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Course on Modeling & Solving Combinatorial Problems with MiniZinc
September 16, 2019 @ 10:00 - September 20, 2019 @ 12:00Free
By Guido Tack, Monash University, Australia.
Sponsored by CASTOR.
To sign up for this course, please RSVP with the “Confirm RSVP” button below (seats are limited).
Combinatorial Optimisation is a collection of techniques for solving hard, real-world problems, such as production scheduling, university timetabling, hospital staff rostering, and many other applications. All these techniques have in common that the real-world problem needs to be modelled, which means to express it in a formal, mathematical language. MiniZinc is a modelling language for optimisation problems. It supports high-level, structured modelling and can be compiled automatically for a variety of different algorithmic solving techniques, with support for Constraint Programming solvers like Gecode or Chuffed, Mathematical Programming solvers such as Gurobi, CPLEX or CBC, as well as SAT/SMT and Local Search approaches.
This course is an introduction to modelling with MiniZinc. The course is hands-on, with many exercises and worked examples, as well as an automatic system that gives students feedback on their modelling attempts.
- Basic modelling: variables, constraints, objectives
- Generic models: parameterised constraints
- Complex constraints: Boolean expressions
- Modelling functions: array access constraints
- Modelling patterns: regular expression constraints
- Symmetry breaking
The expected effort is around 40 hours (one week). There will be four lecture slots:
- Mon Sep 16, 10:00-12:00 Introduction: basic modelling in MiniZinc
- Mon Sep 16, 14:00-16:00 Parametric models, Boolean and functional constraints
- Wed Sep 18, 10:00-12:00 Modelling patterns, schedules and rosters
- Fri Sep 20, 10:00-12:00 Symmetry breaking; presentation of participant’s models; closing
And individual hands-on work (great fun!).
The course will be targeting PhD students, advanced master students, KTH staff & faculty, and staff from CASTOR’s industrial partners. The number of participants is capped at 40 attendants with a first-come first-served policy, where staff and doctoral students are given preference.
If there is sufficient interest, it will be possible to take this course as a 1.5 credit course on PhD level.
The lectures will take place at KTH premises in Kista, Kistagången 16.
- Room 308 on Monday and Wednesday,
- Room 205 on Friday.
Information about the lecturer:
Guido Tack is a Senior Lecturer at the Faculty of Information Technology, Monash University, Melbourne, Australia. He received his doctoral degree (Dr.-Ing.) from the Department of Computer Science, Saarland University, Germany. Before joining Monash University as a Lecturer and Monash Larkins Fellow in February 2012, he worked as a post-doctoral researcher at NICTA Victoria Laboratory (Melbourne, Australia), Saarland University (Germany), and K.U. Leuven (Belgium).
Guido’s research focuses on combinatorial optimisation, in particular translation of constraint modelling languages and architecture and implementation techniques for constraint solvers. He is the lead developer of the MiniZinc constraint modelling language and toolchain, a project that aims at making state-of-the-art optimisation technology easily accessible to a wide audience. MiniZinc has become a de-facto standard for modelling constraint problems and is widely used in academia and industry, with thousands of downloads of the software every month. Guido is also one of the developers of the popular Gecode constraint solving system, which has been integrated into many industrial solutions (such as SAP’s S/4HANA configuration engine).
Guido received Monash’s 2017 Dean’s Award for Excellence in Research Impact for his work on MiniZinc, and the 2010 ACP Doctoral Research Award for his work on Gecode.
To sign up for this course, please RSVP with the “Confirm RSVP” button below.