Work

Pareto-optimal workforce scheduling with worker skills and preferences

Year: 2025

Type: article

Abstract: This paper addresses employee scheduling in service operations, considering various skill and skill levels and the fluctuating customer demand throughout the day and week. Employee shift and day-off preferences are also considered to enhance morale. We propose a two-stage integer programming model. In the first stage, the model optimizes the number of employees required for each shift period, ensuring uniform distribution of overstaffing to improve customer service. A Pareto frontier approach is applied between the two stages, offering decision-makers a set of non-dominated solutions that balance overstaffing and understaffing. The second stage uses the selected Pareto-optimal solution to assign shifts and day-offs to employees, incorporating their skills, preferences, and fairness considerations. Our model implicitly includes shifts and breaks, reducing decision variables and computational time. Using real data from a dining restaurant chain, we validate the model’s effectiveness in enhancing customer service and reducing labor costs by 12.3% compared to manual scheduling. Furthermore, productivity and employee satisfaction improve by considering individual skills and preferences.

Source: Operational Research

DOI: 10.1007/s12351-025-00903-7

Authors: Ali İşeri, Hatice Güner, Ali Rıza Güner

Institutions: Mudanya Üniversitesi, TC İstanbul Rumeli Üniversitesi

Language: English

Topic: Scheduling and Timetabling Solutions

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

SDG: Decent work and economic growth

Open Access status: hybrid

Estimated APC paid: $3,190