Combining graph decomposition techniques and metaheuristics for solving PCSPs. Application to MI-FAP
Authors
L. Sadeg-Belkacem, Z. Habbas, W. Aggoune-Mtala, and F. Benbouzid-Si Tayeb
Reference
International Journal of Reasoning-based Intelligent Systems, vol. 8, no. 3-4, pp. 104–118, 2016
Description
This paper presents a study towards a framework for solving discrete optimisation problems modelled as partial constraint satisfaction problems (PCSPs). These studies follow two approaches, namely a bottom-up, and a top-down one. Three decomposition methods and an adaptive genetic algorithm (AGA) are associated with these approaches. The experimental results obtained for MI-FAP problems show a good trade-off between the quality of the solution and the execution time of the different algorithms.
