Filtering techniques for the intervention planning problems case of incident management in ITIL context

In the after-sales services management, and particularly customer interventions planning, artificial intelligence can play an important role in finding optimal solutions. Several works have been developed in this context, for example trying to transform the problem of planning interventions into a v...

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Bibliographic Details
Published in2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) pp. 308 - 313
Main Authors Ketata, Mounir, Loukil, Zied, Gargouri, Faiez
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2017
Subjects
Constraint optimization
COP
CSP
Filtering
Intervention planning
ITIL
Linear programming
Planning
Search problems
Transforms
Vehicle routing
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Summary:In the after-sales services management, and particularly customer interventions planning, artificial intelligence can play an important role in finding optimal solutions. Several works have been developed in this context, for example trying to transform the problem of planning interventions into a vehicle routing problem (VRP), or to transform it into a CSP, particularly for planning interventions in ITIL framework. However, solving these problems by classical CSP solvers still needs quite large time and we hardly need to optimize the search time by proposing specific heuristics or filtering rules. In this paper we propose to improve the CSP and COP models for the problem of planning interventions and to propose filtering rules in order to optimize the resolution time by reducing the search space. The experimental studies will be carried out with examples inspired by the incidents management in ITIL context.
DOI:10.1109/FSKD.2017.8393277