Enhancing the decision optimization of interaction design in sustainable healthcare with improved artificial bee colony algorithm and generative artificial intelligence.

ABSTRACT: With the development of digital health, enhancing decision-making effectiveness has become a critical task. This study proposes an improved Artificial Bee Colony (ABC) algorithm aimed at optimizing decision-making models in the field of digital health. The algorithm draws inspiration from the dual-layer evolutionary space of cultural algorithms, combining normative knowledge from the credibility space to dynamically adjust the search range, thereby improving both convergence speed and exploration capabilities. Additionally, a population dispersion strategy is introduced to maintain diversity, effectively balancing global exploration with local exploitation. Experimental results show that the improved ABC algorithm exhibits a 96% convergence probability when approaching the global optimal s

SUBMITTER: Yu S 

PROVIDER: S-EPMC11856313 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature