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Pattern backtracking algorithm for the workflow satisfiability problem with user-independent constraints

Karapetyan, Daniel, Gagarin, Andrei and Gutin, Gregory 2015. Pattern backtracking algorithm for the workflow satisfiability problem with user-independent constraints. Presented at: FAW 2015: 9th International Workshop on Frontiers in Algorithmics, Guilin, China, 3-5 July 2015. Published in: Wang, Jianxin and Yap, Chee eds. Frontiers in Algorithmics: 9th International Workshop, FAW 2015, Guilin, China, July 3-5, 2015, Proceedings. Springer Verlag, pp. 138-149. 10.1007/978-3-319-19647-3_13

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Abstract

The workflow satisfiability problem (WSP) asks whether there exists an assignment of authorised users to the steps in a workflow specification, subject to certain constraints on the assignment. (Such an assignment is called valid.) The problem is NP-hard even when restricted to the large class of user-independent constraints. Since the number of steps k is relatively small in practice, it is natural to consider a parametrisation of the WSP by k. We propose a new fixed-parameter algorithm to solve the WSP with user-independent constraints. The assignments in our method are partitioned into equivalence classes such that the number of classes is exponential in k only. We show that one can decide, in polynomial time, whether there is a valid assignment in an equivalence class. By exploiting this property, our algorithm reduces the search space to the space of equivalence classes, which it browses within a backtracking framework, hence emerging as an efficient yet relatively simple-to-implement or generalise solution method. We empirically evaluate our algorithm against the state-of-the-art methods and show that it clearly wins the competition on the whole range of our test problems and significantly extends the domain of practically solvable instances of the WSP.

Item Type: Conference or Workshop Item (Paper)
Status: Published
Schools: Mathematics
Subjects: Q Science > QA Mathematics
Publisher: Springer Verlag
ISBN: 9783319196466
ISSN: 0302-9743
Date of First Compliant Deposit: 1 June 2016
Last Modified: 26 Jan 2018 14:28
URI: http://orca.cf.ac.uk/id/eprint/91297

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