Multi crteria decision making and its applications : a literature review

This paper presents current techniques used in Multi Criteria Decision Making (MCDM) and their applications. Two basic approaches for MCDM, namely Artificial Intelligence MCDM (AIMCDM) and Classical MCDM (CMCDM) are discussed and investigated. Recent articles from international journals related to MCDM are collected and analyzed to find which approach is more common than the other in MCDM. Also, which area these techniques are applied to. Those articles are appearing in journals for the year 2008 only. This paper provides evidence that currently, both AIMCDM and CMCDM are equally common in MCDM

The state of the art development of AHP (1979-2017): A literature review with a social network analysis

Although many papers describe the evolution of the analytic hierarchy process (AHP), most adopt a subjective approach. This paper examines the pattern of development of the AHP research field using social network analysis and scientometrics, and identifies its intellectual structure. The objectives are: (i) to trace the pattern of development of AHP research; (ii) to identify the patterns of collaboration among authors; (iii) to identify the most important papers underpinning the development of AHP; and (iv) to discover recent areas of interest. We analyse two types of networks: social networks, that is, co-authorship networks, and cognitive mapping or the network of disciplines affected by AHP. Our analyses are based on 8441 papers published between 1979 and 2017, retrieved from the ISI Web of Science database. To provide a longitudinal perspective on the pattern of evolution of AHP, we analyse these two types of networks during the three periods 1979?1990, 1991?2001 and 2002?2017. We provide some basic statistics on AHP journals and researchers, review the main topics and applications of integrated AHPs and provide direction for future research by highlighting some open questions

The state of the art development of AHP (1979-2017): a literature review with a social network analysis

Although many papers describe the evolution of the analytic hierarchy process (AHP), most adopt a subjective approach. This paper examines the pattern of development of the AHP research field using social network analysis and scientometrics, and identifies its intellectual structure. The objectives are: (i) to trace the pattern of development of AHP research; (ii) to identify the patterns of collaboration among authors; (iii) to identify the most important papers underpinning the development of AHP; and (iv) to discover recent areas of interest. We analyse two types of networks: social networks, that is, co-authorship networks, and cognitive mapping or the network of disciplines affected by AHP. Our analyses are based on 8441 papers published between 1979 and 2017, retrieved from the ISI Web of Science database. To provide a longitudinal perspective on the pattern of evolution of AHP, we analyse these two types of networks during the three periods 1979–1990, 1991–2001 and 2002–2017. We provide some basic statistics on AHP journals and researchers, review the main topics and applications of integrated AHPs and provide direction for future research by highlighting some open questions

A Comprehensive Review of the Novel Weighting Methods for Multi-Criteria Decision-Making

In the realm of multi-criteria decision-making (MCDM) problems, the selection of a weighting method holds a critical role. Researchers from diverse fields have consistently employed MCDM techniques, utilizing both traditional and novel methods to enhance the discipline. Acknowledging the significance of staying abreast of such methodological developments, this study endeavors to contribute to the field through a comprehensive review of several novel weighting-based methods: CILOS, IDOCRIW, FUCOM, LBWA, SAPEVO-M, and MEREC. Each method is scrutinized in terms of its characteristics and steps while also drawing upon publications extracted from the Web of Science (WoS) and Scopus databases. Through bibliometric and content analyses, this study delves into the trend, research components (sources, authors, countries, and affiliations), application areas, fuzzy implementations, hybrid studies (use of other weighting and/or ranking methods), and application tools for these methods. The findings of this review offer an insightful portrayal of the applications of each novel weighting method, thereby contributing valuable knowledge for researchers and practitioners within the field of MCDM.WOS:0009972313000012-s2.0-85160203389Emerging Sources Citation IndexarticleUluslararası işbirliği ile yapılan - EVETHaziran2023YÖK - 2022-2

Multiple Criteria Decision Support; Proceedings of an International Workshop, Helsinki, Finland, August 7-11, 1989

Multiple Criteria Decision Making has been an important and active research area for some 20 years. In the 1970's, research focused on the theory of multiple objective mathematical programming and on procedures for solving multiple objective mathematical programming problems. During the 1980's, a shift in emphasis towards multiple criteria decision support was observed. Accordingly, much research has focused on the user interface, the behavioral foundations of decision making, and on supporting the entire decision-making process from problem structuring to solution implementation. Because of the shift in research emphasis the authors decided to make "Multiple Criteria Decision Support" the theme for the International Workshop, which was held at Suomen Saeaestoepankkiopisto in Espoo, Finland. The Workshop was organized by the Helsinki School of Economics, and sponsored by the Helsinki School of Economics and IIASA, Austria. This volume provides an up-to-date coverage of the theory and practice of multiple criteria decision support. The authors trust that it will serve the research community as well as the previously published Conference Proceedings based on IIASA Workshops

A review of Smart Contract Blockchain Based on Multi-Criteria Analysis: Challenges and Motivations

A smart contract is a digital program of transaction protocol (rules of contract) based on the consensus architecture of blockchain. Smart contracts with Blockchain are modern technologies that have gained enormous attention in scientific and practical applications. A smart contract is the central aspect of a blockchain that facilitates blockchain as a platform outside the cryptocurrency spectrum. The development of blockchain technology, with a focus on smart contracts, has advanced significantly in recent years. However research on the smart contract idea has weaknesses in the implementation sectors based on a decentralized network that shares an identical state. This paper extensively reviews smart contracts based on multi criteria analysis challenges and motivations. Therefore, implementing blockchain in multi-criteria research is required to increase the efficiency of interaction between users via supporting information exchange with high trust. Implementing blockchain in the multi-criteria analysis is necessary to increase the efficiency of interaction between users via supporting information exchange and with high confidence, detecting malfunctioning, helping users with performance issues, reaching a consensus, deploying distributed solutions and allocating plans, tasks and joint missions. The smart contract with decision-making performance, planning and execution improves the implementation based on efficiency, sustainability and management. Furthermore the uncertainty and supply chain performance lead to improved users confidence in offering new solutions in exchange for problems in smart contacts. Evaluation includes code analysis and performance while development performance can be under development.Comment: Revie

Enterprise, project and workforce selection models for industry 4.0.

Abstract Enterprise, project, and workforce selection models for Industry 4.0. Rupinder Kaur The German federal government first coined industry 4.0 in 2011. Industry 4.0 involves the use of advanced technologies such as cyber-physical system, internet of things, cloud computing, and cognitive computing with the aim to revolutionize the current manufacturing practices. Automation and exchange of big data and key characteristics of Industry 4.0. Due to its numerous benefits, industries are readily investing in Industry 4.0, but this implementation is an uphill struggle. In this thesis, we address three key problems related to Industry 4.0 implementation namely Enterprise selection, Project selection and Workforce selection. The first problem involves identification of enterprises suitable for Industry 4.0 implementation. The second problem involves prioritization and selection of Industry 4.0 projects for the chosen digital enterprises. The third and last problem involves workforce selection and assignment for execution of the identified Industry 4.0 projects. Multicriteria solution approaches based on TOPSIS and Genetic Algorithms are proposed to address these problems. Industry experts are involved to prioritize the criteria used for enterprise, project and workforce selection. Numerical applications are provided. The proposed work is innovative and can be useful to manufacturing and service organizations interested in implementing Industry 4.0 projects for performance improvement