Sustainable Integral Optimization of Service Queues: A Human-Centered Approach Using IAM and SMAA

This paper contributes to queueing systems by introducing the concept of sustainable integral optimization, which integrates both quantitative and qualitative criteria, such as comfort, anxiety, and perceived service quality, into traditional performance metrics. We extend Kendall’s notation with a new element (G), focused on subjective sustainability indicators. The optimization process is conducted via the Integral Analysis Method (IAM), complemented by the SMAA framework for multicriteria decision-making. To demonstrate the applicability of the proposed approach, a case study in a high-end car dealership is developed. The goal is to address a persistent deficiency in queueing theory literature by incorporating human-centered sustainability principles, seeking a systemic balance between operational efficiency and user-oriented effectiveness in service delivery.