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The B2B Scheduling Optimization Problem (B2BSOP) consists in finding an schedule of a set of meetings between pairs of participants, minimizing the number of idle time periods between meetings. Recent works have shown that SAT-based approaches are state-of-the-art on this problem. One interesting feature of such approaches is the use of implied constraints. In this work we provide an experimental setting to study the effectiveness of using these implied constraints. Since there is a reduced number of real-world B2B instances, we propose a random B2B instances generator, which reproduces certain features of the known real-world B2B instances. We show the usefulness of some implied constraints depending on the characteristics of the problem, and the benefits of combining them.
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