The aim of this research is to present a new mathematical model for a multi-mode resource-constrained\r\nproject scheduling problem (MRCPSP) with discounted cash flows. The objective is to minimize the\r\nproject makespan and maximize the net present value (NPV), simultaneously, which are the two\r\ncommon objectives of this problem in the literature. Two evolutionary algorithms, NSGA-II and MOPSO\r\nare applied to find the set of Pareto solutions for this bi-objective scheduling problem. Furthermore, a\r\nnew policy is proposed to have feasible solutions for both algorithms. To show the superiority and\r\napplicability of the algorithms, different metrics are applied and the graphical comparisons are also\r\nconsidered. Finally, the computational results illustrate the superior performance of the NSGA-II\r\nalgorithm with regard to the proposed metrics.
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