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Optimization - Algorithms and Applications (Hardcover)
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Optimization - Algorithms and Applications (Hardcover)
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Choose the Correct Solution Method for Your Optimization Problem
Optimization: Algorithms and Applications presents a variety of
solution techniques 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 tabu search methods. The author shows
how to solve non-convex multi-objective optimization problems using
simple modifications of the basic PSO code. The book also
introduces multidisciplinary design optimization (MDO)
architectures-one of the first optimization books to do so-and
develops software codes for the simplex method and affine-scaling
interior point method for solving linear programming problems. In
addition, it examines Gomory's cutting plane method, the
branch-and-bound method, and Balas' algorithm for integer
programming problems. The author follows a step-by-step approach to
developing the MATLAB (R) codes from the algorithms. He then
applies the codes to solve both standard functions taken from the
literature and real-world applications, including a complex
trajectory design problem of a robot, a portfolio optimization
problem, and a multi-objective shape optimization problem of a
reentry body. This hands-on approach improves your understanding
and confidence in handling different solution methods. The MATLAB
codes are available on the book's CRC Press web page.
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