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We address this deficiency by using a heuristic approximate method together with the equations-based method in a two-stage procedure.
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To solve medium to large-sized problems, the well-known NSGA-II proposed by Deb et al. (2002) is improved by using a heuristic method in order to achieve good approximate Pareto-optimal frontiers.
Approximate optimal solutions are found using a heuristic approach called simulated annealing combined with pure random search that generates efficient initial solutions.
We carry out the normalization using a heuristic way.
Parsimony analyses were conducted using a heuristic search strategy.
The initial exam was further improved using a heuristic.
One thousandbootstrap replicates were computed using a heuristic search with the optimal criterion set to "parsimony".
PAUP* was used to generate a maximum parsimony phylogeny using a heuristic search algorithm.
Tantipathananandh et al. [27] used a heuristic to approximate the community detection for a more efficient algorithm.
We will use a heuristic to approximate this decomposition.
Instead we use a heuristic to approximate this decomposition.
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