Optimization Models for Personnel Scheduling

Personnel scheduling involves the systematic allocation of employees to shifts or tasks over a defined planning horizon, subject to legal, contractual and organisational constraints. Early approaches relied on manual or rule-based procedures, but the complexity of modern operations has driven the adoption of rigorous mathematical and computational models. Integer and mixed-integer linear programming formulations remain foundational for exact solutions in small to medium-scale settings, whereas meta-heuristic and hybrid techniques address the combinatorial explosion inherent in large or highly constrained instances. Recent trends emphasise multi-objective and stochastic frameworks that integrate employee preferences, dynamic adjustments for absenteeism and real-time demand fluctuations. The fusion of operational task scheduling with workforce rostering has further elevated solution quality by recognising interdependencies between staff allocation and underlying activities. These advances have yielded demonstrable benefits in healthcare, transport and energy sectors, improving service continuity, cost efficiency and worker satisfaction on a global scale.

Research from Nature Portfolio

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Research from all publishers

Recent studies have extended goal-programming methods to balance fairness and dynamic satisfaction in nurse scheduling by integrating lexicographic ordering with a time-adaptive satisfaction function, yielding schedules that accommodate both regulatory constraints and changing absenteeism patterns. In airport operations, an integrated task scheduling and personnel rostering model has been formulated as a mixed-integer linear programme enhanced by customised valid inequalities, enabling near-optimal solutions for large-scale ground staff allocation under real-world demand scenarios. A comprehensive survey of nurse rostering methodologies has catalogued the evolution of solution methods—ranging from pure meta-heuristics to matheuristics and hyper-heuristics—highlighting the rise of hybrid approaches and the need for standardised benchmark datasets to facilitate comparative assessment.

Optimization Models for Personnel Scheduling publication trend

The graph below shows the total number of articles in optimization models for personnel scheduling across all publications each year (not limited to Nature Index journals).

Technical terms

Personnel scheduling: The process of assigning staff members to work periods or tasks within a planning horizon, respecting multiple constraints.

Mixed-integer linear programming (MILP): An optimisation framework in which some decision variables are constrained to be integer, used to model discrete allocation decisions.

Goal programming: A multi-objective technique that minimises deviations from a set of predefined goals rather than optimising a single objective.

Meta-heuristic: A high-level strategy, such as genetic algorithms or simulated annealing, designed to efficiently explore large solution spaces for near-optimal solutions.

Hybrid approach: A method that combines different optimisation paradigms or heuristics to leverage their respective strengths and mitigate individual limitations.

References

1. An integrated Lexicographic goal programming and dynamic satisfaction function model for effective nurse scheduling. Decision Analytics Journal (2023).
2. Integrated task scheduling and personnel rostering of airports ground staff: A case study. Expert Systems with Applications (2024).
3. A Survey of the Nurse Rostering Solution Methodologies: The State-of-the-Art and Emerging Trends. IEEE Access (2022).