FTOPSIS

The TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) method and its expansion were introduced five decades ago. During the recent years, the distinct techniques of multi-criteria decision-making (MCDM) have been used to develop decision makers to select better alternatives for various decision making problems. In this paper we represent the fuzzy set and TOPSIS according to the traditional decision theory with different algorithms. Using the algorithms ranking order of TOPSIS method, fuzzy TOPSIS method are calculated by closeness coefficients based on negative ideal solution (NIS) and proximity of positive ideal solution (PIS). Lastly, we present few applications of fuzzy TOPSIS method.

Human  Resource  Selection  (HRS)  is  considered
to be the most important aspect of HR department
as it requires fishing best talents from job markets.
Decision makers  are involved in order to evaluate
multi-alternatives  with  respect  to  multi-criteria.
The  data  needed  for  the  evaluation  process  are
sometimes  crisp  and  vague  in  nature.  Such
circumstances  cause  difficulty  to  fairly  judge  the
alternatives  based  on  the  selected  evaluation
criteria.  This  study  aims  to  design  a  framework
for Integrated  Decision Support System  based  on
TOPSIS  models  for  HRS.  The  IDSS  model
comprises  of  Technique  for  Order  Preference  by
Similarity  to  Ideal  Solution  (TOPSIS),  Fuzzy
TOPSIS  and  Fuzzy  Set  theory.  Successful
integration  of  these  models  will  provide  a
platform  for  DM’s  to  conduct  HRS  process
assuring fair judgment among applicants.

This paper employs three Fuzzy Multi-Criteria Decision Making (FMCDM) methodologies in the evaluation and selection of robots for automated foundry operations. In the methodologies, a Fuzzy Analytical Hierarchy Process (FAHP) is integrated individually with a Fuzzy Technique for Order Preference by Similarity to the Ideal Solution (FTOPSIS), a Fuzzy VIsekriterijumska optimizacija i KOmpromisno Resenje (FVIKOR) and a Complex PRoportional ASsessment method with the application of Grey systems theory (COPRAS-G). In each case, a FAHP is used to estimate the fuzzy weights of the selection criteria under consideration. FTOPSIS, FVIKOR and COPRAS-G are applied to evaluate as well as to select the robots. A real life problem of robots selection in foundry operation is cited to demonstrate and validate the applicability and potentiality of the employed methodologies. A comparative analysis of the results obtained by the methodologies is carried out. The study finds that the employed methodologies are useful, effective and sound surrogates for selecting the best robot in an FMCDM environment.