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An optimization problem for multiple objectives is called a multi-objective optimization problem.
Designing of QoS routing protocols, which optimize the multiple objectives is computationally intractable.
Building optimization involving multiple objectives is generally an extremely time-consuming process.
The genetic algorithm that is effective in accomplishing multiple objectives is used to optimize the fuzzy model predictive controller.
A control system design procedure based on the optmllsation of mUltiple objectives is used to address the control design requirements of a simulated gasification plant.
The robust optimization of multiple objectives is introduced to identify robust parameter settings with high dimensional accuracy and high yield rates for molded gears despite process parameter deviations.
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In the first stage, multiple objectives are combined via the multiplication of the relative measure of each objective.
Multiple objectives are considered in these design problems.
Examples include reducing power consumption, maximising IP revenue and combined where multiple objectives are sought.
Various optimization algorithms appropriate for dealing with single and multiple objectives are described.
Then, the multiple objectives are aggregated into a single global index with a minimization rule.
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