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Combining graph decomposition techniques and metaheuristics for solving PCSPs. Application to MI-FAP

Abstract : 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.
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https://hal.univ-lorraine.fr/hal-01784141
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Submitted on : Thursday, May 3, 2018 - 9:36:10 AM
Last modification on : Thursday, February 10, 2022 - 11:22:11 AM

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Lamia Sadeg Belkacem, Zineb Habbas, Wassila Aggoune Mtalaa, Fatima Benbouzid Si Tayeb. Combining graph decomposition techniques and metaheuristics for solving PCSPs. Application to MI-FAP. International Journal of Reasoning-based Intelligent Systems, Inderscience Enterprises Ltd, 2016, 8 (3/4), pp.104-118. ⟨10.1504/IJRIS.2016.082960⟩. ⟨hal-01784141⟩

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