In the transition to knowledge-based economy, ensuring effective performance and competitiveness of the or- ganization (enterprises, companies, firms, etc.) requires increased attention to the personnel, i.e. human factor. Employees of the organizations are considered as the main strategic resource, ensuring its performance and achievements of its objectives. According to this concept, the staff becomes one of the main resources of the or- ganization and the necessary funds must be invested to ensure its proper management and optimal conditions for its development [1] .

The concept basis of personnel management constitutes an increasing role of the worker’s individuality, his knowledge of motivational attitudes, and his ability to shape and direct them in accordance with the challenges facing the organization. Intelligent capital occupies a special position among other assets and requires specific approaches to the management perspective [2] . Evaluation of intelligent capital of the organization is needed to determine its effectiveness and growth factors, as well as to make decisions on the advisability of investment in this resource.

Objectives of human resource management (HRM) are the basis of personnel policy. The correct solution to these problems, making objective and transparent decisions on HRM allows the organization to achieve its global goals [3] [4] . In general, today, an effective HRM becomes the strategy of the company. In this case, the funds invested in the development of human resources, transform into an investment, not expenditure [5] . The changes, occurred in the labor market, require major changes in the relationship with employees, in the policy of their recruitment, retention and motivation. In this regard, human resource management at the professional level has become a strong modern means used in HR. Fundamentally new attitude towards the personnel as valuable resource of the organization actualizes the importance of developing new conceptual approaches and technolo- gies for HRM. Therefore, in recent years, computer technology is increasingly used for the HRM problem solu- tions.

Thus, to make more objective decisions regarding personnel planning, selection, recruitment, adaptation, fir- ing, promotion, development, training and motivation of personnel the decision-maker (DM) must evaluate and take into account the information in each case, that characterizes the applicant, his interests, potential impacts and results. Essential factor for the quality of personnel management is its assessment using competencies. The problems solved in the field of HRM are complex and varied. They are united by the fact that the finite number of evaluated objects is used as the raw data, and these objects are characterized by a set of diverse features, i.e. these tasks are multicriterial, and many factors should be taken into account, many influences, preferences, in- terests and consequences, characterizing alternatives should be evaluated [6] - [8] .

Volume, quantitative and qualitative nature, complexity and contradictions of the information flow to be reached to the decision-makers, as well as the need to address the interrelationship of numerous factors, dynamic situation created difficulties in decision-making on human resource management. To overcome these difficulties, and consequently, more effective HRM of the organization the application of intelligent decision support tech- nologies seems appropriate [7] - [9] .

The following problems belong to the HRM problems that are most frequently met in practice [4] [10] : selec- tion of applicant on a vacant position; compliance of workers to requirements of a workplace, a position; forma- tion of a personnel reserve and planning of vocational advancement, career; selection of people on key positions in operation of business; awarding, compensation of employees etc.

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 (candidates applying for the position).

Personnel selection often acts the most important role for controlling the human source and quality in HRM [4] [11] [12] . Effective employee selection is a critical component of a successful organization. Personnel selection is the process of collecting and evaluating information about individuals and choosing those who match the qua- lifications needed to perform a predefined job in the best way [13] . This process plays a determining role in HRM and is crucial to the success of an organization.

References [14] and [15] reviewed the personnel selection studies and found that the several main factors in- cluding change in organizations, change in work, change in personnel, change in the society, change of laws, and change in marketing have influenced personnel selection. In literature, there are a number of studies which use heuristic methods for employee selection. A fuzzy MCDM framework based on the concepts of ideal and anti-ideal solutions for the most appropriate candidate is presented in [16] . Also, a fuzzy number ranking me- thod by metric distance for personnel selection problem was proposed in [17] and a personnel selection system based on fuzzy AHP was developed in [18] .

In addition, researchers used fuzzy technique for order preference by similarity to ideal solition (TOPSIS) based on the veto threshold for ranking job applicants [19] - [22] .

Recently, owing to the advancements in information technology, researchers have developed decision support systems and expert systems to improve the outcomes of HRM [23] [24] .

A model to design an expert system for effective selection and appointment of the job applicants is developed in [25] . The applications of expert system or decision support systems on personnel selection and recruitment are increasing [11] [12] [26] . In this paper, the description of fuzzy decision-making support method in the solu- tion of employment problems is given, and comparison of the results obtained by this method application and the results obtained by real use of approach are presented hereunder.

Therefore, the goal of personnel selection is applying a valid and effective method to reduce the risks of hir- ing an unsuitable employee, and increase the opportunities to find an eligible employee who can enhance the productivity of the organization [4] [27] . In other words, businesses find eligible employees meet the require- ments of organization and occupation from mass job applicants through effective personnel selection methods.

The technique for the personnel selection proposed by the authors in this paper has the following advantages: 1) allows the use of both qualitative and quantitative data; 2) removes the limit on the number of criteria and the number of experts; 3) takes into account the hierarchical structure of criteria. The main advantage of the article is to carry out the step calculation and allowing the comparison of experimental results with real data.

Referring to fuzzy logic formalism, fuzzy TOPSIS method was used for evaluation and selection of alternatives in realization of decision making support system in hiring issues of candidates. For realization of the system, primarily a general criteria system is formed in order to evaluate hired employees to the plant. This system con- tains criteria and characterizing indicators allowing evaluating candidates hiring to any department or position at the plant.

Candidate evaluation issue for hiring to HRM department of the plant has been reviewed during conducted experiment. For this purpose, following criteria and criteria indicators were determined from the general criteria system with participation of experts for appointment to the position:

―science and education criteria and indicators characterizing it:

―relevance of completed education to corresponding job;

―character of investigator.

―behavior and appearance criteria and indicators characterizing it:

―balanced;

―well-conducted and polite.

―personal psychological criteria and indicators characterizing it:

―hardworking, industrious;

―creative;

―loyal;

―high intelligence.

―functional activity criteria and indicators characterizing it:

―work capability;

―learning capability.

―medical criteria and indicators characterizing it:

―physical health;

―spiritual and psychological health.

Results obtained from evaluation of these indicators―will define the value of chance―-hiring chance of the candidate.

Result to be obtained based on fuzzy TOPSIS method-, will express the hiring chance of candi- date as a value defined in interval. Depending on this value, experts pre-form following hiring decision options:

1. If, then this candidate decidedly cannot be hired;

2. If, hiring of this candidate carries great risk;

3. If, hiring of this candidate carries a bit of risk;

4. If, this candidate can be hired;

5. If, this candidate is unconditionally hired.

In the next stage, importance coefficients of these criteria and their characterizing indicators relatively to each other are defined, for this objective paired comparison method is referred to, detection of contradictions in ex- perts’ evaluation is reviewed [30] [37] . Based on obtained results, weight coefficients of criteria indicators have been defined in accordance with hierarchic analysis method (Table 2).

Relevance of hiring of 3 candidates to listed criteria indicators has been evaluated in accordance with Table 3 with participation of 4 experts.

Based on Formula (3), single trapeze matrix is developed based on individual evaluation of experts. Results of single trapeze fuzzy matrix in accordance with and criteria indicators are provided below (Table 4).

Based on (4) formula, single trapeze matrix is formed and all its elements are multiplied by weight coeffi- cients of criteria in accordance with Formula (5) and resultants are given in Table 5.

ISO and EBS single matrixes are developed on existing grounds of alternatives. ISO proximity matrix with dimensions reflecting the obtained results is given in Table 6.

EBS remoteness proximity with dimensions reflecting remoteness of alternatives from EBS is

as following and resultants are given in Table 7.

Numerical value of proximity to ISO, remoteness from EXP and relevance to ideal solution of each alterna- tive in accordance with all criteria is calculated resultants are given in Table 8.

Based on obtained results, the best solution option is alternative and the value of its hiring chance is. In accordance with decision options of the experts: this candidate can be hired. In accordance with next listing, alternative is. And alternatives equal to and their hiring chance value matches the identical decision option: hiring of this candidate can carry a bit of risk.

The proposed approach was foreseen for realization of support system applied to decision-making issues in the employment of applicants within SOCAREF2013¹ grant project. It should be noted that at the moment SOCAR department of human resourses management for applicants evaluation in the enployment issues realization bases on their precise report indexes, expert assessment defined on the bases of quality competition and final results are determined by point system. In order to ground benefits of the approach proposed in the article the results of approach application have been compared with the results of point system application herewith.

With this purpose let’s look through alternatives decision formation given in Table 3 that was compiled on the basis of expert evaluation with references to point system.

For alternatives evaluation on the basis of points system “very good” equals 10 points, “good”―8 points, “medium good”―6 points and “fair”―4 points.

Table 9 given below is being compiled on the basis of statistic results of evaluation by considered three alter- natives criteria indexes according to Table 3.

According to the statistic results obtained on the basis of point system the correspondence degree of each alternative to the ideal solution (480 points) is defined. In this case the highest point alternative is very good, next is and the last is alternative.

The decision per each alternative is made according to its ideal sulution correspondence estimate:

alternative―this candidate is unconditionally hired.

alternative―this candidate is unconditionally hired.

alternative―this candidate is unconditionally hired.

The results obtained according to the proposed method are compared with the results of application of point system approach in Table 10 herein:

As it is seen the results of point system application in the solution of applicant employment problem differs from the results of proposed FDMSM application and this method supports the employment of “unconditionally hired” employee rather than “risk-carrying” as appointed by point system.

Traditional methods of multi-criteria assessment and ordering cannot effectively solve the problem of the group (collective) decision making under imprecise and linguistic information. Basing on the proposed model and me- thod, the key features of more objective and transparent management decisions of the personnel are as follows:

Ÿ The number of criteria and criteria indicators characterizing the issue are not restricted;

Ÿ The quality of criteria indicators characterizing the issue, the importance and advantage of criteria and crite- ria indicators in relation to each other are taken into account, and the conflict is determined;

Ÿ Subjectivity of decision-maker in the decision-making process are reduced, more objective and transparent decisions are made.

The proposed method for multi-criteria assessment and ranking can be applied for solving the problems of Personnel Management, as well as for other problems arising from the human activity.

However, the criteria, assessment indicators characterizing assessed objects should be formed previously and their importance coefficients should be determined using appropriate methods. Quite difficult and time-con- suming procedure for implementing the above steps is a weak point of the proposed approach.

One of the advantages of this approach is possibility of taking into consideration the competence of the par- ticipating experts in appropriate subject domain. Thus, Decision-Maker do not always consider these experts’ competency equal in appropriate subject and their competence is considered only within decision-making pro- cess. That’s why we are planning to consider this parameter also in our future researches.