scheduling

Scheduling is the process of planning and allocating resources over time to perform tasks. It involves deciding which tasks to execute when and on which resources, and estimating start and finish times. The goal is to optimize objectives such as minimizing makespan, reducing waiting times, maximizing utilization, and meeting deadlines or service levels.

Scheduling appears in many domains. In computing, CPU scheduling decides which process runs next. In manufacturing and operations research, production scheduling determines the timing of orders and machine usage. In project management, project scheduling defines a timeline with milestones. In workforce management, employee scheduling assigns shifts. Real-time scheduling focuses on meeting hard deadlines under timing constraints.

Common methods include Gantt charts and analytical techniques such as the critical path method and program evaluation and review technique. In production and services, Kanban supports flow. Classical computer science scheduling algorithms include First-Come, First-Served; Shortest-Job-First; Round Robin; and priority-based or multilevel queue scheduling. Resource leveling and capacity planning address limited resources and variability.

Key considerations include task precedence, resource constraints, setup times, and uncertainty. Performance is measured by makespan, lateness, throughput, utilization, and cycle time. Effective scheduling aligns with strategic goals, adapts to disturbances, and often uses forecasting and stochastic models to handle variability.

History and impact: Scheduling has been central to operations research since the mid-20th century, evolving from manufacturing into computing and project management. Modern approaches blend mathematical optimization with heuristic and data-driven methods to handle complexity and uncertainty in large-scale systems.