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首页> 外文期刊>Journal of applied mathematics >Multiproject Resources Allocation Model under Fuzzy Random Environment and Its Application to Industrial Equipment Installation Engineering
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Multiproject Resources Allocation Model under Fuzzy Random Environment and Its Application to Industrial Equipment Installation Engineering

机译：模糊随机环境下的多项目资源分配模型及其在工业设备安装工程中的应用

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摘要

This paper focuses on a multiproject resource allocation problem in a bilevel organization. To solve this problem, a bilevel multiproject resource allocation model under a fuzzy random environment is proposed. Two levels of decision makers are considered in the model. On the upper level, the company manager aims to allocate the company's resources to multiple projects to achieve the lowest cost, which include resource costs and a tardiness penalty. On the lower level, each project manager attempts to schedule their resource-constrained project, with minimization of project duration as the main objective. In contrast to prior studies, uncertainty in resource allocation has been explicitly considered. Specifically, our research uses fuzzy random variables to model uncertain activity durations and resource costs. To search for the optimal solution of the bilevel model, a hybrid algorithm made up of an adaptive particle swarm optimization, an adaptive hybrid genetic algorithm, and a fuzzy random simulation algorithmis also proposed. Finally, the efficiency of the proposedmodel and algorithm is evaluated through a practical case froman industrial equipment installation company.The results show that the proposed model is efficient in dealing with practical resource allocation problems in a bilevel organization.
机译：本文着重研究双层组织中的多项目资源分配问题。为了解决这个问题，提出了一种模糊随机环境下的双层多项目资源分配模型。该模型考虑了两个层次的决策者。在较高级别，公司经理旨在将公司资源分配给多个项目，以实现最低成本，其中包括资源成本和拖延罚款。在较低级别上，每个项目经理都试图安排其资源受限的项目，并以最小化项目持续时间为主要目标。与先前的研究相反，资源分配的不确定性已得到明确考虑。具体而言，我们的研究使用模糊随机变量对不确定的活动持续时间和资源成本进行建模。为了寻找双层模型的最优解，提出了一种由自适应粒子群算法，自适应混合遗传算法和模糊随机仿真算法组成的混合算法。最后，通过工业设备安装公司的实际案例对所提出的模型和算法的效率进行了评估。结果表明，所提出的模型可以有效地解决双层组织中的实际资源分配问题。

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