Payment models and net present value optimization for resource-constrained project scheduling

• A general scheduler for six NPV optimization models is proposed.
• Three different payment models are discussed in both single- and multi-mode cases.
• The added value of each part of the proposed methodology is illustrated.
• The impact of project parameters on project NPV is analyzed in an extensive computational experiment.

This manuscript focuses on the single- and multi-mode resource-constrained project scheduling problem with discounted cash flows (RCPSPDC and MRCPSPDC) and three payment models. The contribution of the paper is twofold. First, we extend a new scheduling technique, which moves activities in order to improve the project net present value. This more general version is applicable to multiple problem formulations and provides an overarching framework in which these models can be implemented. The changes in activity finish times take other activities and the possible changes in the finish times of these other activities into account, by forming a set of activities which is subsequently moved in time. The scheduling technique is implemented within a genetic algorithm metaheuristic and employs two penalty functions, one for deadline feasibility and one for non-renewable resource feasibility. Second, we test the proposed approach on several datasets from literature and illustrate the added value of each part of the algorithm. The influence of data parameters on the project net present value is highlighted. The detailed results provided in this paper can be used as future benchmarks for each of the six models discussed.