@inproceedings{9fb5e1608aea47109432ee2ec22389bc,
title = "A stochastic continuous optimization backend for minizinc with applications to geometrical placement problems",
abstract = "MiniZinc is a solver-independent constraint modeling language which is increasingly used in the constraint programming community. It can be used to compare different solvers which are currently based on either Constraint Programming, Boolean satisfiability, Mixed Integer Linear Programming, and recently Local Search. In this paper we present a stochastic continuous optimization backend for MiniZinc models over real numbers. More specifically, we describe the translation of FlatZinc models into objective functions over the reals, and their use as fitness functions for the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) solver. We illustrate this approach with the declarative modeling and solving of hard geometrical placement problems, motivated by packing applications in logistics involving mixed square-curved shapes and complex shapes defined by B{\'e}zier curves.",
author = "Thierry Martinez and Fran{\c c}ois Fages and Abder Aggoun",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; 13th International Conference on Integration of Artificial Intelligence and Operations Research Techniques in Constraint Programming, CPAIOR 2016 ; Conference date: 29-05-2016 Through 01-06-2016",
year = "2016",
month = jan,
day = "1",
doi = "10.1007/978-3-319-33954-2\_19",
language = "English",
isbn = "9783319339535",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "262--278",
editor = "Claude-Guy Quimper",
booktitle = "Integration of AI and OR Techniques in Constraint Programming - 13th International Conference, CPAIOR 2016, Proceedings",
}