نتایج جستجو برای: keywords analytic hierarchy process ahp
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Effort Estimation has always been a challenging task for the Project managers. Many researchers have tried to help them by creating different types of models. This has been already proved that none is successful for all types of projects and every type of environment. Analytic Hierarchy Process (AHP) has been identified as the tool that would help in Multi Criteria Decision Making. Researchers ...
Kehadiran perusahaan-perusahaan industri membuka peluang cukup besar bagi kontraktor lokal untuk ikut bergabung dalam pembangunan proyek perindustrian tersebut sesuai bidang keahlian masing-masing. Para Kontraktor harus mampu menyikapi kondisi persaingan agar dapat mempertahankan keberlangsungan operasional perusahaan. Perencanaan dan pengendalian Proyek merupakan hal yang diperhatikan kontruks...
Fuzzy AHP is often used in multi-criteria decision analysis. In this paper we consider an example given by Deng [I] and in particular the method used to approximate the fuzzy principle eigenvector of the fuzzy pairwise comparison matrices. We show Nigel Steele Computational Intelligence Group, School of Mathematical and Information Sciences, Coventry University, Priory Street, Coventry. CV1 5FB...
Cloud computing has created a new perception of computation with all its features and characteristics. With its profound computational capabilities, it provides a platform for solving complex computational problems. Cloud computing deals with different kinds of virtualized resources and scheduling plays a vital role in cloud computing. This paper focuses on that various scheduling policies with...
The Analytic Hierarchy Process (AHP) (Saaty, 1990) has been accepted as a leading multiattribute decision model both by practitioners and academics. AHP can solve decision problems in various fields by the prioritization of alternatives. The heart of the most familiar version of the AHP is the Saaty’s eigenvector method (EM) which approximates an positive reciprocal matrix n n× ) ( ij a A = , ,...
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