This Special Issue was inspired by the 11th International Workshop on Numerical and Evolutionary Optimization (NEO 2024), held from 3 to 6 September 2024 in Mexico City, Mexico, and hosted by Cinvestav. Solving real-world scientific and engineering problems has always been a challenge, and the complexity of these tasks has increased in recent years as more sources of data and information have been continuously developed. Thus, the design and analysis of powerful search and optimization techniques is of great importance. Two well-established fields that focus on this task are (i) traditional numerical optimization techniques and (ii) bio-inspired metaheuristic methods. Both of these general approaches have unique strengths and weaknesses, allowing researchers to solve certain challenging problems while failing to solve others. The goal of the NEO workshop series is to gather experts from both fields to discuss, compare, and merge these complementary perspectives. Collaborative work allows researchers to maximize the strengths and minimize the weaknesses of both paradigms. NEO also intends to help researchers in these fields to understand and tackle real-world problems like pattern recognition, routing, energy, lines of production, prediction, and modeling, among others.