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Article Dans Une Revue Journal of Network and Computer Applications (JNCA) Année : 2012

Distributed constraint optimization with MULBS: A case study on collaborative meeting scheduling

Résumé

This paper introduces MULBS, a new DCOP (distributed constraint optimization problem) algorithm and also presents a DCOP formulation for scheduling of distributed meetings in collaborative environments. Scheduling in CSCWD can be seen as a DCOP where variables represent time slots and values are resources of a production system (machines, raw-materials, hardware components, etc.) or management system (meetings, project tasks, human resources, money, etc). Therefore, a DCOP algorithm must find a set of variable assignments that maximize an objective function taking constraints into account. However, it is well known that such problems are NP-complete and that more research must be done to obtain feasible and reliable computational approaches. Thus, DCOP emerges as a very promising technique: the search space is decomposed into smaller spaces and agents solve local problems, collaborating in order to achieve a global solution. We show with empirical experiments that MULBS outperforms some of the state-of-the-art algorithms for DCOP, guaranteeing high quality solutions using less computational resources for the distributed meeting scheduling task.

Dates et versions

hal-00849849 , version 1 (01-08-2013)

Identifiants

Citer

Fabrició Enembreck, Jean-Paul Barthès. Distributed constraint optimization with MULBS: A case study on collaborative meeting scheduling. Journal of Network and Computer Applications (JNCA), 2012, 35 (1), pp.164-175. ⟨10.1016/j.jnca.2011.02.016⟩. ⟨hal-00849849⟩
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