SciELO - Scientific Electronic Library Online

 
vol.14 número2Qualidade da Secagem de Eucalyptus grandis Mediante Vaporização Simultânea em Toros e em Madeira SerradaDestilação por Vapor de Água de Alecrim (Rosmarinus officinalis L.) de Portugal índice de autoresíndice de assuntosPesquisa de artigos
Home Pagelista alfabética de periódicos  

Serviços Personalizados

Journal

Artigo

Indicadores

Links relacionados

  • Não possue artigos similaresSimilares em SciELO

Compartilhar


Silva Lusitana

versão impressa ISSN 0870-6352

Resumo

GOMES, Helena; RIBEIRO, Alexandra B.  e  LOBO, Vitor. Optimisation Model for the Localization of Treated Wood Waste Remediation Units. Silva Lus. [online]. 2006, vol.14, n.2, pp.181-202. ISSN 0870-6352.

The objective of this study is to optimise the location of remediation plants for treating CCA-treated wood waste for further recycling, minimizing costs and respecting environmental criteria. In the next decades, the amounts of treated wood that annually needs to be properly disposed of in Portugal will increase considerably. The recycling of this waste, containing chromium, copper and arsenic, should only be made after its remediation, so planning and optimising the units' locations is of major importance. The location model was implemented with geographic information using Geographic Information Systems (ArcGIS 8.2 © ESRI), soil occupation data and the results of a questionnaire sent to wood preservation industries. Two different clustering methods (Self-Organizing Maps and K-means) were tested in different conditions to solve the location problem. The solution obtained with either clustering methods are valid and could be used to decide the location of these plants. SOM provided more robust and reproducible results than K-means, with the disadvantage of longer computing times. The main advantage of K-means is the reduced computing time. Additionally it allows us to obtain the best solutions in the majority of cases, in spite of bigger variances and more geographical dispersion.

Palavras-chave : CCA-treated wood waste; location models; Self-Organizing Maps; K-means; optimisation.

        · resumo em Português | Francês     · texto em Português     · Português ( pdf )