Nurse scheduling is a critical task in healthcare management, which aims to ensure optimal allocation of nursing staff to meet patient care needs while considering several criteria. This study proposes a comprehensive multi-objective optimization approach to develop efficient nurse schedules. Initially, a mathematical model is formulated to include the various constraints and objectives associated with nurse scheduling. The primary objectives include minimizing the overall cost, maximizing nurse satisfaction, and ensuring compliance with other laws and policies of the hospital. To solve the multi-objective optimization problem, the Epsilon constraint method and the weighted sum method are employed separately to generate a set of a few Pareto-optimal schedules. These approaches allow for the identification of multiple solutions that balance the trade-offs between multiple conflicting objectives. Subsequently, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is utilized to rank these Pareto-optimal schedules obtained via the Epsilon constraint method. TOPSIS considers highly preferred criteria, such as nurse preferences, shift coverage, and workload distribution, to determine the most favourable schedule. The proposed methodologies are then compared before applying to a real-world hospital scenario, demonstrating its effectiveness in producing high-quality nurse schedules that enhance operational efficiency and staff satisfaction. This approach provides a robust decision-making tool for hospital administrators, contributing to improved healthcare service delivery and workforce management. The post-application survey of the hospital will validate the results regarding nurse satisfaction levels and patient care quality. The proposed Epsilon constraint methodology is found to be apparently more effective than weighted sum approach as well as traditional manual scheduling which was used prior in this hospital.