In this Chapter, we imagine a decision maker (or a group of experts) trying to establish or examine fair procedures to combine opinions about alternatives related to different points of view.

Multiple criteria decision making

The philosophy of decision making in economics is to assess and select the most preferable solution, implement it and to gain the biggest profit. Important issues such as competitive market, changing technical, political and social environment have a key role in personnel selection. It is the crucial task which determines the company's present and future. Many decisions made cannot be accurately forecast or assessed. Understanding of the multiple criteria method and knowledge to calculate the algorithm of the method allows a decision maker to trust solutions offered by solution support systems to a greater extent. Many individual attributes considered for personnel selection such as organizing ability, creativity, personality, and leadership exhibit vagueness and imprecision. The fuzzy set theory appears as an essential tool to provide a decision framework that incorporates imprecise judgments inherent in the personnel selection process. In this paper, a fuzzy multi-criteria decision making (MCDM...

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Integrated Fuzzy Multiple Criteria Decision Making Model for Architect Selection

Graphical abstractDisplay Omitted HighlightsBased on Karnik-Mendel (KM) algorithm, we propose an analytical solution to fuzzy TOPSIS method, and apply it in personnel selection problems for knowledge-intensive enterprise.Compared with the existing TOPSIS method, it obtains accurate fuzzy relative closeness instead of the crisp point or approximate fuzzy relative closeness estimate.The global picture of fuzzy relative closeness provides a way to further discuss the inner properties of fuzzy TOPSIS method. Personnel selection is a critical enterprise strategic problem in knowledge-intensive enterprise. Fuzzy number which can be described as triangular (trapezoid) fuzzy number is an adequate way to assess the evaluation and weights for the alternatives. In that case, fuzzy TOPSIS, as a classic fuzzy multiple criteria decision making (MCDM) methods, has been applied in personnel selection problems. Currently, all the researches on this topic either apply crisp relative closeness but causing information loss, or employ fuzzy relative closeness estimate but with complicated computation to rank the alternatives. In this paper, based on Karnik-Mendel (KM) algorithm, we propose an analytical solution to fuzzy TOPSIS method. Some properties are discussed, and the computation procedure for the proposed analytical solution is given as well. Compared with the existing TOPSIS method for personnel selection problem, it obtains accurate fuzzy relative closeness instead of the crisp point or approximate fuzzy relative closeness estimate. It can both avoid information loss and keep computational efficiency in some extent. Moreover, the global picture of fuzzy relative closeness provides a way to further discuss the inner properties of fuzzy TOPSIS method. Detailed comparisons with approximate fuzzy relative closeness method are provided in personnel selection application.

An analytical solution to fuzzy TOPSIS and its application in personnel selection for knowledge-intensive enterprise

A method based on stochastic dominance degrees for stochastic multiple criteria decision making

In recent decades, several mathematical methods have been developed for selecting the most preferable alternatives. Among them, the MCDM (Multiple Criteria Decision Making) methods as disciplines aimed at supporting DMs faced with numerous and sometimes conflicting evaluations. Theses methods have attracted much attention from academics and practitioners. This paper aims to bring together ‘state-of-the-art' reviews and the most recent advances by leading experts on the fundamental theories, methodologies and applications of MCDM. In this paper, in order to classify the current researches on MCDM; 628 scholarly papers from 20 journals (journals with higher published papers in Science Direct) are studied. Section 2 describes research methodology. Section 3 categorized 786 methods applied in all papers, into the 12 application areas and a nonapplication area, regarding to their fuzzy or crisp nature. Sections 4 and 5, categorized papers into the application area; includes 386 papers (61.5%), categorized into twelve subareas and non-application area includes 242 papers (38.5%). Section 6 classified scholarly papers by distribution of applied papers by year of publication, journal of publication, fuzzy or crisp nature of their methods and authors’ nationality. Section 7 is conclusion.

Jen Huei Chang

Papers

A fuzzy multi-criteria decision making approach for solving a bi-objective personnel assignment problem