D. Hemmi
Monash University,
Australia
Keywords: Constraint Programming, Optimisation, Operations Research, Material selection
Summary:
Designing chemical power plants to minimise their footprint is challenging due to the vast number of processing units. Similarly, creating an optimal production schedule for a manufacturing plant is nearly impossible for human operators. Many operational problems in modern industries are too complex to be comprehended and solved by humans. MiniZinc is a programming framework that allows to express operational challenges in a high level format. Once the problem is formalised, traditional Artificial Intelligence, such as search and backtracking based algorithms are used to find an optimal or near optimal solution to the specified problem. Challenges that can be formalised and solved using this AI based approach are; - increasing efficiency in logistics application, such as minimising cost of delivery - Prescriptive analytics based on predictive analytics - Optimally combining ingredients to obtain an improved compound subject to constraints - Scheduling and routing robots in a warehouse MiniZinc is already widely used in industry. However, our research team is continuously looking for new industry challenges to solve using MiniZinc and the AI based solvers that are also developed at Monash University.