RAIRO - Operations Research, Volume (55), No (5), Year (2021-9) , Pages (3107-3119)

Title : ( Assignment model with multi-objective linear programming for allocating choice ranking using recurrent neural network )

Authors: Zahra Sadat Mirzazadeh , Javad Bani hassan , Amin Mansoori ,

Citation: BibTeX | EndNote

Abstract

Classic linear assignment method is a multi-criteria decision-making approach in which criteria are weighted and each rank is assigned to a choice. In this study, to abandon the requirement of calculating the weight of criteria and use decision attributes prioritizing and also to be able to assign a rank to more than one choice, a multi-objective linear programming (MOLP) method is suggested. The objective function of MOLP is defined for each attribute and MOLP is solved based on absolute priority and comprehensive criteria methods. For solving the linear programming problems we apply a recurrent neural network (RNN). Indeed, the Lyapunov stability of the model is proved. Results of comparing the proposed method with TOPSIS, VICOR, and MOORA methods which are the most common multi-criteria decision schemes show that the proposed approach is more compatible with these methods.

Keywords

, MODEL , LINEAR PROGRAMMING, ALLOCATING CHOICE, RECURRENT NEURAL2 NETWORK
برای دانلود از شناسه و رمز عبور پرتال پویا استفاده کنید.

@article{paperid:1086742,
author = {Mirzazadeh, Zahra Sadat and Bani Hassan, Javad and Mansoori, Amin},
title = {Assignment model with multi-objective linear programming for allocating choice ranking using recurrent neural network},
journal = {RAIRO - Operations Research},
year = {2021},
volume = {55},
number = {5},
month = {September},
issn = {0399-0559},
pages = {3107--3119},
numpages = {12},
keywords = {MODEL -LINEAR PROGRAMMING-ALLOCATING CHOICE-RECURRENT NEURAL2 NETWORK},
}

[Download]

%0 Journal Article
%T Assignment model with multi-objective linear programming for allocating choice ranking using recurrent neural network
%A Mirzazadeh, Zahra Sadat
%A Bani Hassan, Javad
%A Mansoori, Amin
%J RAIRO - Operations Research
%@ 0399-0559
%D 2021

[Download]