Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning introduces the evolving area of static and dynamic simulation-based optimization. Covered in detail are model-free optimization techniques - especially designed for those discrete-event, stochastic...

Basic Principles -- Schema Theory -- No Free Lunch for GAs -- GAs as Markov Processes -- The Dynamical Systems Model -- Statistical Mechanics Approximations -- Predicting GA Performance -- Landscapes -- Summary.

Scatter Search -- Experiments Using Scatter Search for the Multidemand Multidimensional Knapsack Problem -- A Scatter Search Heuristic for the Fixed-Charge Capacitated Network Design Problem -- Tabu Search -- Tabu Search-Based Metaheuristic Algorithm for Large-scale Set Covering Problems --...