Expert-based sustainable investment strategies for SMEs with hybrid molecular fuzzy learning algorithms

The purpose of this study is to identify prior sustainable investment strategies for small and medium enterprises (SMEs) by proposing a hybrid molecular fuzzy decision-making model. First, q-learning algorithm is used to compute the weights of the experts. Secondly, selected criteria are evaluated by molecular fuzzy Bayesian networks-based weighting methodology. Finally, molecular fuzzy multi-objective particle swarm optimization technique is considered to prioritize sustainable investment strategies for SMEs. The findings indicate that environmental impact has the greatest weight. Also, this research highlights the importance of optimizing the operations with smart technologies as the most prior sustainable investment strategy for SMEs.