Research On Project Plan Robustness Problem Based On Critical Chain Method

The resource-contained project schedule problem (RCPSP) aims to effectivelyutilize kinds of limited resources to meet special objectives of a project. Compared withthe traditional project schedule methods, including Gantt chart, CPM and PERT, RCPSPis more available to the actual situation of project. Therefore, recent researches aboutproject scheduling are mostly based on RCPSP. It is impartial for project scheduling toreduce the project duration and ensure the stability of the scheduling scheme. Criticalchain project management (CCPM), as a new method based on RCPSP, considers notonly the relationship among project activities, but also the resource-contained problemand the human beings factor simultaneously, and can be able to obviously reduce theproject duration so as to get widely recognition of academia. Robustness refers to thecapacity of less vulnerable to disruption caused by uncontrollable factors, so there is agreat significance to add robustness into project schedule problem in both theory andpractice.This paper is aimed at combining CCPM and Robustness, and making a projectscheduling plan which is more closed to the practical situation. At first, a mathematicalmodel of robust schedule based on critical chain can be built by researching projectscheduling problem and CCPM. Secondly, after selecting a project example from theProject Scheduling Problem Library, we utilize the Crystal Ball as an assistant tool toconduct Monte Carlo simulation, then get a probability distribution of completion raterespectively based on CPM method and resource-contained problem, so that we canverify the necessity of considering resource-contained problem by comparing thecompletion rate of project scheduling plan. Finally, after analyzing the data andselecting an effective robust index by SPSS software, we use the mathematical model ofthis paper to solve the project example and gain a final scheduling plan, ensuing thevalidity of the model, and the superiority of CCPM and robust schedule can be verifiedas well.