Lev Kazakovtsev, Elena Kovlovskaya, Ivan Rozhnov, Olga Patsuk

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We propose a modification to the genetic algorithm with greedy agglomerative crossover operator for the problem of scheduling product types at the facilities of the metal or plastic production factory where the goal is to minimize the number of switchings of the product type of the production lines. Similar algorithms with greedy agglomerative crossover for location problems do not use any elitism in the population. For the considered problem which may also be classified as a location problem, elitism in the population implemened in the form of tournament selection plays a positive role.  The article also discusses the dependence of the efficiency of the evolutionary algorithm on the size of the population.   As our experiments show, the introduction of elitism into such an algorithm enables us to increase both the rate of convergence of the algorithm and the accuracy of the solution. A special aspect chooses an individual with the best value of the objective function.


genetic algorithm, greedy crossover, location problem.

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DOI: https://doi.org/10.22190/FUMI220731068K


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