The Research Of Multi-objective Trade-off Optimization Based On Learning Effect In Repetitive Project

The research of multi-objective optimization of construction projects has been the hottest and difficult issues in engineering.With the great emerging of subway projects,highways,high-rise buildings,repetitive projects are gaining more attention.Large number of manual operations are included in repetitive projects and works in these projects are usually operated from unit to unit,which,establish the foundation for the appearance of learning effect.At present,few paper in China considers and takes advantage of learning effect in research.This paper introduced learning effect into the multi-objective trade-off optimization in repetitive project and proposed a new trade-off optimization model.The main research contents of this paper are as follows,(1)The necessary conditions for occurring learning effect is summarized through reviewing literature and consulting.Then,based on the construction practice in China,basic data in eleven projects are collected to develop the empirical study of learning effect in China.The fact that there indeed exists learning in Chinese construction projects is specified.According to these basic data,learning rates of all works are calculated.Moreover,the learning curves plotted by Origin9.0 can be divided into two stages,namely,downward stage and stable stage.Based on this result,a two-stage learning curve model is proposed.Calculation on correlation coefficient,absolute percent error and paired sample test verified that the improved model has superior predictive performance.(2)Calculation formula of duration in repetitive project is firstly specified,then learning effect is introduced to analysis the relationship between time and cost,time and quality.Further,this paper developed a multi-objective trade-off optimization model based on learning effect in repetitive projects.The two-sides characteristic of learning effects is revealed in this model.That is,learning effect brings positive influence to objective while also has negative impact.Thus,learning effect is a double-edged sword and managers should not improve the objectives’ performance through overemphasizing learning effect in application.(3)The random mutation operation is introduced into adapt grid particle swarm optimization algorithm and an improved adapt grid particle swarm optimization algorithm is developed to solve the multi-objective optimization model of the repetitive project.The random mutation operation is recommend to improve the global and local searching ability of the algorithm.Simulation experiments on multiple objective standard test functions prove that the improved algorithm has better convergence and distributivity.(4)The application of the multi-objective trade-off optimization model based on learning effect and improved algorithm is carried out in Chongqing high-rise building as case study.The application research of this case study testifies the rationally and operability of this improved model and algorithm.The necessity of taking learning effect into account during multi-objective trade-off optimization in repetitive projects is demonstrated through comparing above calculation results to results without consideration of learning effect.Moreover,the differences of objective between results are analysised detailed to reveal how learning effect influence objectives.This paper considers the influence of learning effect to each objective and verifies its two-sides characteristic through theoretical research and case application.These research results lay foundation for the rational use of learning effect in practical projects.