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The proposedalgorithm incorporates a genetic algorithm (GA) approach to assign a priority to each subtask while using a heuristic-based earliest finish time (EFT) approach to search for a solution for the task-to-processor mapping.
FORCE incorporates a genetic algorithm that finds optimal values for parameters automatically.
This method, widely used in prior research [ 25, 67- 69], incorporates a genetic algorithm and a ranking procedure to select nondominated solutions.
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In this view we propose to incorporate a genetic algorithm (GA).
Therefore, in the proposed work, a neuro-genetic algorithm has been designed and implemented by incorporating a genetic algorithm (GA) component into the ANN in the training phase.
This model goes beyond traditional mathematical programming by incorporating a genetic algorithm that is proven to be effective in dealing with the NP-hard problem.
In R-MGAPSO, the techniques of variable-length individuals and the local version of particle swarm optimization are incorporated into a genetic algorithm, where individuals with the same length constitute the same group, and there are multigroups in a population.
It builds on previous work by the authors in which IMs are incorporated in the formulation of a genetic algorithm (GA) multi-objective optimization problem to drive the design towards a solution which is 'balanced' in the importance values of the components.
The obtained collapse load factor is then incorporated into truss optimization using a Genetic Algorithm (GA) in order to generate truss structures which cannot only maintain load-carrying capacity under ordinary load conditions, but also avoid collapse under accidental load conditions such as an extremely large earthquake.
The proposed method incorporates the Finite Element simulations into a Genetic Algorithm framework that aims to yield a multi-material part, with the minimum possible weight, whilst satisfying the imposed design requirements.
The multi-objective optimization was carried out by using a genetic algorithm (GA) incorporating Pareto optimality criterion.
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