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The rebuilding phase of the structure optimization uses the optimally re-refined structure model and the accompanying ED maps.
The optimization uses a variant of the ant colony method.
The multi-objective optimization uses a hybrid Big Bang Big Crunch algorithm.
The optimization uses the FEM combined with the simplified conjugated gradient method (SCGM).
Bayesian optimization uses a probabilistic model of the objective function to guide the search for the optimum.
The clustering-based optimization uses an approximation to the actual cost of a routing solution without actual route construction.
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Solving large-scale global optimization using improved particle swarm optimizer (EPUS-PSO) [52].
The optimization used a linear cone programming approach [29] to identify optimal combinations of foods that satisfy the requirements.
Optimization using genetic algorithm.
Optimization using genetic algorithm. .
Fig. 16 Cost optimization using sensitivity analysis.
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