https://www.findaphd.com/phds/project/a ... y/?p105012
Pharmaceutical industries have great contribution to the economic development and human health. Most processes in pharmaceutical plants are batch processes. Scheduling is one of the important optimisation tools to improve their operational efficiency, reduce operating cost and improve profit margin. The operations in pharmaceutical plants often include production, cleaning, and maintenance. Scheduling of production operations in pharmaceutical plants are often separated from scheduling of their cleaning and maintenance operations, which will reduce their profit margin and result in orders unmet. Therefore, simultaneous optimisation of production scheduling and cleaning scheduling is very important. In this project, we will use advanced mathematical modelling approach especially mixed-integer programming approach to develop reliable and efficient mathematical models for this simultaneous optimisation. The solution approach combining deterministic approach and stochastic approach will be proposed to solve the model to near global optimality within reasonable computational time. During operations, some uncertainty often happens such as processing time variation, demand fluctuation, and product quality variation. The schedules based on deterministic parameters are often suboptimal or infeasible. In this project, we will apply robust optimisation techniques to obtain robust schedules with incorporation of different uncertainties in the operation.