Production planning and scheduling problems arise in many areas, from basic chemicals and consumer products to pharmaceuticals and specialty chemicals. Optimization based chemical production scheduling seeks to allocate limited resources to competing tasks over time. The key decisions include the selection and sizing of tasks (batches), the timing of tasks, and the assignment of tasks to equipment units. 

The objective function for chemical production scheduling depends on the production environment. Typical objective functions include the minimization of makespan, cost, or tardiness and the maximization of profit, or production volume.

The goal of our research is to address industrial scale problems by formulating mixed-integer programming (MIP) models that address current model limitations and develop advanced solution strategies. Furthermore, we aim to understand the characteristics of online scheduling, in which the schedule is regularly updated by repeatedly solving an optimization problem whenever a trigger event occurs and/or the scheduling horizon advances.