A Study On Time Cost Trade-off Problem With The Learning-forgetting Effect In LOB

The learning-forgetting effect has been widely recognized in recent years in the construction field. And its impact can be displayed clearly now in the construction scheduling. However, in view of the learning forgetting effect started late in the field of construction, the research is still in its initial stage. Therefore, the impact of learning-forgetting effect is rarely taken the scheduling methods into account in some classical scheduling programs.The balance method of lines (Line-of-Balance, LOB) is commonly used in project planning and scheduling, is the basis for project scheduling method. However, research on the LOB with learning-forgetting effect is less, the relevant theoretical research is not very perfect, and even there are some obvious defects on the LOB considering learning effect. The responsibility of time claims is hard to judge.Under this background, the research on learning-forgetting effect with the LOB has important value. Features of the learning-forgetting effect is obvious in the repetitive project scheduling field, while the LOB is a method that has been widely accepted and used by the basic method of project scheduling. An improved LOB method is proposed with learning-forgetting effect. Therefore, if the LOB is applied to actual project with the learning-forgetting, the project scheduling will be more practical, and it is useful for time claims. The complete steps of the LOB with the learning-forgetting are proposed, and the LOB can show the actual progress in construction projects.TCTP is a two-objective optimization problem in project scheduling. However, when the problem is solved rarely taken the impact of learning-forgetting effect into account, the planned scheduling is not the optimal solution currently. The necessity of learning-forgetting effect is analyzed in time/cost tradeoff problems in this paper. A new TCTP model is proposed combining the LOB with the learning-forgetting effect. Finally, the improved particle swarm algorithm is designed with a double chain integer coding and penalty function. The effectiveness of the algorithm is proved through the example and compared the difference of the project scheduling before and after the LOB changed. The results show that the improved LOB with the learning-forgetting effect is obviously better than that of the original LOB.The results of this paper are helpful to improve the application and accuracy of LOB and solve the TCTP with the learning-forgetting effect in the actual project scheduling. And it is helpful for solving the time claims, making scheduling more scientific, accurate and economic.