Multiproject Resources Allocation Model under Fuzzy Random Environment and Its Application to Industrial Equipment Installation Engineering
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...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2013-01-01
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| Series: | Journal of Applied Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2013/818731 |
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| _version_ | 1832553377627635712 |
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| author | Jun Gang Jiuping Xu Yinfeng Xu |
| author_facet | Jun Gang Jiuping Xu Yinfeng Xu |
| author_sort | Jun Gang |
| collection | DOAJ |
| description | 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 algorithm is
also proposed. Finally, the efficiency of the proposed model and
algorithm is evaluated through a practical case from an industrial
equipment installation company. The results show that the proposed
model is efficient in dealing with practical resource allocation problems in a bilevel organization. |
| format | Article |
| id | doaj-art-07d6a0650e5d4fff9fb2ec133745afca |
| institution | Kabale University |
| issn | 1110-757X 1687-0042 |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Applied Mathematics |
| spelling | doaj-art-07d6a0650e5d4fff9fb2ec133745afca2025-02-03T05:54:00ZengWileyJournal of Applied Mathematics1110-757X1687-00422013-01-01201310.1155/2013/818731818731Multiproject Resources Allocation Model under Fuzzy Random Environment and Its Application to Industrial Equipment Installation EngineeringJun Gang0Jiuping Xu1Yinfeng Xu2Business School, Sichuan University, Chengdu 610064, ChinaBusiness School, Sichuan University, Chengdu 610064, ChinaBusiness School, Sichuan University, Chengdu 610064, ChinaThis 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 algorithm is also proposed. Finally, the efficiency of the proposed model and algorithm is evaluated through a practical case from an industrial equipment installation company. The results show that the proposed model is efficient in dealing with practical resource allocation problems in a bilevel organization.http://dx.doi.org/10.1155/2013/818731 |
| spellingShingle | Jun Gang Jiuping Xu Yinfeng Xu Multiproject Resources Allocation Model under Fuzzy Random Environment and Its Application to Industrial Equipment Installation Engineering Journal of Applied Mathematics |
| title | Multiproject Resources Allocation Model under Fuzzy Random Environment and Its Application to Industrial Equipment Installation Engineering |
| title_full | Multiproject Resources Allocation Model under Fuzzy Random Environment and Its Application to Industrial Equipment Installation Engineering |
| title_fullStr | Multiproject Resources Allocation Model under Fuzzy Random Environment and Its Application to Industrial Equipment Installation Engineering |
| title_full_unstemmed | Multiproject Resources Allocation Model under Fuzzy Random Environment and Its Application to Industrial Equipment Installation Engineering |
| title_short | Multiproject Resources Allocation Model under Fuzzy Random Environment and Its Application to Industrial Equipment Installation Engineering |
| title_sort | multiproject resources allocation model under fuzzy random environment and its application to industrial equipment installation engineering |
| url | http://dx.doi.org/10.1155/2013/818731 |
| work_keys_str_mv | AT jungang multiprojectresourcesallocationmodelunderfuzzyrandomenvironmentanditsapplicationtoindustrialequipmentinstallationengineering AT jiupingxu multiprojectresourcesallocationmodelunderfuzzyrandomenvironmentanditsapplicationtoindustrialequipmentinstallationengineering AT yinfengxu multiprojectresourcesallocationmodelunderfuzzyrandomenvironmentanditsapplicationtoindustrialequipmentinstallationengineering |