Non-linear Optimization
Seyed Hamzeh Mirzaei; Ali Ashrafi
Abstract
Purpose: One of the most effective methods for solving unconstrained optimization problems is the trust region method. The strategy of determining the radius of the trust region has a significant effect on the efficiency of this method. On the other hand, imposing the monotonocity condition will decrease ...
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Purpose: One of the most effective methods for solving unconstrained optimization problems is the trust region method. The strategy of determining the radius of the trust region has a significant effect on the efficiency of this method. On the other hand, imposing the monotonocity condition will decrease the convergence speed of this method. Therefore, improving and increasing the efficiency of this method is one of the most important issues and the attention of researchers.Methodology: Establishing a new adaptive trust region radius as well as combining the trust region method with a non-monotone strategy to avoid the adverse effects of monotonocity.Findings: A new adaptive trust region radius converged to zero is provided and then trust region combination is performed with a non-monotone strategy. Running the algorithm on a set of test functions shows that the new adaptive radius along with the non-monotone strategy used significantly improves the efficiency of the trust region method.Originality/Value: The presented non-monotone adaptive algorithm has a second-order convergence rate. In addition, it significantly reduces computational costs compared to traditional algorithms. On the other hand, the new adaptive radius avoids the ineffectiveness of the trust region close to the solution.
Data Envelopment Analyses
Seyed Hamzeh Mirzaei
Abstract
One of the problems of based models on data envelopment analysis (DEA) for ranking preference voting systems is that it allows each alternative have its own weight vector. Therefore, alternatives are evaluated with different weight vectors. In this study, we propose a model based on fuzzy logic to solve ...
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One of the problems of based models on data envelopment analysis (DEA) for ranking preference voting systems is that it allows each alternative have its own weight vector. Therefore, alternatives are evaluated with different weight vectors. In this study, we propose a model based on fuzzy logic to solve the weaknesses of the previous models. This model is based on the solving of multi-objective programming models with the help of fuzzy logic, in this way it providing a vector of common weights, and finally, we can rank the alternatives.