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Showing 2 results for Esmaeili
Fatemeh Sadat Seyed Esmaeili, Mohsen Rostamy-Malkhalifeh, Farhad Hosseinzadeh Lotfi,
Volume 1, Issue 2 (12-2020)
Abstract
The main goal of this paper is to propose interval network data envelopment analysis (INDEA) model for performance evaluation of network decision making units (DMUs) with two-stage network structure under data uncertainty. It should be explained that for dealing with uncertainty of data, an interval programming method as a popular uncertainty programming approach is applied. Also, to show the applicability of proposed model, INDEA approach is implemented for performance measurement and ranking of 10 insurance companies from Iranian insurance industry. Note that insurance companies are undoubtedly one of the most important pillars of the financial markets, whose great performance will drive the economy of the country. The empirical results indicate that the proposed INDEA is capable to be utilized to assess the performance of two-stage DMUs in the presence of interval data.
Mr Saeed Banimehri, Mr Hamid Esmaeili,
Volume 3, Issue 2 (12-2022)
Abstract
In this paper, a new modified line search Armijo is used in the diagonal discrete gradient bundle method to solve large-scale non-smooth optimization problems. The new principle causes the step in each iteration to be longer, which reduces the number of iterations, evaluations, and the computational time. In other words, the efficiency and performance of the method are improved. We prove that the diagonal discrete gradient bundle method converges with the proposed monotone line search principle for semi-smooth functions, which are not necessarily differentiable or convex. In addition, the numerical results confirm the efficiency of the proposed correction.
