| Περίληψη: |
Immersive exhibition spaces require layouts that support efficient circulation, clear wayfinding, balanced interaction, and comfortable environmental experience. However, exhibition layouts are often developed through manual design decisions, which makes it difficult to simultaneously evaluate route length, visual accessibility, crowding risk, environmental comfort, and interaction-node distribution. This study developed and evaluated a spatial-design optimization workflow based on adaptive simulated annealing with stage-dependent proposal selection and reheating control. A 36 m x 24 m immersive exhibition hall was constructed with six thematic zones, transition corridors, one rest area, and multiple interaction nodes. Three layout conditions were compared: manual layout, standard simulated annealing layout, and adaptive simulated annealing layout with reheating. The optimization model minimized a weighted spatial cost function that incorporated walking distance, visual accessibility, crowding, environmental comfort, and interaction balance. The selected layouts were implemented in virtual-reality exhibition scenes and evaluated through participant behavioral logs and post-experience ratings. The adaptive algorithm produced a lower final spatial cost, a higher improvement percentage, and fewer iterations to the best solution than standard simulated annealing, with a modest increase in computation time. Participants assigned to the adaptive layout reported higher satisfaction, stronger presence, clearer wayfinding, lower perceived crowding, and lower cognitive load, and they completed the route with shorter walking distance, fewer hesitations, longer dwell time, and broader heatmap coverage. These findings support the workflow as a decision-support approach for the tested exhibition scenario; they do not establish a universally optimal exhibition layout or superiority over all alternative metaheuristics. |