Interactive intuitionistic fuzzy methods for multilevel programming problems

•Three interactive intuitionistic fuzzy methods are proposed for MLPPs.•A score function is defined to depict decision makers’ satisfactory degree.•Use a new distance function to select a priority solution.•A case study and numerical results show that the proposed methods are efficient. Multilevel p...

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Bibliographic Details
Published in:Expert systems with applications Vol. 72; pp. 258 - 268
Main Authors: Zhao, Xiaoke, Zheng, Yue, Wan, Zhongping
Format: Journal Article
Language:English
Published: New York Elsevier Ltd 15.04.2017
Elsevier BV
Subjects:
Algorithms
Cloud computing
Decision making
Enumeration
Fuzzy sets
Intelligent systems
Interactive intuitionistic fuzzy method
Mathematical models
Multilevel
Multilevel programming
Optimization
Penalty function
Programming
Satisfactory solution
Studies
Interactive intuitionistic fuzzy method
Multilevel programming
Decision making
Satisfactory solution
ISSN:0957-4174, 1873-6793
Online Access:Get full text
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Summary:•Three interactive intuitionistic fuzzy methods are proposed for MLPPs.•A score function is defined to depict decision makers’ satisfactory degree.•Use a new distance function to select a priority solution.•A case study and numerical results show that the proposed methods are efficient. Multilevel programming problems model a decision-making process with a hierarchy structure. Traditional solution methods including vertex enumeration algorithms and penalty function methods are not only inefficient to obtain the solution of the multilevel programming problems, but also lead to a paradox that the follower’s decision power dominates the leader’s. In this paper, both multilevel programming and intuitionistic fuzzy set are used to model problems in hierarchy expert and intelligent systems. We first present a score function to objectively depict the satisfactory degrees of decision makers by virtue of the intuitionistic fuzzy set for solving multilevel programming problems. Then we develop three optimization models and three interactive intuitionistic fuzzy methods to consider different satisfactory solutions for the requirements of expert decision makers. Furthermore, a new distance function is proposed to measure the merits of a satisfactory solution. Finally, a case study for cloud computing pricing problems and several numerical examples are given to verify the applicability and the effectiveness of the proposed models and methods.
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ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2016.10.063