The aim of the paper is to present a new global optimization method for determining all the optima of the Least Squares Method (LSM) problem of pairwise comparison matrices. Such matrices are used, e.g., in the Analytic Hierarchy Process (AHP). Unlike some other distance minimizing methods, $LSM$ is usually hard to solve because of the corresponding nonlinear and non-convex objective function. It is found that the optimization problem can be reduced to solve a system of polynomial equations. Homotopy method is applied which is an efficient technique for solving nonlinear systems. The paper ends by two numerical example having multiple global and local minima
Adaptive Least Squares Matching (ALSM) is a powerful technique for precisely locating objects in dig...
Polynomial systems can be solved via LMI (linear matrix inequality) optimizations by exploiting the ...
The approximate solution of optimization and optimal control problems for systems governed by linear...
The aim of the paper is to present a new global optimization method for determining all the optima ...
The aim of the paper is to present a new global optimization method for determining all the optima o...
This is a follow up to “Solution of the least squares method problem of pairwise comparisons matrix”...
The Analytic Hierarchy Process (AHP) is one of the most popular methods used in Multi-Attribute Deci...
In several methods of multiattribute decision making pairwise comparison matrices are applied to der...
The Analytic Hierarchy Process (AHP) is one of the most popular methods used in Multi-Attribute Deci...
The Analytic Hierarchy Process (AHP) is one of the most popular methods used in Multi-Attribute Deci...
In several methods of multiattribute decision making, pairwise comparison matrices are applied to de...
The Analytic Hierarchy Process (AHP) is one of the most popular methods used in Multi-Attribute Deci...
A general procedure is described for setting up monotonically convergent algorithms to solve some ge...
This thesis introduces a globalization strategy for approximating global minima of zero-residual lea...
Some multiple-criteria decision making methods rank actions by associating weights to the different ...
Adaptive Least Squares Matching (ALSM) is a powerful technique for precisely locating objects in dig...
Polynomial systems can be solved via LMI (linear matrix inequality) optimizations by exploiting the ...
The approximate solution of optimization and optimal control problems for systems governed by linear...
The aim of the paper is to present a new global optimization method for determining all the optima ...
The aim of the paper is to present a new global optimization method for determining all the optima o...
This is a follow up to “Solution of the least squares method problem of pairwise comparisons matrix”...
The Analytic Hierarchy Process (AHP) is one of the most popular methods used in Multi-Attribute Deci...
In several methods of multiattribute decision making pairwise comparison matrices are applied to der...
The Analytic Hierarchy Process (AHP) is one of the most popular methods used in Multi-Attribute Deci...
The Analytic Hierarchy Process (AHP) is one of the most popular methods used in Multi-Attribute Deci...
In several methods of multiattribute decision making, pairwise comparison matrices are applied to de...
The Analytic Hierarchy Process (AHP) is one of the most popular methods used in Multi-Attribute Deci...
A general procedure is described for setting up monotonically convergent algorithms to solve some ge...
This thesis introduces a globalization strategy for approximating global minima of zero-residual lea...
Some multiple-criteria decision making methods rank actions by associating weights to the different ...
Adaptive Least Squares Matching (ALSM) is a powerful technique for precisely locating objects in dig...
Polynomial systems can be solved via LMI (linear matrix inequality) optimizations by exploiting the ...
The approximate solution of optimization and optimal control problems for systems governed by linear...