
Optimization: Algorithms and Applications presents a variety of solution tech-
niques for optimization problems, emphasizing concepts rather than rigorous
mathematical details and proofs.
The book covers both gradient and stochastic methods as solution techniques for
unconstrained and constrained optimization problems. It discusses the conjugate
gradient method, Broyden–Fletcher–Goldfarb–Shanno algorithm, Powell method,
penalty function, augmented Lagrange multiplier method, sequential quadratic
programming, method of feasible directions, genetic algorithms, particle swarm
optimization (PSO), simulated annealing, ant colony optimization, and ...