عنوان مقاله [English]
The crashing of project times is not a new topic in the project management area and its history returns to CPM and PERT network development. New views and methods have been presented about the time-cost trade off in recent years. Generally, the completion time of projects could be shortened by reviewing project network logic or crashing the activities through expending more cost. Note that any reduction in the duration of activities could affect their quality. In other words, crashing could decrease the closeness rate of project deliverables from the employer or customer expectation levels. Ambiguity is an unavoidable factor in most activity duration estimates, and uncertainty is another problem that always goes along with project scheduling. By reviewing the literature, it was found that researchers often try to optimize a specific objective function, while, in real world problems, a
project might have several objectives simultaneously. In this paper, we try to study the project scheduling problem in a multi-objective stochastic state. On the other hand, it might be an unpredictable lag that occurs for each activity which affects successor scheduling and the delivery date of the project, finally. This fact increases the importance of scheduling lags and the necessity of compensation or their avoidance. When project managers decide to shorten activities by expending cost, this problem becomes more important. So, it is necessary to consider the stochastic lags of each activity, which might occur after crashing, in project scheduling and the time-cost trade off problem. Since the duration time of these lags is not determined, we can consider them stochastic. Hence, applying stochastic objective functions in these problems is another innovation of this study, which could help to realize better than ever results .
In this paper, the time-cost trade off problem, with quality (TCQTP) as a key element of the projects, is discussed, while crashing with stochastic lags is occurred in activities. First, a stochastic time-cost-quality model has been developed, and then, we use Chance Constrained Compromise Programming (CCCP) to solve it. Eventually, the ability of the proposed model is illustrated through a real case study in a Liquid Gas Tank Establishment (LGTE) project. The results demonstrate the applicability of our model in real world problems.