Multicriteria HR Allocation Based on Hesitant Fuzzy Sets and Possibilistic Programming (original) (raw)

https://doi.org/10.12700/APH.12.3.2015.3.11

Uploaded (2022) | Journal: Acta Polytechnica Hungarica

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Abstract

We focus in this paper on posing and solving a problem of human resource management, namely allocating n people into m groups, such that each group satisfies minimal quality conditions. Each individual is evaluated for every quality by the expert who grades them using hesitant fuzzy numbers, thus enabling a more realistic mark giving method by avoiding artificially imposed accuracy. We compare results with crisp models of Lin and Gen and discuss the significance of fuzzy methodology.

An extension of fuzzy TOPSIS for personnel selection

2009

Considering the fact that contemporary business settings call for work in groups, team selection and formation is a crucial parameter for the smooth function and therefore the achievement of the specific team and business objectives. The problem of team selection members is particularly complex due to the variety of factors and criteria that need to be taken into consideration. Thus, highlighting the complexity in selecting team members, this paper proposes a multi criteria approach to deal with group decision making under fuzzy environment. A Multi Criteria Decision Making Approach (the fuzzy TOPSIS) for group decision making is considered, incorporating a new measurement, which reflects the minimum requirements of the decision makers for each criterion. In this respect, a new reference point is introduced, apart from the Positive Ideal Solution and the Negative Ideal Solution. Finally, an illustrative example of the proposed approach is presented for the selection of a middle level consulting manager.

Applications of fuzzy decision making for personnel selection problem: A review

Journal of Engineering Management and Competitiveness, 2014

Personnel selection determines the input quality of personnel, therefore, plays a decisive role in human resource management. Personnel selection problem has been studied extensively. Selecting the best personnel among many alternatives is a multi-criteria decision making (MCDM) problem. The necessity of dealing with uncertainty in real world problems has been a long-term research challenge that has originated different methodologies and theories. Fuzzy decision making along with their extensions have provided a wide range of tools that are able to deal with uncertainty in different types of problems. Fuzzy decision making methods have become increasingly popular in decision making for personnel selection. Various decision making approaches have been proposed to solve the problem. This paper presents a comprehensive literature review of the applying Fuzzy decision making techniques in personnel selection problem.

Multi-Criteria Decision-Making Methods and Their Applications for Human Resources

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2015

Both within the formation field and the labor market Multi-Criteria Decision Methods (MCDM) provide a significant support to the management of human resources in which the best choice among several alternatives can be very complex. This contribution addresses fuzzy logic in multi-criteria decision techniques since they have several applications in the management of human resources with the advantage of ruling out mistakes due to the subjectivity of the person in charge of making a choice. Evaluating educational achievements as well as the professional profile of a technician more suitable for a job in a firm, industry or a professional office are valuable examples of fuzzy logic. For all of the previous issues subjectivity is a fundamental aspect so that fuzzy logic, due to the very meaning of the word fuzzy, should be the preferred choice. However, this is not sufficient to justify its use; fuzzy technique has to make the system of evaluation and choice more effective and objective...

Application of Fuzzy Optimization Method in Decision-Making for Personnel Selection

Intelligent Control and Automation, 2014

The paper describes the necessity of application of intelligent technologies to support decisions of more objective problems in human resource management. In this paper, we describe the methodology for personnel selection problem for the vacancy with regard to the importance and nonequivalence of numerous indicators characterizing the alternatives. The specific features of the selection problem are highlighted, immersing the problem into a fuzzy environment. A fuzzy multicriterial model of the personnel selection problem is proposed. A technique of order preference by similarity to ideal solition (TOPSIS), was applied for evaluation and regulation of alternatives. This technique is based on criteria of qualitative character, which are hierarchically structured by multiple experts to intellectually support decisions made in personnel selection problem. Using TOPSIS method and generated criteria system an experiment was conducted for evaluation of the candidates during solution of hiring problems. The obtained and reviewed results were compared with results obtained using in reality.

Fuzzy Simple Additive Weighting Method in the Decision Making of Human Resource Recruitment

The Company is one of the jobs that was founded in order to reduce unemployment. The progress of a company is determined by the human resources that exist within the company. So the selection of workers will join the company need to be selected first. The hardest thing in making a selection factor is the effort to eliminate the subjectivity of the personnel manager so that every choice made is objective based on the criteria expected by the company. To help determine who is accepted as an employee in the company, we need a method that can provide a valid decision. Therefore, we use Fuzzy Multiple Attribute Decision Making with Simple Additive Weighting method (SAW) to make a decision making in human resource recruitment. This method was chosen because it can provide the best alternative from a number of alternatives. In this case, the alternative is that the applicants or candidates. This research was conducted by finding the weight values for each attribute. Then do the ranking process that determines the optimal alternative to the best applicants who qualify as employees of the company. Based on calculations by the SAW obtained the two highest ranking results are A5 (alternative 5) and A1 (alternative 1), in order to obtain two candidates received.

The weighted sum preferred levels of performances approach to solving problems in human resources management

Serbian Journal of Management

In the modern market and in competitive business conditions, human resources are the basis of achieving a long-term success and the key resource of competitive advantage. Therefore, employees represent one of the main strategic resources of an organization. The process of the recruitment and selection of personnel plays an extremely important role in human resources management, which tends to provide an organization with motivated and competent personnel. Therefore, the main objective of the paper is to present an approach to solving problems in human resource management, i.e. personnel selection, based on a recently developed multiple-criteria decision making method. The methodology used in the paper is based on the Weighted Sum Preferred Levels of Performances (WS PLP) method adapted for the purpose of an analysis based on decision-makers' preferred levels of performances. The weights of the criteria are determined by using the Step-wise Weight Assessment Ratio Analysis method (the SWARA method). The final ranking order is established by using the weighted averaging operator. Usefulness and efficiency of the proposed approach are considered in the numerical example for the selection of the HR manager. As a result, WS PLP approach can be used for solving personnel selection problems. The proposed multiple-criteria decision-making based approach is easy to use, effective, applicable and adaptable, depending on the goal we want to achieve. In order to solve problems in other areas, the proposed approach can be easily modified.

A new fuzzy decision making approach for personnel selection problem

Intelligent Decision Technologies, 2018

In this study, as a strategic decision-making problem, personnel selection is considered for an organization. Personnel selection is very important issue, matching the qualified personnel with the appropriate vacant position considering the assessment of the organization from each interviewee's in the uncertain environment, for the enterprise performance of the organization. In such problems, the presented candidates for the organization should be evaluated based on the criteria that are determined by the organization. For selecting the most suitable personnel, based on the preferred criteria goaled by the organization and satisfied by the candidates, a fuzzy decision-making approach is proposed. The proposed approach allows an opportunity to evaluate personnel under uncertain enviroment determining the criteria as fuzzy numbers. To show the applicability of our approach, an implementation and its Matlab code is presented. Furthermore, this approach can be applied to the many fields for solving the selection problems in imprecise enviroment and the Matlab code can be adapted to the related problems easily.

Solution of personnel management problem on the basis of fuzzy multi-criterion methods

2011 5th International Conference on Application of Information and Communication Technologies (AICT), 2011

Specific peculiarities of personnel management problem “assigning” the latter to multi-criterion estimation problem in the fuzzy environment are revealed in the article. Classification of personnel management problem is suggested depending on the extent of estimation objects satisfaction to the shown criteria (obligatory and desirable). In the article description of fuzzy relational model of personnel management problems and fuzzy multi-criterion method of scalar optimization allowing estimation and ranging of estimation objects in personnel management tasks are described.

Some fuzzy techniques for staff selection process: A survey

AIP Conference Proceedings, 2013

With high level of business competition, it is vital to have flexible staff that are able to adapt themselves with work circumstances. However, staff selection process is not an easy task to be solved, even when it is tackled in a simplified version containing only a single criterion and a homogeneous skill. When multiple criteria and various skills are involved, the problem becomes much more complicated. In adddition, there are some information that could not be measured precisely. This is patently obvious when dealing with opinions, thoughts, feelings, believes, etc. One possible tool to handle this issue is by using fuzzy set theory. Therefore, the objective of this paper is to review the existing fuzzy techniques for solving staff selection process. It classifies several existing research methods and identifies areas where there is a gap and need further research. Finally, this paper concludes by suggesting new ideas for future research based on the gaps identified.

Design and Development of a Genetic Algorithm Based on Fuzzy Inference Systems for Personnel Assignment Problem

2021

In today’s competitive markets, the role of human resources as a sustainable competitive advantage is undeniable. Reliable hiring decisions for personnel assignation contribute greatly to a firms’ success. The Personnel Assignment Problem (PAP) relies on assigning the right people to the right positions. The solution to the PAP provided in this paper includes the introducing and testing of an algorithm based on a combination of a Fuzzy Inference System (FIS) and a Genetic Algorithm (GA). The evaluation of candidates is based on subjective knowledge and is influenced by uncertainty. A FIS is applied to model experts’ qualitative knowledge and reasoning. Also, a GA is applied for assigning assessed candidates to job vacancies based on their competency and the significance of each position. The proposed algorithm is applied in an Iranian company in the chocolate industry. Thirty-five candidates were evaluated and assigned to three different positions. The results were assessed by ten s...

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

Computers & Industrial Engineering, 2009

Effective personnel assignment is one of the most crucial tasks performed by the decision makers of a company. This paper proposes a systematic approach with a feedback mechanism in which the interdependences among positions and the differences among the selected employees are considered simultaneously. Unfortunately, the two combined considerations have rarely been discussed in the literature. The purpose of this approach is to obtain the best matching of candidates and positions in order to organize a collaboratively cross-functional team. In a fuzzy environment and, then, in the proposed approach, a bi-objective binary integer programming (BOBIP) model is formulated. Based on the weighted composite scores determined in the third step of the proposed procedure, the BOBIP model is transformed into a fuzzy bi-objective goal programming (FBOGP) model. An elaborately designed heuristic algorithm is developed to determine the appropriate values of several important parameters in the FBOGP model, which is solved using LINDO 8.0. An application example is illustrated, and two additional examples are tested. The results indicate that the proposed approach achieves the acceptable satisfaction level and requires less computation time than the brute force enumerative method.

Fuzzy Sets in HR Management

2011

The aim of this paper is to demonstrate the different possible applications of fuzzy sets in HR management. This project is currently being carried out by the AXIOM SW company, which specializes in the implementation of the Microsoft Dynamics NAV information system. The evaluation of employees is based on multiple criteria evaluations. The criteria are derived from typical competencies of the employees. A competency model has been created for any given role with different normalized weights assigned to various competencies. The evaluation proceeds in the following manner: Firstly, the appointed evaluators fill in a questionnaire indicating to what extent, in their view, the tested employee meets his/her competencies. These evaluations are expressed using fuzzy scales. Normalized weights assigned to the evaluators of any given employee are set based on the intensity of cooperation between the employee and his/her evaluators. The level of fulfilment of each competency by the given emp...

A Type-2 Fuzzy Based System for Handling the Uncertainties in Group Decisions for Ranking Job Applicants within Human Resources Systems

Ranking applicants for a given job is one of the most important processes for Human Resources (HR) systems. The ranking of job applicants involves two main processes which are the specification of the requirements criteria for a given job (experience, skills, etc) and the matching between the applicants’ profiles and the job requirements. There is currently a strong move towards automating these two processes to generate an applicants’ ranking system that gives consistent and fair results. However there is a high level of uncertainty involved in these two processes as they involve the input of several experts. These experts will have different opinions, expectations the interpretations for the requirements specification as well as for the applicants matching and ranking. This paper presents a novel approach for ranking job applicants by employing type-2 fuzzy sets for handling the uncertainties in group decisions in a panel of experts. Hence the presented system will enable automating the processes of requirements specification and applicants matching/ranking. We have performed real world experiments in the care domain where our system handled the uncertainties and produced ranking decisions that were consistent with those of the human experts. To the authors’ knowledge, this will be the first type-2 based commercial software system.

Fuzzy Logic Experience Model in Human Resource Management

Lecture Notes in Computer Science, 2005

Job assignment is one of most important functions in human resource management. It presents a new model which optimizes the multi-objectives allocation problem by using fuzzy logic strategic. The fuzzy experience evaluation matrix indicates the score of certain employee on certain task. The values in the matrix are based on the employee's experience. Fuzzy appraisal decisionmaking method provides fuzzy synthesis appraisal matrix referring to individual experience value. Then Task-Arrange or Hungarian Algorithm provides the final solution with the help of our proposed experience matrix. As a numerical example demonstrated, it is helpful to make a realistic decision on human resource allocation under a dynamic environment for organizations.

Personnel Selection Based on Fuzzy Methods Selección De Personal Basada en Métodos Difusos ∗

The decisions of managers regarding the selection of staff strongly determine the success of the company. A correct choice of employees is a source of competitive advantage. We propose a fuzzy method for staff selection, based on competence management and the comparison with the valuation that the company considers the best in each competence (ideal candidate). Our method is based on the Hamming ∗This work has been partially supported by the project TIN2008-06872-C04-02 from the Ministerio de Ciencia e Innovación of Spain. †Departamento de Organización de Empresas, Universidad Politécnica de Valencia, Valencia, Spain. E-Mail: loucada@omp.upv.es ‡Departamento de Matemáticas para la Economı́a y la Empresa, Universitat de Valencia, Valencia, Spain. E-Mail: trinidad.casasus@uv.es §Misma dirección que/same address as T. Casasús. E-Mail: enric.crespo@uv.es ¶Human Resources Manager, Faurecia, Valencia, Spain. E-Mail: tomas.lara@faurecia.com ‖IES Andreu Sempere, Valencia, Spain. E-Mail: jcp...

MEASURING THE PERFORMANCE OF EMPLOYEES WITH FUZZY LOGIC

Journal of International Management Research and Applications, 2024

Employees are the most valuable assets for an organization today. Many factors such as educational background, job skills and abilities should be considered when selecting and evaluating employees. Any institution or organization aims to improve the performance of its employees, to achieve its business goals and to select the right employee when recruiting. Fuzzy logic, which is one of the artificial intelligence techniques, is a decision-making method that enables the strengthening and improvement of human resources and finding the best solution to uncertain problems. In order to select the right employee by using fuzzy logic, many performance evaluation criteria are considered, and the candidates are scored with a decision-making mechanism. This study's objective is to use fuzzy set theory, the Mamdani method, to measure and assess performance during the personnel evaluation and selection process in order to produce the most accurate conclusions for the organization. Fuzzy logic clusters with multiple parameters to provide answers to uncertainties will be used in this study. The performance of current employees is measured using the Mamdani method and training help and awards are given in accordance. According to the outcome as measured, improvements should be made. Candidates are ranked according to their scores, and it is aimed to determine the best one as a result. In order to improve the performance of existing employees with a fuzzy logic decision-making mechanism, first of all, it should be determined which rating criteria the employees lack. Afterward, it is expected that the person will improve himself/herself in this field by providing training according to the needs. If the person is still not at the desired level, the job can be terminated.

Measurement of Employees on Human Resources with Fuzzy Logic

Emerging Markets Journal, 2021

Artificial intelligence, which is the indispensable technology of our age, has started to gain a place in many institutions. Institutions give great importance to human resources management because hiring the right employee for the job will increase productivity within the organization. When recruiting personnel for the position, human resources face difficulties such as measuring the success levels of applicants and deciding whether they are suitable. In this study, in order to provide solutions to the difficulties encountered, a decision-making mechanism is created by using the fuzzy logic method, which is one of the artificial intelligence techniques. This decision-making mechanism measures the performance of people applying for recruitment. While measuring performance, all applications are taken into consideration, and a rule base is formed according to graduation status and experience. The system, which is based on this rule base, evaluates people according to the inputs and finds out their success levels in return. According to the results, it is decided whether the persons are suitable for the position sought. When human resources departments in corporations are combined with artificial intelligence technologies, an advantage will be achieved in the competitive environment between corporations.

Multicriteria Personnel Selection by the Modified Fuzzy VIKOR Method

2020

Correspondence should be addressed to Ramiz M. Aliguliyev; r.aliguliyev@gmail.com Personnel evaluation is an important process in human resource management. The multicriteria nature and the presence of both qualitative and quantitative factors make it considerably more complex. In this study, a fuzzy hybrid multicriteria decision-making (MCDM) model is proposed to personnel evaluation. This model solves personnel evaluation problem in a fuzzy environment where both criteria and weights could be fuzzy sets. The triangular fuzzy numbers are used to evaluate the suitability of personnel and the approximate reasoning of linguistic values. For evaluation, we have selected five information culture criteria. The weights of the criteria were calculated using worst-case method. After that, modified fuzzy VIKOR is proposed to rank the alternatives. The outcome of this research is ranking and selecting best alternative with the help of fuzzy VIKOR and modified fuzzy VIKOR techniques. A compara...

Personnel Selection Based on the Self-Confidence Level of the Decision Maker: A Fuzzy Approach

2019

PERSONNEL SELECTION BASED ON THE SELFCONFIDENCE LEVEL OF THE DECISION MAKER: A FUZZY APPROACH Personnel selection is considered as the decisive factor of the companies’ overall success rate. Appropriate personnel selection is desired in order to enhance the human capital of an organization. As the nature of all selections, personnel selection involves the decision making process. In other words, for effective and efficient personnel selection process managers (or accountable subordinate) who are decision makers (DM), should generate and analyze the possible alternative candidate pool for a vacant position. In order to select the most appropriate and suitable candidate it might be needed to use several effective tools such as linear programming or LP model to be able to obtain the overall ranking weights for the candidates and to minimize the sum of information deviation between the judgment or preference relations of DM and the priority vector w. A novel approach for more robust dec...

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The use of multi-criteria decision-making methods can contribute to finding the most rational solution more easily and efficiently. The purpose of the research is to investigate the applicability of the PROMETHEE and TOPSIS methods at the level of family farms and their comparative analysis in the case of the purchase of agricultural mechanization. Both methods start from a set of criteria established based on the subjective expectations of 48 farmers (decision makers) who were asked to choose the decision criteria. Then, mathematical models are used to determine the most suitable choice for the farm. Based on the research findings, it can be concluded that applying both methods in parallel leads to similar outcomes. Although decision support systems can be instrumental in making the right decisions, their usage is still not widely adopted in family farms due to the challenges of introducing new solutions in a production setting.