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In the paper, the complete set of solutions is provided for 6- and 7-ply laminates, and the methodology to find solutions for a higher number of layers is presented.
As a single trace can represent a big number of solutions, by enumerating traces we can generate a set much smaller than the complete set of solutions.
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With the objective of calculating alternative evolutionary scenarios for big permutations, we developed three different algorithms that perform a partial enumeration of the complete set of solution traces of a given permutation.
Before introducing the algorithms for partial enumeration of traces, in this section we make a quick presentation of the algorithms which were designed for the enumeration of the complete set of solution traces.
The most feasible SMILEY solutions out of the complete set of 1176 solutions were investigated in more detail.
To obtain these results, we identified 25 regions of a 6-parameter space in which the complete set of analytic solutions are explicitly obtained.
The Pareto front is a key concept in resolving a MOOP, and it is associated with the complete set of optimal solutions.
Algorithms for enumerating the complete set of traces of solutions were developed.
An approximation of the complete set of all best solutions, known as the Pareto optimal or non-inferior set, is derived by a special version of a multi-objective genetic algorithm (MOGA).
Multi-Objective Evolutionary Algorithms based on the principle of Pareto optimality are designed to explore the complete set of non-dominated solutions, which then allows the user to choose among many alternatives.
Since it is difficult to obtain the complete set of weak Pareto optimal solutions, we explored the approximate set of weak Pareto optimal solutions in the RNA inverse problem by using a framework of MOGA.
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CEO of Professional Science Editing for Scientists @ prosciediting.com