In collaboration with Payame Noor University and Iranian Society of Instrumentation and Control Engineers
Control and Optimization
Approximate Pareto Optimal Solutions of Multi objective Optimal Control Problems by Evolutionary Algorithms

Akbar Hashemi Borzabadi; Manije Hasanabadi; Navid Sadjadi

Volume 1, Issue 1 , April 2016, , Pages 1-19

Abstract
  In this paper an approach based on evolutionary algorithms to find Pareto optimal pair of state and control for multi-objective optimal control problems (MOOCP)'s is introduced‎. ‎In this approach‎, ‎first a discretized form of the time-control space is considered and then‎, ‎a ...  Read More

Control and Optimization
The Control Parametrization Enhancing Technique for Multi-Objective Optimal Control of HIV Dynamic

Hassan Zarei

Volume 1, Issue 2 , October 2016, , Pages 1-21

Abstract
  In this paper‎, ‎a computational approach is adopted for solving a multi-objective optimal control problem (MOOCP) formulation of optimal drug scheduling in human immunodeficiency (HIV) virus infected by individuals‎. ‎The MOOCP‎, ‎which uses a mathematical model of HIV infection‎, ...  Read More

Control and Optimization
A Computational Method for Solving Optimal Control Problems and Their Applications

Zahra Rafiei; Behzad Kafash; Seyyed Mehdi Karbassi

Volume 2, Issue 1 , April 2017, , Pages 1-13

Abstract
  In order to obtain a solution to an optimal control problem‎, ‎a numerical technique based on state-control parameterization method is presented‎. ‎This method can be facilitated by the computation of performance index and state equation via approximating the control and state variable ...  Read More

Control and Optimization
Haar Matrix Equations for Solving Time-Variant Linear-Quadratic Optimal Control Problems

Saeed Nezhadhosein

Volume 2, Issue 2 , December 2017, , Pages 1-14

Abstract
  ‎In this paper‎, ‎Haar wavelets are performed for solving continuous time-variant linear-quadratic optimal control problems‎. ‎Firstly‎, ‎using necessary conditions for optimality‎, ‎the problem is changed into a two-boundary value problem (TBVP)‎. ‎Next‎, ...  Read More

Control and Optimization
A Numerical Solution of Fractional Optimal Control Problems Using Spectral Method and Hybrid Functions

seyed mehdy shafiof; Javad Askari; Maryam Shams Solary

Volume 3, Issue 1 , July 2018, , Pages 1-25

https://doi.org/10.30473/coam.2019.46969.1119

Abstract
  In this paper‎, ‎a modern method is presented to solve a class of fractional optimal control problems (FOCPs) indirectly‎. ‎First‎, ‎the necessary optimality conditions for the FOCP are obtained in the form of two fractional differential equations (FDEs)‎. ‎Then‎, ...  Read More

Quasi-Gap and Gap Functions for Non-Smooth Multi-Objective Semi-Infinite Optimization Problems

Atefeh Hassani Bafrani; Ali Sadeghieh

Volume 3, Issue 2 , January 2018, , Pages 1-12

https://doi.org/10.30473/coam.2020.50781.1133

Abstract
  In this paper‎, ‎we introduce and study some new single-valued gap functions for non-differentiable semi-infinite multiobjective optimization problems with locally Lipschitz data‎. ‎Since one of the fundamental properties of gap function for optimization problems is its abilities in characterizing ...  Read More

Apply Optimized Tensor Completion Method by Bayesian CP-Factorization for Image Recovery

Ali Reza Shojaeifard; Hamid Reza Yazdani; Mohsen Shahrezaee

Volume 6, Issue 1 , January 2021, , Pages 1-10

https://doi.org/10.30473/coam.2021.59727.1166

Abstract
  In this paper‎, ‎we are going to analyze big data (embedded in the digital images) with new methods of tensor completion (TC)‎. ‎The determination of tensor ranks and the type of decomposition are significant and essential matters‎. ‎For defeating these problems‎, ‎Bayesian ...  Read More

Chaotic Dynamics in a Fractional-Order Hopfield Neural Network and its Stabilization via an Adaptive Model-Free Control Method

Majid Roohi; Mohammad Pourmahmood Aghababa; Javid Ziaei; Chongqi Zhang

Volume 6, Issue 2 , July 2021, , Pages 1-21

https://doi.org/10.30473/coam.2022.59941.1169

Abstract
  The present study introduces a kind of fractional-order Hopfield neural network (FOHNN)‎, ‎and its complex dynamic behavior is investigated through chaos analyses‎. ‎With the use of phase space analysis and bifurcation diagrams and maximal Lyapunov exponent (MLE) it is demonstrated that ...  Read More

Integrated Fault Detection and Robust Control for Linear Uncertain Switched Systems with Mode-Dependent Time-Varying State Delay

Sayyed Hossein Ejtahed; Naser Pariz; Ali Karimpour

Volume 7, Issue 2 , December 2022, , Pages 1-34

https://doi.org/10.30473/coam.2022.62848.1192

Abstract
  Switched linear systems are noted as a major category of control systems‎. ‎Fault detection of these systems is affected by switching phenomena and therefore their integrated fault detection and robust control (IFDRC) are the central issues of recent studies‎. ‎Existing studies on IFDRC ...  Read More

Applying Robust Adaptive Lyapunov-Based Control for Hexa-Rotor

Mohammad Reza Zarrabi

Volume 7, Issue 1 , January 2022, , Pages 1-14

https://doi.org/10.30473/coam.2022.63671.1199

Abstract
  Drones are among the most valuable and versatile technologies in the world‎, ‎with applications in a vast number of ‎‎‎fields such as traffic control‎, ‎agriculture‎, ‎firefighting and‎ ‎rescue‎, ‎and filmmaking‎, ‎to name a few‎. ‎As ...  Read More

Solving a Class of Nonlinear Optimal Control Problems Using Haar Wavelets and Hybrid GA

Saeed Nezhadhosein‎; Reza Ghanbari; Khatere Ghorbani-Moghadam

Volume 8, Issue 1 , June 2023, , Pages 1-17

https://doi.org/10.30473/coam.2023.65549.1214

Abstract
  In this paper, we solve a class of nonlinear optimal control problems using a hybrid genetic algorithm (HGA) and a direct method based on the Haar wavelets where the performance index is Bolza-form and the dynamic system is linear‎. ‎First‎, ‎we change the problem by using HWs to a static ...  Read More

Graph Feature Selection for Anti-Cancer Plant Recommendation

Mahmood Amintoosi; Eisa Kohan-Baghkheirati

Volume 8, Issue 2 , December 2023, , Pages 1-15

https://doi.org/10.30473/coam.2023.67660.1231

Abstract
  Every year‎, ‎extensive experimental analysis is conducted to evaluate the anti-cancer properties of plants‎. ‎Developing a well-ranked list of potential anti-cancer plants based on verified anti-cancer metabolites can significantly reduce the time and cost required for plant evaluation‎. ...  Read More

A Decision Support System Framework Based on Text Mining and Decision Fusion Techniques to Classify Breast Cancer Patients

Mostafa Boroumandzadeh; Elham Parvinnia; Reza Boostani; Sepideh Sefidbakht

Volume 6, Issue 1 , January 2021, , Pages 11-29

https://doi.org/10.30473/coam.2021.60533.1175

Abstract
  Medical decision support systems (MDSS) are designed to assist physicians in making accurate decisions‎. ‎The required data by MDSS are collected from various resources such as physical examinations and electronic health records (EHR)‎. ‎In this paper‎, ‎an MDSS framework has ...  Read More

A General Scalar-Valued Gap Function for Nonsmooth Multiobjective Semi-Infinite Programming

Ahmad Rezayi

Volume 3, Issue 2 , January 2018, , Pages 13-26

https://doi.org/10.30473/coam.2019.45495.1110

Abstract
  For a nonsmooth multiobjective mathematical programming problem governed by infinitely many constraints‎, ‎we define a new gap function that generalizes the definitions of this concept in other articles‎. ‎Then‎, ‎we characterize the efficient‎, ‎weakly efficient‎, ...  Read More

Control and Optimization
A New Approach for Solving Grey Assignment Problems

Hadi Nasseri; Davood Darvishi Salokolaei; Allahbakhsh Yazdani

Volume 2, Issue 1 , April 2017, , Pages 15-28

Abstract
  Linear assignment problem is one of the most important practical models in the literature of linear programming problems‎. ‎Input data in the cost matrix of the linear assignment problem are not always crisp and sometimes in the practical situations is formulated by the grey systems theory approach‎. ...  Read More

Control and Optimization
Application of Grey System Theory in Rainfall Estimation

Davood Darvishi Salookolaei; Sifeng Liu; Parvin Babaei

Volume 2, Issue 2 , December 2017, , Pages 15-32

Abstract
  Considering the fact that Iran is situated in an arid and semi-arid region, rainfall prediction for the management of water resources is very important and necessary. Researchers have proposed various prediction methods that have been utilized in such areas as water and meteorology, especially water ...  Read More

Finding the Most Efficient DMU in DEA‎: A Model-Free Procedure

Zahra Noori; Hamed Zhiani Rezai; Alireza Davoodi; Sohrab Kordrostami

Volume 7, Issue 1 , January 2022, , Pages 15-29

https://doi.org/10.30473/coam.2022.62871.1193

Abstract
  Data envelopment analysis models are able to rank decision-making units (DMUs) based on their efficiency scores‎. ‎In spite of the fact that there exists a unique ranking of inefficient DMUs‎, ‎ranking efficient DMUs is problematic‎. ‎However‎, ‎rather than ranking methods‎, ...  Read More

Optimal Control of Infectious Diseases Using the Artificial Neural Networks

Rasoul Heydari Dastjerdi; Ghasem Ahmadi; Mahmood Dadkhah; Ayatollah Yari

Volume 8, Issue 2 , December 2023, , Pages 17-32

https://doi.org/10.30473/coam.2023.64776.1208

Abstract
  This paper presents a novel approach using artificial neural networks to solve the SEIR (Susceptible‎, ‎Exposed‎, ‎Infected‎, ‎and Recovered) model of infectious diseases based on dynamical systems‎. ‎Optimal control techniques are employed to determine a vaccination schedule ...  Read More

A Proximal Method of Stochastic Gradient for Convex Optimization

Zeinab Saeidian; Maryam Mahmoudoghli

Volume 8, Issue 1 , June 2023, , Pages 19-32

https://doi.org/10.30473/coam.2023.64060.1205

Abstract
  ‎The Proximal Stochastic Average Gradient (Prox-SAG+) is a primary method used for solving optimization problems that contain the sum of two convex functions. This kind of problem usually arises in machine learning, which utilizes a large amount of data to create component functions from a dataset. ...  Read More

Control and Optimization
Regularity Conditions for Non-Differentiable Infinite Programming Problems using Michel-Penot Subdifferential

Nader Kanzi

Volume 1, Issue 1 , April 2016, , Pages 21-30

Abstract
  In this paper we study optimization problems with infinite many inequality constraints on a Banach space where the objective function and the binding constraints are locally Lipschitz‎. ‎Necessary optimality conditions and regularity conditions are given‎. ‎Our approach are based on the ...  Read More

Control and Optimization
Numerical Solution of Optimal Heating of Temperature Field in Uncertain Environment Modelled by the use of Boundary Control

Ali Nehrani; Mohammad Keyanpour

Volume 1, Issue 2 , October 2016, , Pages 23-38

Abstract
  ‎In the present paper‎, ‎optimal heating of temperature field which is modelled as a boundary optimal control problem‎, ‎is investigated in the uncertain environments and then it is solved numerically‎. ‎In physical modelling‎, ‎a partial differential equation with ...  Read More

Guignard Qualifications and Stationary Conditions for Mathematical Programming with Nonsmooth Switching Constraints

Fatemeh Gorgini Shabankareh; Nader Kanzi; Javad Izadi; Kamal Fallahi

Volume 6, Issue 2 , July 2021, , Pages 23-35

https://doi.org/10.30473/coam.2021.60747.1176

Abstract
  In this paper‎, ‎some constraint qualifications ‎of‎ the Guignard type are defined for optimization problems with continuously differentiable objective functions and locally Lipschitz switching constraints‎. ‎Then‎, ‎a new type of stationary condition‎, ‎named ...  Read More

Control and Optimization
A New Hybrid Conjugate Gradient Method Based on Eigenvalue Analysis for Unconstrained Optimization Problems

Farzad Rahpeymaii; majid rostami

Volume 3, Issue 1 , July 2018, , Pages 27-43

https://doi.org/10.30473/coam.2019.44564.1108

Abstract
  In this paper‎, ‎two extended three-term conjugate gradient methods based on the Liu-Storey ({\tt LS})‎ ‎conjugate gradient method are presented to solve unconstrained optimization problems‎. ‎A remarkable property of the proposed methods is that the search direction always satisfies‎ ...  Read More

A New Optimization Method Based on Dynamic Neural Networks for Solving Non-convex Quadratic Constrained Optimization Problems

Kobra Mohammadsalahi; Farzin Modarres Khiyabani; Nima Azarmir Shotorbani

Volume 7, Issue 2 , December 2022, , Pages 35-52

https://doi.org/10.30473/coam.2022.64268.1206

Abstract
  This paper presents a capable recurrent neural network, the so-called µRNN for solving a class of non-convex quadratic programming problems‎. ‎Based on the optimality conditions we construct a new recurrent neural network (µRNN)‎, ‎which has a simple structure and its capability ...  Read More

MQ-Radial Basis Functions Center Nodes Selection with PROMETHEE Technique

Farhad Hadinejad; Saeed Kazem

Volume 3, Issue 2 , January 2018, , Pages 27-47

https://doi.org/10.30473/coam.2019.46609.1117

Abstract
  In this paper‎, ‎we decide to select the best center nodes‎ ‎of radial basis functions by applying the Multiple Criteria Decision‎ ‎Making (MCDM) techniques‎. ‎Two methods based on radial basis‎ ‎functions to approximate the solution of partial differential‎ ‎equation ...  Read More