A Multi-Objective Optimization Framework and MCDM for Spectator Itineraries in Mega-Events with Concurrent Attractions

Mega-events with concurrent attractions create a script decision for each viewer: which sessions to watch within a budget of time, money, and travel effort.
We propose a two-stage framework that supports this decision and is reusable by smart cities to recommend customized itineraries during these events.
First, a mixed integer multi-objective program (MO-MIP) optimizes cost, attractiveness, and logistics using the multidirectional augmented Ɛ-constraint method (AUGMECON) with adaptive gap filling.
Then, a multicriteria decision-making layer (MCDM) ranks the resulting Pareto set via simple weighted sum (SAW) under three calibrated spectator profiles (Fanatic, Tourist, Economic).
We validated the framework in 671 sessions of the Rio 2016 Olympic Games distributed in five venue zones, generating 14 unmastered solutions from 216,095 feasible transitions.
The framework reports 83% top-rank agreement, compared to three MCDM baselines (AHP+TOPSIS, AHP+VIKOR, WS/MAVT).