Multi-objective optimization of decoration engineering construction organization based on genetic algorithm

Abstract

Abstract Abstract：The comprehensive optimization of decoration construction organization is of great significance to rational construction and reduces the construction period and construction costs. Flow construction is an important approach for the optimization of construction decoration engineering; however, it has not been used in the multi-objective optimization of the construction organization in decoration engineering. Moreover, current researches on the multi-objective optimization of the construction organization in decoration engineering does not consider the dynamic situations in practice. Consequently, there exists a difference between optimization research and practice. Therefore, this paper presented a multi-population genetic algorithm (MPGA) for optimizing the construction sequence of orders placed by customers and realizing multi-objective optimization of the construction period, transportation costs, and delay time of decoration engineering. Furthermore, three dynamic scenarios were proposed, where in a new customer placed an order, a process delay occurred, and an emergency order was received; a dynamic multi-objective optimization algorithm was also designed to solve the target problem. The results of the case study revealed that the Pareto solution obtained by the MPGA could shorten the construction period, reduce transportation costs, and reduce labor delay times, as compared with those before optimization. Moreover, the MPGA could effectively solve the multi-objective optimization problem of a decoration engineering construction organization, serving as a reference for the development of algorithms to solve the construction management problem; this, in turn, can promote the reform and development of the construction industry in the intelligent era.