Abstract: The present invention provides a method and a system for train periodic message scheduling based on a multi-objective evolutionary algorithm, relating to the field of information and communications technology, mainly including: acquiring an MVB periodic message table; binary encoding the MVB periodic message table and initializing it randomly, to generate an iterative population; performing crossover and mutation operations on the individuals of the iterative population using a genetic algorithm, to update the iterative population; constructing an MVB periodic scheduling table that meets scheduling needs and minimizes the macro cycle according to a multi-objective algorithm and the updated iterative population; scheduling train periodic messages according to the MVB periodic scheduling table, thereby meeting the real-time requirement of periodic data transmission in actual scheduling scenarios.

Abstract: A dyeing color matching method and system based on a preference genetic algorithm includes: obtaining a reflectivity of a color scheme sample and a first color scheme set having N color schemes; initializing the first color scheme set using a preference genetic algorithm to obtain an initialized color scheme set; conducting crossover and mutation on any two color schemes in the initialized set to obtain a second color scheme set having 2N color schemes; substituting the color schemes in the second set into the conventional model to obtain 2N model reflectivities; determining a third color scheme set according to the 2N model reflectivities; determining whether a color scheme that satisfies a customer's requirement exists in the third set; if yes, conducting proofing on the color scheme to obtain a proofing color scheme set; and determining a color scheme with a minimum color difference according to the proof color scheme.

Abstract: The present invention provides a method and a system for train periodic message scheduling based on a multi-objective evolutionary algorithm, relating to the field of information and communications technology, mainly including: acquiring an MVB periodic message table; binary encoding the MVB periodic message table and initializing it randomly, to generate an iterative population; performing crossover and mutation operations on the individuals of the iterative population using a genetic algorithm, to update the iterative population; constructing an MVB periodic scheduling table that meets scheduling needs and minimizes the macro cycle according to a multi-objective algorithm and the updated iterative population; scheduling train periodic messages according to the MVB periodic scheduling table, thereby meeting the real-time requirement of periodic data transmission in actual scheduling scenarios.

Abstract: A dyeing color matching method and system based on a preference genetic algorithm includes: obtaining a reflectivity of a color scheme sample and a first color scheme set having N color schemes; initializing the first color scheme set using a preference genetic algorithm to obtain an initialized color scheme set; conducting crossover and mutation on any two color schemes in the initialized set to obtain a second color scheme set having 2N color schemes; substituting the color schemes in the second set into the conventional model to obtain 2N model reflectivities; determining a third color scheme set according to the 2N model reflectivities; determining whether a color scheme that satisfies a customer's requirement exists in the third set; if yes, conducting proofing on the color scheme to obtain a proofing color scheme set; and determining a color scheme with a minimum color difference according to the proof color scheme.