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Differential Evolution (DE), a population-based stochastic search technique is adept at solving real-world optimization problems. Unlike most population based algorithms, the use of DE is usually inexpedient in solving expensive optimization problems as the computational costs of these simulations are excessively high. This problem can be resolved by commingling surrogate model in DE that approximates...
In the evolutionary multi-objective optimization community, algorithm comparison is usually performed under the same population size. However, this is not always fair because its best specification is usually different in each algorithm. In many-objective optimization, the number of solutions to be found may depend on the situation. If the decision maker wants to analyze the entire Pareto front, thousands...
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