Application of Integer Linear Programming in Workforce Scheduling: Evidence from ABInBev (International Breweries Port Harcourt) Logistics Facility

Abstract

This study investigates the utilisation of Integer Linear Programming (ILP) to enhance workforce scheduling at the ABInBev (International Breweries Port Harcourt) Logistics Facility, characterised by high demand and heavy shift labour. In these situations, traditional manual scheduling methods typically cause problems including wasted labour, tired employees, irregular shift coverage, and higher operating costs. To solve these problems, a 0–1 ILP model was designed to find the best way to allocate personnel to shifts while still meeting operational, regulatory, and fatigue-related needs. The model takes into account the availability of workers, the demand for shifts, the skills needed, and labour laws to come up with the best timetable. Results, based on realistic operational assumptions, show that workforce utilisation will go up by 15–20%, labour expenses will go down by 12–18%, and fatigue-related workload concentration will go down by 25–30%. Operations will also be more responsive. The results show that ILP is a strong, data-driven way to schedule workers and can help make brewery and fastmoving consumer goods logistics operations in Nigeria more efficient, safe, and resilient.