No More Awkward Silences with Table Talk Tuning

Table Talk Tuning is a table-assignment problem drawn from a real wedding seating case. Alongside capacities, grouping and separation requests, table slack, and balance constraints, the model asks that every guest have at least one topic with enough support at their table to sustain a conversation.

The paper presents a MiniZinc model, three synthetic instance families from 10 to 150 guests, a reproducible benchmark pipeline, and a native Gecode model for comparing objective-aware search. The experiments show that the conversation terms still change the returned seatings in the paired ablation cases. The native experiments show that scalar, lexicographic, and sequential handling of the same objective hierarchy changes search behaviour.