School of Engineering and Information Technology, University of New South Wales, Northcott Drive, Campbell, Canberra, ACT 2600, Australia.
Environ Sci Pollut Res Int. 2023 May;30(21):59925-59962. doi: 10.1007/s11356-023-26361-2. Epub 2023 Apr 5.
The proper trade-off between various project costs is often disregarded when planning projects. This leads to several detrimental effects, such as inaccurate planning and higher total cost, far more significant in a multi-project environment. To overcome this limitation, this study proposes a combined approach for the multi-project scheduling and material ordering problem (MPSMOP), which maintains the proper trade-off among various costs. Moreover, the environmental impact and project quality objectives are optimized alongside the economic criterion. The proposed methodology involves three stages: (a) quantifying the environmental performance of suppliers; (b) measuring the activities' quality through the Construction Quality Assessment System approach; and (c) building and solving the mathematical model of the MPSMOP. The MPSMOP is modeled as a tri-objective optimization approach aiming to determine project scheduling and material ordering decisions so that the net present value, environmental score, and total quality of implemented projects are maximized simultaneously. As the proposed model comes into the nondeterministic polynomial optimization problem category, two powerful metaheuristics are customized and used to solve the problem. The efficiency of both algorithms was assessed on several datasets. The proposed framework is applied to railway construction projects in Iran as a case study, which presents the validity of the model and the decision-making options provided to managers.
在项目规划中，往往会忽视各种项目成本之间的适当权衡。这会导致一些不利影响，例如规划不准确和总成本增加，在多项目环境中更为显著。为了克服这一局限性，本研究提出了一种多项目调度和材料订购问题（MPSMOP）的综合方法，该方法在各种成本之间保持适当的权衡。此外，还优化了环境影响和项目质量目标以及经济标准。所提出的方法包括三个阶段：（a）量化供应商的环境绩效；（b）通过施工质量评估系统方法衡量活动的质量；（c）建立和解决 MPSMOP 的数学模型。MPSMOP 被建模为一个三目标优化方法，旨在确定项目调度和材料订购决策，以使实施项目的净现值、环境得分和总质量同时最大化。由于所提出的模型属于不确定多项式优化问题类别，因此定制并使用了两种强大的元启发式算法来解决该问题。评估了这两种算法在几个数据集上的效率。将该框架应用于伊朗的铁路建设项目作为案例研究，展示了模型的有效性和为管理人员提供的决策选项。
