# Optimization Notes Hub > [!Note] > Hub consolidating notes on **Optimization** — continuous, linear, convex, > combinatorial, and metaheuristic methods. Reference: Boyd & Vandenberghe > (*Convex Optimization*), Nocedal & Wright (*Numerical Optimization*), > Wolsey (*Integer Programming*). ## 1. Foundations - [[Optimization Problem]] - [[Objective Function]] - [[Feasibility Region]] - [[Local vs Global Optimum]] - [[Convex vs Non-Convex Optimization]] --- ## 2. Continuous Optimization - [[Gradient Descent]] - [[Newton's Method]] - [[Quasi-Newton Methods]] - [[Conjugate Gradient]] - [[Lagrangian Multipliers]] - [[KKT Conditions]] --- ## 3. Linear and Convex Programming - [[Linear Programming]] - [[Simplex Method]] - [[Duality]] - [[Convex Optimization]] --- ## 4. Combinatorial Optimization - [[Combinatorial Optimization]] - [[Integer Linear Programming]] - [[Branch and Bound]] - [[Branch and Cut]] - [[Dynamic Programming]] - [[Bellman Equation]] - [[Combinatorial-planning-problem (CPP)]] --- ## 5. Metaheuristics - [[Simulated Annealing]] - [[Genetic Algorithms]] - [[Tabu Search]] - [[Particle Swarm Optimization]] - [[Ant Colony Optimization]]