Modeling and simulating for the treatment of subjectivity in the process of choosing personnel using fuzzy logic

Every day organizations pay more attention to Human Resources Management, because the human factor is preponderant in the results of it. One of the important policies is the Selection of Personnel, these are needed for their decision-making results, which in many organizations is done in a subjective manner and which brings consequences not very favorable to them. Taking this problem into account, it is decided to design and apply procedures and tools of fuzzy mathematics to reduce subjectivity and uncertainty in decision-making, creating work algorithms for this policy that includes multifactorial weights and analysis with measurement indicators that they allow tangible and reliable results. In this case of personnel selection, eight candidates were taken into account and by applying a diffuse evaluation system, the candidate with the highest rating of 98% was chosen. This indicates that subjectivity was reduced when choosing the best evaluated candidate

Fit between humanitarian professionals and project requirements: hybrid group decision procedure to reduce uncertainty in decision-making

Choosing the right professional that has to meet indeterminate requirements is a critical aspect in humanitarian development and implementation projects. This paper proposes a hybrid evaluation methodology for some non-governmental organizations enabling them to select the most competent expert who can properly and adequately develop and implement humanitarian projects. This methodology accommodates various stakeholders’ perspectives in satisfying the unique requirements of humanitarian projects that are capable of handling a range of uncertain issues from both stakeholders and project requirements. The criteria weights are calculated using a two-step multi-criteria decision-making method: (1) Fuzzy Analytical Hierarchy Process for the evaluation of the decision maker weights coupled with (2) Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to rank the alternatives which provide the ability to take into account both quantitative and qualitative evaluations. Sensitivity analysis have been developed and discussed by means of a real case of expert selection problem for a non-profit organisation. The results show that the approach allows a decrease in the uncertainty associated with decision-making, which proves that the approach provides robust solutions in terms of sensitivity analysis