Research On Multi-objective Optimization Of Green Construction Project Based On Improved Particle Swarm Optimization

According to the sustainable development strategy,green construction will be the development direction of building construction.Compared with the traditional construction technology,the green construction considers the green environmental factors,and pays more attention to the protection of environment.And the multi-objective management of traditional construction projects only considers the three goals that are the construction schedule,cost and quality.However,in the advocacy of low-carbon economy,the multi-objective management of traditional construction projects needs to be improved to meet the demand of modern construction industry development.Therefore,the multi-objective management of green construction projects is to increase the environmental objective on the basis of multi-objective management of traditional construction projects,which meets the requirement of sustainable development strategy and promotes the development of green construction.Nowadays,people pay more and more attention to the multi-objective optimization of construction schedule,cost,quality,environmental protection,etc.This paper mainly studies the multi-objective optimization of green construction projects.Based on the studies of multi-objective management of traditional projects,the environmental objectives,schedule,cost and quality are combined to form the multi-objective management system of green construction projects.By analyzing the relationship of the goals in the green construction project,the paper uses the marginal utility decreasing theory and reasonable assumptions to establish the function expressions of schedule-cost,schedule-quality and schedule-environmental protection.And the multi-objective optimization model of the green construction projects is built.There are many methods to solve the multi-objective optimization problems.Nowadays,intelligent algorithm is the most widely used in the application of the multi-objective integrated optimization problems,and now has become a hot topic.This paper introduces particle swarm optimization(PSO)and genetic algorithm(GE),which are commonly used in the multi-objective optimization problems.Based on the analysis of the principles,algorithm flow,advantages and disadvantages of PSO and GE,the former is easy to fall into the local optimal solution in the process of optimization.Therefore,this paper adds the selection operator,crossover operator and mutation operator of the genetic algorithm to the particle swarm optimization.And this improved particle swarm optimization(IPSO)can avoid prematurity effectively and escape from local optimum,which is proposed to improve the global convergence of the algorithm.At the end of the paper,the multi-objective optimization model of the green construction projects and the improved particle swarm optimization are applied to a concrete example.The algorithm is programmed with MATLAB software to solve the model.And the optimal state of environmental protection,schedule,cost and quality of green construction project is showed in the results.Meanwhile,the effectiveness and rationality of the improved particle swarm optimization is also verified.