

The specific problem that occurs in multi-criteria decision-making (MCDM) processes is ranking a number of alternatives using complex criteria functions (the hierarchical structure of criteria) whose values must consider the impacts of all-important characteristics and parameters of alternatives. The problem becomes more complex by increasing the number of levels of sub-criteria functions (degree of decomposition). This paper proposes an extended procedure based on the mean values conversion of the net outranking flow of sub-criterion functions obtained by modified PROMETHEE methods. The actual value of criterion functions is used only at the last level, and transformed values of the net outranking flow for generating a final rank of alternatives are introduced at other levels. This procedure provides a more objective comparison of the impact of various individual criteria to rank the alternatives and easier making of unique solution, where the impact of decision-maker (DM) experience and subjective estimation is minimised in the selection. Applicability and practicability of the presented procedure for solving the selection problem of a logistics warehouse location are demonstrated in the analysis of a case study example. © 2020, Strojarski Facultet. All rights reserved.
| Engineering controlled terms: | LocationMultiobjective optimization |
|---|---|
| Engineering uncontrolled terms | Criteria functionsCriterion functionsDegree of decompositionHierarchical structuresLocation problemsMulti-criteria decision makingMulticriteria optimizationPROMETHEE |
| Engineering main heading: | Decision making |
| Funding sponsor | Funding number | Acronym |
|---|---|---|
| Ministarstvo Prosvete, Nauke i Tehnološkog Razvoja | MPNTR |
A part of this research is a contribution to the project TR 35038 funded by the Ministry of Education, Science and Technological Development of the Republic of Serbia.
Marković, G.; Faculty of Mechanical and Civil Engineering in Kraljevo, University of Kragujevac, Dositejeva 19, Kraljevo, Serbia;
© Copyright 2020 Elsevier B.V., All rights reserved.