Abstract Project scheduling and financing should be adequately integrated during the planning phase to avoid probable cost overruns and delays. Many studies addressed the achievement of integration between project financing and scheduling using multi-objective optimization in particular. However, up to the knowledge of the authors, there is no research conducted to evaluate and assess the performance of the multi-objective optimization techniques employed in this domain. Thus, the current study developed a finance-based scheduling multi-objective optimization model for multiple projects using the elitist non-dominated sorting genetic algorithm (NSGA-II). Further, the obtained results were compared with the results obtained by solving the same problem in another study from the literature using the multi-objective optimization technique of strength Pareto evolutionary algorithm (SPEA). Benchmarking was conducted based on the quality of the obtained solutions and performance. The results indicated that the NSGA-II outperformed SPEA in most aspects with achieved improvements range from 1.7% to 98.2%.

中文翻译：

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基于财务的调度多目标优化：进化算法的基准测试

摘要 在规划阶段应充分整合项目进度和融资，以避免可能的成本超支和延误。许多研究特别针对使用多目标优化实现项目融资和调度之间的整合。然而，据作者所知，还没有进行研究来评估和评估该领域中采用的多目标优化技术的性能。因此，当前的研究使用精英非支配排序遗传算法（NSGA-II）为多个项目开发了基于财务的调度多目标优化模型。更多，将获得的结果与使用强度帕累托进化算法 (SPEA) 的多目标优化技术从文献中解决同一问题的另一项研究中获得的结果进行比较。根据获得的解决方案的质量和性能进行基准测试。结果表明，NSGA-II 在大多数方面都优于 SPEA，实现了 1.7% 到 98.2% 的改进。