This book provides a balanced selection of both conventional
optimization algorithms and modern metaheuristic methods
commonly used in mathematical optimization. Conventional
algorithms include gradient-based methods such as the steepest
descent method, the simplex method for linear programming,
Lagrange multipliers, and Hooke-Jeeves pattern search.
Metaheuristic methods include ant colony optimization (ACO),
particle swarm optimization (PSO), simulated annealing (SA), and
Tabu search, recursive method for multiobjective optimization.
With dozens of worked examples and three Matlab/Octave
programs, this book can ideally serve as a textbook, especially
suitable for undergraduates and graduates.

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