The Department of Statistics & Operations Research is organising a seminar for Friday 22 March at 12:00 in Lab Room 602 Maths & Physics Building.
The seminar is entitled 'Scheduling Pharmaceutical Quality Control Tests via Mixed Integer Programming'. The speaker is Ms Monique Sciortino
Abstract
Mixed integer programs capture the discrete nature of some decision variables and are thus widely applicable for solving real-world optimisation problems. This presentation shall delve into the general formulation of mixed integer linear programs and conditions that guarantee existence and uniqueness of optimal solutions. Mixed integer programs are most commonly solved by a technique called branch-and-cut, which shall be introduced.
A case study on scheduling quality control tests, within a local pharmaceutical company, will be discussed. Scheduling such tests is a very challenging task given the limited resource availability and the fact that a single product family must undergo multiple tests. Effective plans are thus essential for increasing efficiency of the laboratory and improving utilisation of resources. An original mixed integer linear programming model has been developed for scheduling these laboratory tests at the company and will be presented.
The proposed model has been implemented in GAMS and solved by GUROBI via a branch-and-cut solution approach. The model determines a schedule over a given planning horizon by minimizing the makespan. It encompasses constraints such as assignment constraints of different stages of tests to resources and timing constraints between tests pertaining to the same product family. Computational experiments were run on real data provided by the company over different planning horizons. The success of obtained results shall be reported.
Keywords: scheduling, mixed integer linear programming, optimisation, branch-and-cut algorithm
A case study on scheduling quality control tests, within a local pharmaceutical company, will be discussed. Scheduling such tests is a very challenging task given the limited resource availability and the fact that a single product family must undergo multiple tests. Effective plans are thus essential for increasing efficiency of the laboratory and improving utilisation of resources. An original mixed integer linear programming model has been developed for scheduling these laboratory tests at the company and will be presented.
The proposed model has been implemented in GAMS and solved by GUROBI via a branch-and-cut solution approach. The model determines a schedule over a given planning horizon by minimizing the makespan. It encompasses constraints such as assignment constraints of different stages of tests to resources and timing constraints between tests pertaining to the same product family. Computational experiments were run on real data provided by the company over different planning horizons. The success of obtained results shall be reported.
Keywords: scheduling, mixed integer linear programming, optimisation, branch-and-cut algorithm