A Heuristic for Scheduling Payments in project: Two Different Approaches for Contractor and Client

In this paper, we consider the problem of simultaneously determining the amount, timing and location of progress payments in projects to maximize NPV of the cash flows. Due to the combinatorial nature of the problem, for the first time, we propose an iterative two-stage heuristics where payment scheduling is determined in the first stage ones activities are fixed, and in the second stage activities are rescheduled to improve contractor NPV by fixing the amount and location of payment scheduling. The two stages iterate up to achieve ideal solutions. In the first stage, two objects are considered; maximization of contractor NPV and maximization of client NPV. Two Meta heuristics; genetic algorithm and simulated annealing are designed and the results are compared. By standard test problems with 120 activities, whole performances of the algorithm is considered and effect of model parameters on NPV and completion time for both objective functions is measured. In addition, effect of the second stage on project feasibility and contractor improvement is considered. The result shows that the proposed algorithm is able to achieve non-dominated solutions in consequential iterations.