SELECCIÓN MULTICRITERIO DE CONTRATISTAS DE OBRAS. ENFOQUE BASADO EN REDES NEURONALES

Autor:	Alfredo Del Caño Gochi, Mª Pilar De La Cruz Lopez, Ricardo Javier Bendaña Jácome, Alberto Castro Rascado
Rok vydání:	2010
Předmět:	Artificial neural network Operations research Computer science business.industry Contractor Selection General Engineering Complex system Artificial intelligence business Selection (genetic algorithm)
Zdroj:	DYNA INGENIERIA E INDUSTRIA. 85:71-84
ISSN:	1989-1490 0012-7361
DOI:	10.6036/3016
Popis:	This paper presents two cases of applying neural networks to extract knowledge for, subsequently, using it to support multicriteria contractor selection, in traditional design-bid-build projects with one-step selection processes. Different qualitative and quantitative selection criteria are taken into account, up to 22 and 9, respectively. The ? rst case includes a high number of input variables, making up a complex system related to complex and medium or large-sized projects. The second case is related to small projects in a medium-sized municipality. One advantage of these systems is that they can serve to ‘homogenize’ speci? c decision making in medium and large organizations. The paper also analyzes other pros of this approach, as well as the main problems.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::e4c53b865925d0db8d2c7ec5470b4f77 https://doi.org/10.6036/3016 Zobrazit plný text záznamu