@Article{cmes.2022.022418,
AUTHOR = {Fangwei Zhang, Shihe Xu, Bing Han, Liming Zhang, Jun Ye},
TITLE = {Neutrosophic Adaptive Clustering Optimization in Genetic Algorithm and Its Application in Cubic Assignment Problem},
JOURNAL = {Computer Modeling in Engineering \& Sciences},
VOLUME = {134},
YEAR = {2023},
NUMBER = {3},
PAGES = {2211--2226},
URL = {http://www.techscience.com/CMES/v134n3/49746},
ISSN = {1526-1506},
ABSTRACT = {In optimization theory, the adaptive control of the optimization process is an important goal that people pursue. To solve this problem, this study introduces the idea of neutrosophic decision-making into classical heuristic algorithm, and proposes a novel neutrosophic adaptive clustering optimization thought, which is applied in a novel neutrosophic genetic algorithm (NGA), for example. The main feature of NGA is that the NGA treats the crossover effect as a neutrosophic fuzzy set, the variation ratio as a structural parameter, the crossover effect as a benefit parameter and the variation effect as a cost parameter, and then a neutrosophic fitness function value is created. Finally, a high order assignment problem in warehouse management is taken to illustrate the effectiveness of NGA.},
DOI = {10.32604/cmes.2022.022418}
}