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Showing 3 results for Darvishi

Dr. Davood Darvishi,
Volume 9, Issue 1 (7-2018)
Abstract

Linear programming problems with interval grey numbers have recently attracted some interest. In this paper, we study linear programs in which right hand sides are interval grey numbers. This model is relevant when uncertain and inaccurate factors make difficult the assignment of a single value to each right hand side. Some methods have been developed for solving these problems. In this paper, we propose a new approach for solving interval grey number linear programming problems is introduced without converting them to classical linear programming problems. A numerical example is provided to illustrate the proposed approach.
Dr Hamid Reza Yousefzadeh, Dr Davood Darvishi, Mrs Arezoo Sayadi Salar,
Volume 11, Issue 1 (9-2020)
Abstract

Ant colony optimization (ACOR) is a meta-heuristic algorithm for solving continuous optimization
problems (MOPs). In the last decades, some improved versions of ACO
R have been proposed.
The UACO
R is a unified version of ACOR that is designed for continuous domains. By adjusting
some specified components of the UACO
R, some new versions of ACOR can be deduced. By doing
that, it becomes more practical for different types of MOPs. Based on the nature of meta-heuristic
algorithms, the performance of meta-heuristic algorithms are depends on the exploitation and
exploration, which are known as the two useful factors to generate solutions with different
qualities. Since all the meta-heuristic algorithms with random parameters use the probability
functions to generate the random numbers and as a result, there is no any control over the
amount of diversity; hence in this paper, by using the best parameters of UACO
R and making
some other changes, we propose a new version of ACO
R to increase the efficiency of UACOR.
These changes include using chaotic sequences to generate various random sequences and also
using a new local search to increase the quality of the solution. The proposed algorithm, the two
standard versions of UACO
R and the genetic algorithm are tested on the CEC05 benchmark
functions, and then numerical results are reported. Furthermore, we apply these four algorithms
to solve the utilization of complex multi-reservoir systems, the three-reservoir system of Karkheh
dam, as a case study. The numerical results confirm the superiority of proposed algorithm over
the three other algorithms.

 
Jafar Pourmahmoud, Mahdi Eini, Davood Darvishi Salokolaei, Saeid Mehrabian,
Volume 14, Issue 2 (12-2023)
Abstract

In the evaluation of decision making units with classical models of data envelopment analysis, it is assumed that the factors are deterministic. In some decision-making problems, the amount of inputs or outputs of the units is not exactly known and it is a three-parameter interval in grey form. In this case, it is recommended to choose the factors from their center of gravity. In the classic models of data envelopment analysis, all factors are also considered desirable, but in real problems there are undesirable factors too which cannot be used to evaluate problems with undesirable inputs and undesirable outputs. In this paper, a model is presented for calculating the efficiency of decision making units in the presence of the center of gravity of undesirable three-parameter interval grey undesirable factors based on the combination of strong and weak disposability principles. To this end, the proposed method is discussed with a practical example.
 

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مجله انجمن ایرانی تحقیق در عملیات Iranian Journal of Operations Research
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