Balancing Diversity and Consensus: Intelligent Support Systems for Group Decisions  

•  In complex decision environments, group decision-making (GDM) often leads to more informed and balanced outcomes than individual decisions, as it leverages the diversity of knowledge, perspectives, and expertise among stakeholders. However, this diversity also introduces significant challenges in achieving consensus, as participants may have conflicting objectives, priorities, or preferences. To address this issue, this research develops decision support systems (DSS) grounded in multi-criteria decision-making (MCDM) and optimization techniques to facilitate conflict resolution and consensus formation in group decision processes. The proposed frameworks model stakeholder preferences, quantify trade-offs across multiple criteria, and employ optimization-based consensus mechanisms to guide groups toward mutually acceptable solutions. From a managerial and practical perspective, these tools enhance transparency, fairness, and collaboration in multi-stakeholder decision contexts—ranging from policy development and infrastructure planning to organizational strategy—ultimately leading to more robust and widely supported decisions.