This chapter explores the challenges in applying optimization techniques to real-world decision-making projects. While many such challenges can be modeled as mathematical problems, practical implementation often faces obstacles due to the complexity of real-world scenarios. We propose three novel optimization problems that address practical issues: high-performance but opaque algorithms, practitioner’s tacit knowledge, and consensus among practitioners. These aim to bridge the gap between theoretical research and real-world applications. For each proposed problem, we discuss potential algorithmic strategies.