uncertain, the problem is much more complicated. In this paper, we modify a genetic algorithm to compute robust schedules when … genetic algorithm can find solutions that are robust with respect to both types of robustness. Moreover, the risk associated … with a specific solution can be easily evaluated. The modified genetic algorithm is applied to a just-in-time scheduling …

Monte Carlo simulations and compare the genetic algorithm with another technique, the iterative linear programming algorithm …

a simple dispatching heuristic as well as a more advanced genetic algorithm for the general model. Based on a tailored … results that suggest that the genetic algorithm is well suited for application in practice. …

transferring process using a genetic algorithm. In this process, it is found that the chromosome (the individual guanxi), crossover …

solution is demonstrated on the real problem. Finally, the genetic algorithm shows to be a very good option for network …

In this paper, an artificial neural network-based genetic algorithm (ANN-GA) model was developed for generating the …

objective function in Genetic algorithm approach. In comparison to previous works, the results have been noticeably improved … applying new coding approach in solving this problem. Therefore, running genetic algorithm only once for each case is …

through multi-objective genetic algorithm for this site and the influence of the load profiles on the optimal configuration …

properties are applied in MATLAB software to generate the objective function; furthermore Genetic Algorithm (GA) is used as an …