نتایج جستجو برای: multi attribute decision making madm
تعداد نتایج: 1024031 فیلتر نتایج به سال:
Although simple additive weighting method (SAW) is the most popular approach for classical multiple attribute decision making (MADM), it is not practical any more if information is fuzzy. The existing methods of Fuzzy Simple Additive Weighting method (FSAW) apply defuzzification which distorts fuzzy numbers. Furthermore, most of the methods usually require lengthy and laborious manipulations. I...
This study aims to assist human work in knowing the decision support system for determining outstanding teachers using topsis method Multi Attribute Decision Making (MADM) making which is used evaluate or select several alternatives as a one method, namely The trick order preference by similarity ideal solution (TOPSIS). widely solve practical decision-making. because concept simple and easy un...
– Normalization procedures are required in multiattribute decision making (MADM) to transform performance ratings with different data measurement units in a decision matrix into a compatible unit. MADM methods generally use one particular normalization procedure without considering the suitability of other available procedures. This study compares four commonly known normalization procedures in...
Multi-attribute decision-making (MADM) is commonly used to investigate fuzzy information effectively. However, selecting the best alternative not always symmetric because alternatives do have complete information, so asymmetric often involved. Expressing under uncertainty using closed subintervals of [0, 1] beneficial and effective instead crisp numbers from 1]. The goal this paper enhance noti...
Residential buildings are the main consumer of materials in construction industry. Selection of appropriate materialled to a great impact on quality of architecture in many aspects. Considering the extent of construction in the residential sector, study on this context seems necessary. Therefore the aim of this study is to represent a “materials selection model” for residential building facade ...
The rush of the humanitarian suppliers into disaster area proved to be counter-productive. To reduce this proliferation problem, present research is designed provide a technique for supplier ranking/selection in response using principles utility theory. A resource allocation problem solved optimisation based on decision maker’s preferences. Due lack real-time data first 72 h after strike, Decis...
Abstract Picture fuzzy set (PFS) is a direct generalization of the sets (FSs) and intuitionistic (IFSs). The concept PFS suitable to model situations that involve more answers type yes, no, abstain, refuse. In this study, we introduce novel picture (PF) distance measure on basis operation functions membership, non-membership, neutrality, refusal, upper bound function membership two PFSs. We con...
OBJECTIVE To develop and validate a new instrument that assesses women's autonomy and role in decision making during maternity care. DESIGN Through a community-based participatory research process, service users designed, content validated, and administered a cross-sectional quantitative survey, including 31 items on the experience of decision-making. SETTING AND PARTICIPANTS Pregnancy expe...
This paper addresses the multi-mode multi-skilled resource-constrained project scheduling problem. Activities of real world projects often require more than one skill to be accomplished. Besides, in many real-world situations, the resources are multi-skilled workforces. In presence of multi-skilled resources, it is required to determine the combination of workforces assigned to each activity. H...
Multi-attribute decision-making (MADM) refers to making preference decisions via assessing a finite number of pre-specified alternatives under multiple and usually conflicting attributes. Many problems in the field additive manufacturing (AM) are essentially MADM or can be converted into problems. Recently, variety methods have been applied solve AM. This generates series interesting questions:...
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