Jip J. Dekker

Jip J. Dekker
Monash University (Australia) · Data Science and AI

Doctor of Philosophy

About

7
Publications
371
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
22
Citations
Introduction
Jip is a OPTIMA research fellow based at Monash University's Faculty of Information Technology, in the Department of Data Science and Artificial Intelligence. His research focuses on programming languages and tools to model and solve combinatorial optimisation problems. In particular, his research has involved the improved implementation and optimisation of the MiniZinc constraint modelling language and the creation of advanced interfaces to different types of solving technologies.
Additional affiliations
October 2021 - present
Monash University (Australia)
Position
  • Research Associate
Description
  • OPTIMA Research Fellow working on the development of modelling techniques for optimisation problems and applications of discrete optimisation technology. The primary research objective is to improve the MiniZinc modelling language.
Education
September 2017 - July 2021
Monash University (Australia)
Field of study
  • Computer Science
September 2014 - February 2017
Uppsala University
Field of study
  • Computer Science
September 2011 - August 2014
Radboud University
Field of study
  • Computing Science

Publications

Publications (7)
Conference Paper
Full-text available
Boolean satisfiability (SAT) solvers have dramatically improved their performance in the last twenty years, enabling them to solve large and complex problems. More recently MaxSAT solvers have appeared that efficiently solve optimisation problems based on SAT. This means that SAT solvers have become a competitive technology for tackling discrete op...
Thesis
Full-text available
Constraint modelling languages are a prominent way to model and solve real world problems. They are used in areas such as scheduling, supply chain management, and transportation, among many others. The rewriting process of a constraint modelling language transforms a constraint model into a solver model, the input required by the program that solve...
Article
Full-text available
This paper describes the implementation of Nutmeg, a solver that hybridizes mixed integer linear programming and constraint programming using the branch-and-cut style of logic-based Benders decomposition known as branch-and-check. Given a high-level constraint programming model, Nutmeg automatically derives a mixed integer programming master proble...
Conference Paper
Full-text available
The combination of large neighbourhood search (LNS) methods with complete search methods has proved to be very effective. By restricting the search to (small) areas around an existing solution, the complete method is often able to quickly improve its solutions. However, developing such a combined method can be time-consuming: While the model of a p...
Article
Full-text available
A well-known and powerful constraint model reformulation is to compute the solutions to a model part, say a custom constraint predicate, and tabulate them within an extensional constraint that replaces that model part. Despite the possibility of achieving higher solving performance, this tabling reformulation is often not tried, because it is tedio...
Thesis
Full-text available
Constraint models often describe complicated problems that contain sub-problems that could be solved in sub-models. Although pre-solving these sub-models might improve the performance of the model, manually splitting the model to accommodate the occurrences of these sub-models can be a great inconvenience for the modeler. This thesis introduces an...
Thesis
Full-text available
Dealing with concurrency and parallelism is hard. Using scientific tools, models can be created giving insight into the nature of concurrent structures. Using these models one can sometimes even prove that various conditions hold within the model. To prevent human error when implementing a given model, one might consider a scheme where the source c...