Research On Time-cost Trade-off Problem For Repetitive Projects Based On Improved Nsga-Ⅱ

In order to become a "powerful country in transportation",a large number of repetitive projects,such as highway and railway projects,are currently under construction or are about to be under construction in China.In the face of such large-scale and high-investment construction projects,reasonable,scientific and efficient Construction schedule management is the key to its high-quality development.The purpose of this paper is to focus on the timecost trade-off problem of repetitive projects(TCTPRP),improve the mathematical expression and constraint system of the model,and design a multi-objective intelligent optimization algorithm that can solve large-scale TCTPRP problems.The main research work includes:Firstly,sorted out and summarized the basic principles of existing project planning methods and their advantages and disadvantages in repetitive projects,and choose repetitive project modelling(RSM)as the schedule method and research basis of this paper.Based on the RSM method,this paper constructs a multi-mode time cost optimization model suitable for complex scenarios,aiming at the shortcomings of the current TCTPRP problem in terms of construction scenarios and constraint systems.On the basis of the traditional multi-mode TCTPRP problem,the model adds the optimization of reverse construction linear activities,strip activities,block activities,typical activities and atypical activities.In order to meet the actual situation in the project,based on the fixed logic multi-mode TCTPRP problem model of the above complex scene,this paper adds a discussion on the construction sequence and resource allocation.The above model is extended to a TCTPRP model that can handle soft logic and multiple work teams at the same time.At the same time,in order to decide the allocation of multiple work teams among activities(units),a resourcecentric scheduling process is designed.Considering the difficulty of solving the model,this paper designs a multi-objective intelligent optimization algorithm to solve the above model.From the perspective of the mining ability and exploration ability of the balanced algorithm,the algorithm introduces the differential evolution operator on the basis of NSGA-II,and designs a hierarchical multistrategy adaptive mutation crossover operator.At the same time,an improved uniform evolution elite selection strategy is proposed to speed up the algorithm convergence speed.In the simulation experiments,the algorithm proposed in this paper and several other mainstream multi-objective optimization algorithms are used to solve random cases of different scales.Through comparative analysis,the superiority of the algorithm in this paper in terms of optimization ability,convergence and stability is proved.The soft logic multi-mode multi-team TCTPRP model proposed in this paper can cover more situations that may occur in actual projects.While the algorithm provides managers with more refined and diverse construction plans,managers can also adjust the additional conditions given in the model by adjusting the input data of the algorithm,improving the flexibility of the schedule.By applying the model and algorithm proposed in this paper to the optimization of actual railway engineering projects,the Pareto optimal solution set of the trade-off between construction period and cost can be obtained,and the automatic preparation of the schedule can be realized.