Research On The Duration Optimization For LOB Initial Scheduling

Repetitive project is a common kind of construction projects in practical.And resource optimization scheduling problem is one of the hot topics in the project schedule management research.there are a lot of research and algorithm models for the resource optimization problems in the general engineering projects,and it is more mature in theory and application.But there are few research about the resource optimization in the repetitive project,especially a lot of existed tudies have not considered a special kind of activity named the backward controlling activity in LOB,which provides a new solution to the problem of duration optimization problem.The initial scheduling given by LOB method often exceed the duration of the contract.To solve this problem,this paper established duration optimization model.The purpose is to meet the requirement duration of the project,and make the least resource cost increase.Firstly,considering the special nature of the backward controlling activity,interrupting the backward controlling activity to change its resource allocation,which can shorten the duration of the project.The model can achieve the purpose of reducing the duration for project without any else resource allocation.In addition,according to the more general case,this paper built a duration optimization model by adjusting the number of crows,make adjustments in different ways for different controlling activities.then we transformed the LOB model into GPRs model,and a mixed integer programming model is established under the GPRs network.GPRs network can be used to express the time constraint of LOB method,that make it easy to adjust the resources.Finally,an example is used to prove that two model can meet the project duration and increase the least cost of the project.these models have their own advantages and applicable conditions,and can well solve the problem that initial schedule given by LOB beyond the duration of the project.It will help project management to solve different problems with different methods in practice.