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Taking into account the equality constraints and embedding the information of infeasible points/chromosomes into the evaluation function, an extended fuzzy-based methodology and three new evaluation functions are proposed to formulate and evaluate the infeasible chromosomes.
Firstly, we describe evaluation functions using three constraints.
Also, the calibration and the measurement accuracy evaluation functions are discussed.
For comparison, we present results obtained using three types of evaluation functions.
The partitioning algorithm depends on the specific features used, and the similarity evaluation functions adopted.
It will also enable us to explore and quantify the way evaluation functions across contexts.
Then, we describe the analyzed ranking evaluation functions and also the employed image data sets.
Wu et al. ([7], pp. 688 689) describe two types of evaluation functions.
Fitness (or evaluation) functions are defined for both types of solutions.
During the evaluation process external factors, monitoring, and evaluation functions were considered.
Moreover, a technique based on Genetic Programming is proposed to generate approximated evaluation functions.
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