This session delves into the cutting-edge techniques in soft computing, focusing on multi-objective evolutionary algorithms that tackle complex optimization problems with competing objectives. Explore the latest advancements in evolutionary strategies, genetic algorithms, fuzzy logic, and neural networks, and how they are combined to create robust, adaptive solutions across diverse domains such as engineering design, resource allocation, and machine learning. Attendees will learn how multi-objective evolutionary computing enables efficient trade-offs among conflicting goals, improving decision-making in uncertain and dynamic environments. Real-world case studies and algorithmic innovations will provide practical insights for researchers, practitioners, and students eager to push the boundaries of computational intelligence.