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Handbook of Simulation Optimization
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where f is the objective function, x represents the decision variables, and Θ is the feasible region or constraint set. All of the chapters with the exception of the final one basically address this problem in some form. As in the deterministic optimization domain, one dichotomy is whether the decision variables are discrete (ordered or unordered, finite or infinite) or continuous, or a mixture of the two. Most real-world simulation optimization problems have multiple objectives. Although this handbook focuses on the case of a single objective function, this (generally nonlinear) function could be understood as having already subsumed competing objectives through an appropriate combination or having moved all other objectives to the constraints in the constrained optimization setting (discussed in many of the chapters, but see especially
Michael C. Fu - Personal Name
1st Edtion
978-1-4939-1383-1
NONE
Handbook of Simulation Optimization
Management
English
Springer Science Business Media New York
2015
London
1-400
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