---
title: "Finding Diverse Solutions of High Quality to Constraint Optimization Problems"
authors:
  - "Thierry Petit"
  - "Andrew C. Trapp"
doi: ""
url: "https://ijcai.org/proceedings/2015/43"
pdf: "https://ijcai.org/proceedings/2015/0043.pdf"
venue: "Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence"
year: 2015
pages: "260-266"
track: "Main Track"
keywords:
---

# Finding Diverse Solutions of High Quality to Constraint Optimization Problems

Thierry Petit, Andrew C. Trapp

*Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence*, pages 260-266.

## Abstract

A number of effective techniques for constraint-based optimization can be used to generate either diverse or high-quality solutions independently, but no framework is devoted to accomplish both simultaneously. In this paper, we tackle this issue with a generic paradigm that can be implemented in most existing solvers. We show that our technique can be specialized to produce diverse solutions of high quality in the context of over-constrained problems. Furthermore, our paradigm allows us to consider diversity from a different point of view, based on generic concepts expressed by global constraints.