A new integer solution approach for fractional linear programming problem
Srikant
Gupta
Jaipuria Institute of Management, India
author
Ather
Raina
Department of Mathematics, Govt. Degree College Darhal, Jammu and Kashmir, India
author
text
article
2021
eng
In mathematical programming different types of cuts have been developed in the past to get an integer value of the decision variables. In this paper, we have developed a new integer cut for getting an integer solution of the fractional linear programming problem (FLPP). This technique allows the decision-maker to solve the formulated FLPP to be conveniently using the Branch and Bound approach in order to achieve the optimum final solution. The process of development of the integer cut is shown with sufficient detail and a numerical illustration is used for clarification purpose.
Annals of Optimization Theory and Practice
Firouzabad Institute of Higher Education
2588-3666
4
v.
2
no.
2021
1
12
http://aotp.fabad-ihe.ac.ir/article_133970_792b46078853b9b0c4a727a023112fc2.pdf
dx.doi.org/10.22121/aotp.2021.292397.1072
Application of the induced generalized averaging hybrid aggregation operators using interval-valued Pythagorean fuzzy environment
Khaista
Rahman
Shaheed Benazir Bhutto University, Pakistan
author
text
article
2021
eng
Induced aggregation operators are more suitable for aggregating the individual preference relations into a collective fuzzy preference relation. Therefore the focus of our this paper is to develop some induced generalized aggregation operators using interval-valued Pythagorean fuzzy numbers, such as induced generalized interval-valued Pythagorean fuzzy ordered weighted averaging (I-GIVPFOWA) operator, induced generalized interval-valued Pythagorean fuzzy hybrid averaging (I-GIVPFHA) operator. Some desirable properties, such as idempotency, boundedness, and monotonicity corresponding to the proposed operators have been investigated. The main advantage of the proposed operators is that these operators are able to reflect the complex attitudinal character of the decision-maker using order inducing variables and provide much more complete information for decision-making. Furthermore, these operators are applied to decision-making problems in which experts provide their preferences in the Pythagorean fuzzy environment to show the validity, practicality, and effectiveness of the new approach.
Annals of Optimization Theory and Practice
Firouzabad Institute of Higher Education
2588-3666
4
v.
2
no.
2021
13
29
http://aotp.fabad-ihe.ac.ir/article_134335_d740578f0d2ef6c15caf755d7950798e.pdf
dx.doi.org/10.22121/aotp.2021.286814.1067
Estimation of electrical energy consumption in Tamil Nadu using univariate time-series analysis
D.
Karthika
Department of Mathematics, School of Advanced Sciences and Technology, VIT, Vellore, Tamil Nadu, India
author
K.
Karthikeyan
Department of Mathematics, School of Advanced Sciences and Technology, VIT, Vellore, Tamil Nadu, India
author
text
article
2021
eng
Demand estimation for power utilization might be a key achievement factor for the occasion of any nation. This might be accomplished if the requirement is estimated precisely. In this paper, Distinctive Univariate methods of forecasting Autoregressive Integrated Moving Average (ARIMA), ETS, Holt's model, Holt Winter's Additive model, Simple exponential model was used to figure forecast models of the power consumption in Tamil Nadu. The goal is to look at the presentation of these five methodologies and the experimental information utilized in this investigation was data from previous years for the monthly power consumption in Tamil Nadu from 2012 to 2020. The outcomes show that the ARIMA model diminished the MAPE value to 5.9097%, while those of ETS, Holt's Model, Holt winter's technique, SES is 6.3451%, 9.7708%, 7.3439%, and 9.5305% separately. Depend on the outcomes, we conclude that the ARIMA approach beat the ETS and Holt winter's techniques in this situation.
Annals of Optimization Theory and Practice
Firouzabad Institute of Higher Education
2588-3666
4
v.
2
no.
2021
31
37
http://aotp.fabad-ihe.ac.ir/article_133971_77911a662000c8e24bfe83aef4831dcb.pdf
dx.doi.org/10.22121/aotp.2021.292718.1073
Fuzzy logic based controller for optimization of voltage unbalance compensation in an autonomous electric microgrid
Amir
Khaledian
Department of Electrical Engineering, Faculty of Electrical and Computer Engineering, Technical and Vocational University (TVU), Tehran, Iran
author
text
article
2021
eng
Recently, there has been an increasing utilization of distributed generators (DGs) in electric power systems not only to supply the demand power of the grid but also to enhance the power quality. In this paper, a new control scheme is proposed for optimization of voltage unbalance compensation in an autonomous microgrid. Adaptive fuzzy PI controller (AFPIC) is applied to a voltage compensation loop which modifies the droop control based inverter reference voltage. Virtual impedance loop is used to enhance the operation of droop control. Voltage unbalance factor (VUF) is calculated by positive and negative sequence components of the output voltage and compared with the maximum threshold. Second-order generalized integrator (SOGI) is used to extract the voltage positive and negative sequence. In the proposed method, microgrid has the dynamic potential of decreasing the VUF below the standard value in all kinds of load conditions while the conventional methods are designed only for a specific load operating point. Proper voltage regulation is also satisfied by back to back embedded voltage and current controllers. A sample microgrid is analyzed in presence of single phase unbalanced load and Matlab simulation results are given to show the effectiveness of the proposed controller.
Annals of Optimization Theory and Practice
Firouzabad Institute of Higher Education
2588-3666
4
v.
2
no.
2021
39
54
http://aotp.fabad-ihe.ac.ir/article_132845_c1f2075ebea74a087ca1c953b9a8ce00.pdf
dx.doi.org/10.22121/aotp.2021.286982.1068
Machine learning approaches to mental stress detection: a review
Vishakha
Arya
Department of Computer Science, School of Computing, DIT University, Dehradun, 248001 India
author
Amit
Mishra
Department of Computer Science, School of Computing, DIT University, Dehradun, 248001 India
author
text
article
2021
eng
Purpose of Review: Machine Learning has shown exponential growth in ingesting a huge amount of data and give accurate outcomes equivalent to the human level. It provides a glance at the future where complex data, analysis and analytical model together help innumerable people suffering from health issues. This paper reviews the current application of ML in the health sector, their limitation, predictive analysis, and areas that are hard-to-diagnose and need advance research.New Findings: We have reviewed 30 papers on mental stress detection using ML that used Social networking sites, student’s record, Questioner technique, clinical dataset, real-time data, Bio-signal technology, wireless device and suicidal tendency. Collectively, these studies show high accuracy and potential of ML algorithms in mental health, and which ML algorithm yields the best result. Summary: With the advancement of ML, it has unfolded many areas like traditional clinical trials which are not sufficient to collect all the information about a person. Currently, define under DSM-V stage to detect these illnesses at the preliminary stage, diagnosing and treating before any mishap. It has re-defined the mental health practicing reducing cost and time, making it easier and convenient for patients to reach better health care whenever they need it.
Annals of Optimization Theory and Practice
Firouzabad Institute of Higher Education
2588-3666
4
v.
2
no.
2021
55
67
http://aotp.fabad-ihe.ac.ir/article_133972_e76e2b3325f15997830e07bee5314cb5.pdf
dx.doi.org/10.22121/aotp.2021.292083.1074
On discounted discrete scheduled replacement model
Tijjani A
Waziri
School of Continuing Education, Bayero University Kano, Nigeria
author
text
article
2021
eng
An operating unit sometimes cannot be replaced at the exact optimum replacement time for some reasons. The unit may be rather replaced at idle times, such as a day, a week, a month, a year and so on. So to address such problem of replacing a unit at idle times, this paper come up with a discounted discrete scheduled replacement model for a unit. It is assumed that the replacement is at scheduled times NT(N=1,2,3,…) for a fixed T>0, such that the model constructed involves minimal repair and discounting rate (∝ >0). The unit considered in this paper is subjected to three categories of failures, which are Category I, Category II and Category III failures. Category I failure is an un-repairable one, which occurs suddenly. While Category II and Category III failures are both repairable, which occurs due to time and usage, and the two failures are minimally repaired. A numerical example is provided, so as to investigate the characteristics of the model presented and determine the optimal discrete replacement time (N^*) of the unit.
Annals of Optimization Theory and Practice
Firouzabad Institute of Higher Education
2588-3666
4
v.
2
no.
2021
69
82
http://aotp.fabad-ihe.ac.ir/article_133605_e5d0423ea94c196c8d26e8d72aad1730.pdf
dx.doi.org/10.22121/aotp.2021.283204.1065