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 enterprises...
| Publicado en: | Scientific World Journal pp. 652135 - 652136 |
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| Autores principales: | , , |
| Formato: | research Journal Article |
| Publicado: |
Wiley-Blackwell
2014
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=103834422&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 103834422 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 1537744X 1BX5 jtl: Scientific World Journal issn: 1537744X maglogo: N pubinfo: dt: 2014 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 103834422 NLM25032232 2012651249 10.1155/2014/652135 NLM25032232 PMC4083149 103834422 ppf: 652135 ppct: 1 formats: tig: atl: Multiple R&D projects scheduling optimization with improved particle swarm algorithm. aug: au: Liu, Mengqi Shan, Miyuan Wu, Juan affil: School of Business Administration, Hunan University, Changsha, Hunan 410082, China. sug: subj: Models, Theoretical Research Personnel Staffing and Scheduling Research Economics Research Standards ab: 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. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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