Multiple R&D Projects Scheduling Optimization with Improved Particle Swarm Algorithm
For most enterprises, in order to win the initiative in the fierce competition of market, a key step is to improve their R&D ability to meet the various demands of customers more timely and less costly. This paper discusses the features of multiple R&D environments in large make-to-order en...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/652135 |
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| _version_ | 1849468614892060672 |
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| author | Mengqi Liu Miyuan Shan Juan Wu |
| author_facet | Mengqi Liu Miyuan Shan Juan Wu |
| author_sort | Mengqi Liu |
| collection | DOAJ |
| description | For most enterprises, in order to win the initiative in the fierce competition of market, a key step is to improve their R&D ability to meet the various demands of customers more timely and less costly. This paper discusses the features of multiple R&D environments in large make-to-order enterprises under constrained human resource and budget, and puts forward a multi-project scheduling model during a certain period. Furthermore, we make some improvements to existed particle swarm algorithm and apply the one developed here to the resource-constrained multi-project scheduling model for a simulation experiment. Simultaneously, the feasibility of model and the validity of algorithm are proved in the experiment. |
| format | Article |
| id | doaj-art-f29082b5a7b547c9a20b45f3c0cd3f15 |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-f29082b5a7b547c9a20b45f3c0cd3f152025-08-20T03:25:47ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/652135652135Multiple R&D Projects Scheduling Optimization with Improved Particle Swarm AlgorithmMengqi Liu0Miyuan Shan1Juan Wu2School of Business Administration, Hunan University, Changsha, Hunan 410082, ChinaSchool of Business Administration, Hunan University, Changsha, Hunan 410082, ChinaSchool of Business Administration, Hunan University, Changsha, Hunan 410082, ChinaFor most enterprises, in order to win the initiative in the fierce competition of market, a key step is to improve their R&D ability to meet the various demands of customers more timely and less costly. This paper discusses the features of multiple R&D environments in large make-to-order enterprises under constrained human resource and budget, and puts forward a multi-project scheduling model during a certain period. Furthermore, we make some improvements to existed particle swarm algorithm and apply the one developed here to the resource-constrained multi-project scheduling model for a simulation experiment. Simultaneously, the feasibility of model and the validity of algorithm are proved in the experiment.http://dx.doi.org/10.1155/2014/652135 |
| spellingShingle | Mengqi Liu Miyuan Shan Juan Wu Multiple R&D Projects Scheduling Optimization with Improved Particle Swarm Algorithm The Scientific World Journal |
| title | Multiple R&D Projects Scheduling Optimization with Improved Particle Swarm Algorithm |
| title_full | Multiple R&D Projects Scheduling Optimization with Improved Particle Swarm Algorithm |
| title_fullStr | Multiple R&D Projects Scheduling Optimization with Improved Particle Swarm Algorithm |
| title_full_unstemmed | Multiple R&D Projects Scheduling Optimization with Improved Particle Swarm Algorithm |
| title_short | Multiple R&D Projects Scheduling Optimization with Improved Particle Swarm Algorithm |
| title_sort | multiple r d projects scheduling optimization with improved particle swarm algorithm |
| url | http://dx.doi.org/10.1155/2014/652135 |
| work_keys_str_mv | AT mengqiliu multiplerdprojectsschedulingoptimizationwithimprovedparticleswarmalgorithm AT miyuanshan multiplerdprojectsschedulingoptimizationwithimprovedparticleswarmalgorithm AT juanwu multiplerdprojectsschedulingoptimizationwithimprovedparticleswarmalgorithm |