Discrete particle swarm optimization with scout particles for library materials acquisition.
Materials acquisition is one of the critical challenges faced by academic libraries. This paper presents an integer programming model of the studied problem by considering how to select materials in order to maximize the average preference and the budget execution rate under some practical restricti...
| Publicado en: | Scientific World Journal pp. 636484 - 636485 |
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| Autores principales: | , , , |
| Formato: | Journal Article |
| Publicado: |
Wiley-Blackwell
2013
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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=104101185&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104101185 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 1537744X 1BX5 jtl: Scientific World Journal issn: 1537744X maglogo: N pubinfo: dt: 2013 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 104101185 NLM24072983 2012330589 10.1155/2013/636484 NLM24072983 PMC3773454 104101185 ppf: 636484 ppct: 1 formats: tig: atl: Discrete particle swarm optimization with scout particles for library materials acquisition. aug: au: Wu, Yi-Ling Ho, Tsu-Feng Shyu, Shyong Jian Lin, Bertrand M T affil: Institute of Information Management, National Chiao Tung University, Hsinchu 30010, Taiwan. sug: subj: Libraries Administration Particle Swarm Optimization Budgets Computer Simulation Libraries Economics Models, Theoretical ab: Materials acquisition is one of the critical challenges faced by academic libraries. This paper presents an integer programming model of the studied problem by considering how to select materials in order to maximize the average preference and the budget execution rate under some practical restrictions including departmental budget, limitation of the number of materials in each category and each language. To tackle the constrained problem, we propose a discrete particle swarm optimization (DPSO) with scout particles, where each particle, represented as a binary matrix, corresponds to a candidate solution to the problem. An initialization algorithm and a penalty function are designed to cope with the constraints, and the scout particles are employed to enhance the exploration within the solution space. To demonstrate the effectiveness and efficiency of the proposed DPSO, a series of computational experiments are designed and conducted. The results are statistically analyzed, and it is evinced that the proposed DPSO is an effective approach for the studied problem. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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