The use of genetic algorithms (GAs) to evolve neural network (NN) weights has risen in popularity in recent years, particularly when used together with gradient descent as a mutation operator. However, crossover operators are often omitted from ...
The paper presents a study on the application of messy genetic algorithms for the winner determination problem in the combinatorial auction realm. Messy genetic algorithms operate explicitly on building blocks in order to obtain good solutions. Since ...
The scheduling and mapping of the precedence-constrained task graph to processors is considered to be the most crucial NP-complete problem in parallel and distributed computing systems. Several genetic algorithms have been developed to solve this ...
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