Design optimization is an engineering design methodology using a mathematical formulation of a design problem to support selection of the optimal design among many alternatives.
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Continuous Optimization.
Bound Constrained Optimization.
Constrained Optimization.
Derivative-Free Optimization.
Discrete Optimization.
Global Optimization.
Linear Programming.
Nondifferentiable Optimization
Optimization methods are used in many areas of study to find solutions that maximize or minimize some study parameters, such as minimize costs in the production of a good or service, maximize profits, minimize raw material in the development of a good, or maximize production.
Design optimization involves the following stages:
Variables: Describe the design alternatives
Objective: Elected functional combination of variables (to be maximized or minimized)
Constraints: Combination of Variables expressed as equalities or inequalities that must be satisfied for any acceptable design alternative
Feasibility: Values for set of variables that satisfies all constraints and minimizes/maximizes Objective.
Application
Design optimization applies the methods of mathematical optimization to design problem formulations and it is sometimes used interchangeably with the term engineering optimization. When the objective function f is a vector rather than a scalar, the problem becomes a multi-objective optimization one.
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