Multi-objective Comprehensive Optimal Management of Construction Projects Based on Particle Algorithm

Abstract

Construction industry is one of the pillars of rapid economic development. The optimization of construction project management can greatly optimize the cycle, cost and quality of projects. In this paper, the multi-objective management optimization model of construction projects and the particle swarm optimization (PSO) algorithm for calculating the optimal solution of the model are briefly introduced, genetic operators are introduced into the PSO algorithm to prevent premature phenomenon, so as to improve the accuracy of the solution, and then case analysis is performed on a single-storey building project. The results show that the algorithm converges to stability and obtains the optimum solution set after 400 times of iterations and a total of 63250 seconds. The construction period of each process of the solution with the shortest total construction period in the optimum solution set is shorter than that before optimization, the total construction period reduces by 56 days, the total cost reduces by 520,000 yuan, and the total quality increases by 3.58. In summary, the improved PSO algorithm can effectively optimize the management of construction projects. Povzetek: Predstavljen je izboljšani algoritem na osnovi delcev in večkriterijske optimizacije za izboljšanje vodenja gradbeniških projektov.

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

“…This study evaluates the multi-objective optimization problem 33 . Based on the NSGA II algorithm, the MPGA is used for the investigation.…”