DocumentCode :
3117193
Title :
Multi-level multi-objective decision problem through fuzzy random regression based objective function
Author :
Arbaiy, Nureize ; Watada, Junzo
Author_Institution :
Grad. Sch. of Inf., Production & Syst., Waseda Univ., Kitakyushu, Japan
fYear :
2011
fDate :
27-30 June 2011
Firstpage :
557
Lastpage :
563
Abstract :
A multi-level decision making problem confronts several issues especially in coordinating decision in hierarchic processes and in compromising conflicting objectives for each decision level. Therefore, its mathematical model plays a pivotal role in solving such problem, and is influencing to the final result. However, it is sometimes difficult to estimate the coefficients of objective functions of the model in real situations specifically when the statistical data contain random and fuzzy information. Thus, decision making scheme should provide an appropriate method to handle the presence of such uncertainties. Hence, this paper proposes a fuzzy random regression method to estimate the coefficients value for the objective functions of multi-level multi-objective model. The algorithm is constructed to obtain a satisfaction solution, which fulfills at least weak Pareto optimality. A numerical example illustrates the proposed solution procedure.
Keywords :
Pareto optimisation; decision making; fuzzy set theory; hierarchical systems; random processes; regression analysis; uncertainty handling; Pareto optimality; coefficients value; fuzzy random regression method; hierarchic process; mathematical model; multilevel multiobjective decision making problem; objective functions; satisfaction solution; uncertainty handling; Additives; Decision making; Delta modulation; Mathematical model; Production; Programming; Random variables; additive fuzzy goal programming; fuzzy random regression model; multi-level problem; multi-objective;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems (FUZZ), 2011 IEEE International Conference on
Conference_Location :
Taipei
ISSN :
1098-7584
Print_ISBN :
978-1-4244-7315-1
Electronic_ISBN :
1098-7584
Type :
conf
DOI :
10.1109/FUZZY.2011.6007355
Filename :
6007355
Link To Document :
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