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Therefore, multi-objective optimization is called multi criteria optimization or vector optimization.
The performances are illustrated in the context of a multi criteria optimization: minimal length and minimal risk path planning.
Single criteria optimization of energy generation potential has been done to show and evaluate the effectiveness of the process in qualitative and quantitative manner.
Among a number of algorithms provided by optimization frameworks, Genetic Algorithms (GAs) have demonstrated their efficiency on single and multiple criteria optimization.
A bilateral method for multi-performance criteria optimization combines a gradient based method and the DSS to control dynamic state variables of SFJS concurrently.
In this study, the identification of potential cancer biomarkers from microarray data is casted as a multiple criteria optimization (MCO) problem.
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Non-preference multi-criteria optimization methods were used and the Pareto optimal set of efficient solutions was evaluated.
In this paper, non-preference multi-criteria optimization methods were used and the Pareto-optimal set of efficient solutions was evaluated.
We design algorithms that allow us to construct the set of Pareto optimal points (POPs) for a given decision table and the corresponding bi-criteria optimization problem.
This is a bi-criteria optimization problem.
The discovery problem is a bi-criteria optimization problem.
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