ncirl.ie/id/eprint/9754

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