During this period, constrained and nonlinear optimization matured into practical, scalable methods. Interior-Point Optimization became a standard approach for large-scale linear and nonlinear programs, while exact Branch and Bound techniques extended solvability to bilevel and Stackelberg-type problems. Global Sensitivity Analysis promoted robust decision making, benchmarking ecosystems enabled reproducible evaluation of nonlinear optimization algorithms, and advances in program analysis, exemplified by Program Dependence Graph concepts, began to inform optimization-oriented reasoning in software design.