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Abstract
In this paper, the multimode payment scheduling project is studied, which aims to maximize the net present value (NPV) of a project by deciding on payments and the start times of its activities. The problem is formulated mathematically from the point of view of the selected contractor of the project. In the proposed model, a bonus and penalty structure is considered, in which the project’s activities can be performed through different execution modes. Another interesting feature of the developed model is the possibility of switching between the execution’s modes during the implementation of each activity, which can increase the NPV. Because of the proposed model’s computational complexity, two metaheuristic algorithms are developed to tackle the underlying problem. In order to evaluate the performance of the developed algorithms, a set of 108 test instances are solved, and the computational results confirm the applicability of the solving methodologies.
Highlights
Net present value (NPV) is among the standard methods to evaluate the economic aspects of the projects
If it is possible to postpone an activity before the project’s deadline, the implementation cost can be reduced through reduction of the consuming resources. is flexibility in selection of the execution modes can be exploited to achieve maximum net present value (NPV)
Having a review of the project scheduling literature, we found many works on project scheduling problems with possibility of preemption for the activities
Summary
Net present value (NPV) is among the standard methods to evaluate the economic aspects of the projects. Azimi et al studied multimode resource-constrained project scheduling with the aim of maximization of the net present value and minimization of makespan simultaneously To solve this problem, they used an evolutionary algorithm named multiobjective particle swarm optimization (MOPSO) [28]. Afshar-Nadjafi et al presented multimode resource-constrained project scheduling problem (P-MRCPSP) to minimize the project’s makespan subject to mode changeability after preemption He used simulated annealing (SA) algorithm to obtain a globally optimum solution. Afshar-Nadjafi in another study developed the preemptive multimode resource-constrained project scheduling problem (P-MRCPSP), where mode changeability is allowed following preemption, to minimize makespan of the project He used simulated annealing (SA) algorithm to deal with this problem and applied statistical method in order to determine the effect of the presented method on the problem.
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