Abstract

Building information modeling technology creates and utilizes digital models for the design, construction, and operation management of projects", organizing various building information into a whole. The algorithms of each era are limited by the level of research at that time: the first generation The problem faced by the evolutionary multi-objective optimization algorithm is how to combine the evolutionary algorithm with the multi-objective optimization problem organically. How to deal with the problem of high-dimensional multi-objective optimization. Evolutionary multi-objective optimization has developed to the present, and gradually shows the characteristics of diversity. In the process of single-objective optimization, when the fitness value of individuals in the population does not increase within a certain algebra, it can be It is determined that the algorithm can be stopped. This stopping strategy cannot be simply applied to multi-objective optimization. Finally, the superiority of the algorithm in this paper is obtained.

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