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**Interactive balance space approach for solving multi-level multi-objective programming problems.**
*(English)*
Zbl 1278.90350

Summary: This paper studies a multi-level multi-objective decision-making (ML-MODM) problems with linear or non-linear constraints. The objective functions at each level are non-linear functions, which are to be maximized or minimized.This paper presents a three-level multi-objective decision-making (TL-MODM) model and an interactive algorithm for solving such a model. The algorithm simplifies three-level multi-objective decision-making problems by transforming them into separate multi-objective decision making problems at each level, thereby avoiding the difficulty associated with non-convex mathematical programming. Our algorithm is an extension of the work of X. Shi and H. Xia [J. Oper. Res. Soc. 48, No. 9, 943–949 (1997; Zbl 0892.90200)], which dealt with interactive bi-level multi-objective decision-making problems, with some modifications in assigning satisfactoriness to each objective function in all the levels of the TL-MODM problem. Also, we solve each separate multi-objective decision making problem of the TL-MODM problem by the balance space approach.

A new formula is introduced to interconnect the satisfactoriness and the proportions of deviation needed to reflect the relative importance of each objective function. Thus, we have the proportions of deviation including satisfactoriness.

In addition, we present new definitions for the satisfactoriness and the preferred solution in view of singular-level multi-objective decision making problems that corresponds to the \(\eta\)-optimal solution of the balance space approach. Also, new definitions for the feasible solution and the preferred solution (\(\eta\)-optimal point) of the TL-MODM problem are presented. An illustrative numerical example is given to demonstrate the algorithm.

A new formula is introduced to interconnect the satisfactoriness and the proportions of deviation needed to reflect the relative importance of each objective function. Thus, we have the proportions of deviation including satisfactoriness.

In addition, we present new definitions for the satisfactoriness and the preferred solution in view of singular-level multi-objective decision making problems that corresponds to the \(\eta\)-optimal solution of the balance space approach. Also, new definitions for the feasible solution and the preferred solution (\(\eta\)-optimal point) of the TL-MODM problem are presented. An illustrative numerical example is given to demonstrate the algorithm.

### Keywords:

multi-objective optimization; nonscalarized global optimization methods; balance set; interactive methods; multi-level programming problem; satisfactoriness### Citations:

Zbl 0892.90200
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\textit{M. A. Abo-Sinna} and \textit{I. A. Baky}, Inf. Sci. 177, No. 16, 3397--3410 (2007; Zbl 1278.90350)

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### References:

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