The comparison between MAUT and PROMETHEE

Wang, M.; Lin, Shin-Yi; Lo, Yu-Lung

doi:10.1109/ieem.2010.5675608

Cited by 27 publications

(11 citation statements)

References 22 publications

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“…In this paper, multi-attribute utility theory (MAUT) and the fuzzy set theory are used. MAUT is one kind of MADM and used for evaluating different items taking multiple computing attributes into consideration (Wang et al 2010;Pachauri et al 2014). The basic model is expressed as following.…”

Section: Overview Of Multi-criteria Decision-making Algorithmsmentioning

confidence: 99%

A semi-automatic image-based object recognition system for constructing as-is IFC BIM objects based on fuzzy-MAUT

Chen

Zhao

2019

International Journal of Construction Management

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Building Information Modelling (BIM) could support different activities throughout the life cycle of a building and has been widely applied in design and construction phases nowadays. However, BIM has not been widely implemented in the operation and maintenance (O&M) phase. As-is information for the majority of existing buildings is not complete and even outdated or incorrect. Lack of accurate and complete as-is information is still one of the key reasons leading to the low-level efficiency in O&M. BIM performs as an intelligent platform and a database that stores, links, extracts and exchanges information in construction projects. It has shown promising opportunities and advantages in BIM applications for the improvement in O&M. Hence, an effective and convenient approach to record as-is conditions of the existing buildings and create as-is BIM objects would be the essential step for improving efficiency and effectiveness of O&M, and furthermore possibly refurbishment of the building. Many researchers have paid attention to different systems and approaches for automated and real-time object recognition in past decades. This paper summarizes state-ofthe-art statistical matching-based object recognition methods and then presents the imagebased Industry Foundation Classes (IFC) BIM object creation application, which extracts object information by simply conducting point-and-click operations. Furthermore, the object recognition research system is introduced, including recognizing structure object types and their corresponding materials. This paper combines the Multi-Attribute Utility Theory (MAUT) with the fuzzy set theory to be Fuzzy-MAUT, since the MAUT allows complex and powerful combinations of various criteria and fuzzy set theory assists improving the performance of this system. With the goal of creating an effective method for as-is IFC BIM objects construction, this image-based object recognition system and its recognition process are further validated and tested. Key challenges and promising opportunities are also addressed.

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Section: Overview Of Multi-criteria Decision-making Algorithmsmentioning

confidence: 99%

A semi-automatic image-based object recognition system for constructing as-is IFC BIM objects based on fuzzy-MAUT

Chen

Zhao

2019

International Journal of Construction Management

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“…The impacts of any changes in values can be revealed by sensitivity analysis". 35 In view of the above ¯ndings and MCDA guidelines, we have decided to use MAUT-based decision analysis methodology taking into account that we are experts on MAUT and that this methodology has not been applied until now for selecting ontologies for reuse.…”

Section: Mcda Approaches For Selecting Ontologiesmentioning

confidence: 99%

A MAUT APPROACH FOR REUSING DOMAIN ONTOLOGIES ON THE BASIS OF THE NeOn METHODOLOGY

Jiménez

Suárez-Figueroa

Mateos

et al. 2013

Int. J. Info. Tech. Dec. Mak.

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Knowledge resource reuse is becoming a widespread approach in the ontology engineering field because it can speed up the ontology development process. In this context, the NeOn Methodology specifies some guidelines for reusing different types of knowledge resources (ontologies, nonontological resources, and ontology design patterns). These guidelines prescribe how to perform the different activities involved in any of the diverse types of reuse processes. One such activity is to select the best knowledge resources for reuse in an ontology development. This selection activity is a complex decision-making problem involving conflicting objectives, like understandability, integration or reliability. We propose a multi-attribute utility theory (MAUT) approach to deal with the selection of the best domain ontologies for reuse, stressing the identification of attributes to measure ontology performances. We take advantage of the sensitivity analysis tools provided by the GMAA system, a PC-based decision support system based on an additive multi-attribute utility model, to exploit imprecise information on the inputs. An example concerning the selection of a subset of ontologies for reuse in the development of a new ontology in the sports domain illustrates the approach.

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“…The underlying idea of MAUT is that in any decision problem there is a real valued function or utility which has to be maximized (Zietsman et al, 2006). Due to MAUT, the decision makers can compare all alternatives simultaneously (Wang et al, 2010). The decision maker's preferences are reflected in the form of the utility function which is defined over a set of criteria.…”

Section: Maut (Multi Attribute Utility Theory)mentioning

confidence: 99%

Critic and Maut Methods for the Contract Manufacturer Selection Problem

Adalı¹,

Işık²

2017

Europ. j. multidiscip. stud.

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Nowadays companies should respond and satisfy the customer needs effectively and quickly to establish a position in the competitive market. One of the ways of achieving these goals is the outsourcing their some manufacturing operations to contract manufacturers. Outsourcing manufacturing operation to contract manufacturers decreases the operational cost, increases the profit and provides the flexibility of production capability. So the selecting a contract manufacturer for a company is an important problem that must be dealt very carefully. This selection is influenced by quantitative and qualitative criteria and it is handled as Multi Criteria Decision Making (MCDM) problem. In this paper, CRITIC (CRiteria Importance Through Intercriteria Correlation) and MAUT (Multi Attribute Utility Theory) methods are applied to the contract manufacturer selection problem. The weights of the contract manufacturer selection criteria are derived from CRITIC method whereas the complete ranking of the contract manufacturer alternatives are obtained by using MAUT. Finally the results are discussed.

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The comparison between MAUT and PROMETHEE

Cited by 27 publications

References 22 publications

A semi-automatic image-based object recognition system for constructing as-is IFC BIM objects based on fuzzy-MAUT

A semi-automatic image-based object recognition system for constructing as-is IFC BIM objects based on fuzzy-MAUT

A MAUT APPROACH FOR REUSING DOMAIN ONTOLOGIES ON THE BASIS OF THE NeOn METHODOLOGY

Critic and Maut Methods for the Contract Manufacturer Selection Problem

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