A multi-level non-linear multi-objective decision-making under fuzziness
This paper studies a three-level non-linear multi-objective decision-making (TLN-MODM) problem with linear (or non-linear) constraints, and in which the objective function at every level are non-linear functions which are to be maximized. This paper makes an extension work of Abo-Sinna [J. Operat. R...
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| Published in: | Applied mathematics and computation Vol. 153; no. 1; pp. 239 - 252 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
New York, NY
Elsevier Inc
25.05.2004
Elsevier |
| Subjects: | |
| ISSN: | 0096-3003, 1873-5649 |
| Online Access: | Get full text |
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| Summary: | This paper studies a three-level non-linear multi-objective decision-making (TLN-MODM) problem with linear (or non-linear) constraints, and in which the objective function at every level are non-linear functions which are to be maximized. This paper makes an extension work of Abo-Sinna [J. Operat. Res. Soc. India (OPSEARCH) 38 (5) (2001) 484–495] which deal with a bi-level non-linear multi-objective decision-making problem under Fuzziness.
The three level programming (TLP) problem, whether from the stand point of the three-planner Stackelberg behavior or from the interactive organizational behavior, is a very practical problem and encountered frequently in actual practice.
This paper proposes a three-planner multi-objective decision-making model and solution method for solving this problem. This method uses the concepts of tolerance membership function and multi-objective optimization at each level to develop a fuzzy Max–Min decision model for generating Pareto optimal (satisfactory) solution for TLN-MODM problem; the first level decision maker (FLDM) specifies his/her objective functions and decisions with possible tolerances which are described by membership functions of fuzzy set theory. Then, the second level decision-maker (SLDM) specifies his/her objective functions and decisions, in the view of the FLDM, with possible tolerances which are described by membership functions of fuzzy set theory. Finally, the third level decision-maker (TLDM) uses the preference information for the FLDM and SLDM to solves his/her problem subject to the two upper level decision-makers restrictions. An illustrative numerical example is given to demonstrate the obtained results. |
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| ISSN: | 0096-3003 1873-5649 |
| DOI: | 10.1016/S0096-3003(03)00628-3 |