Project resource investment problem under progress payment model

As a general branch of project scheduling problems, resource investment problem (RIP) considers resource availabilities as decision variables to determine a level of employed resources minimizing the costs of the project. In addition to costs (cash outflows), researchers in the later extensions of the RIP took payments (cash inflows) received from clients into account and used the net present value (NPV) of project cash flows as a financial criterion evaluating the profitability of the project. A striking point in a financial view of the project scheduling is how cash inflows are paid by the client. There are different payment models in the literature of which progress payment is highly common in practice. In this paper, resource investment problem with maximization of the NPV under progress payment model is investigated. A new mathematical model is developed for the problem and then two metaheuristic algorithms based on the genetic algorithm (GA) and simulated annealing algorithm (SA) are suggested. The experimental results of algorithms are compared with some near-optimal solutions derived from LINGO software. The comparisons show that the results of GA are more reliable than SA.