Multi-objective non-linear programming problem in intuitionistic fuzzy environment: Optimistic and pessimistic view point

Rani, Deepika; Gulati, T. R.; Garg, Harish

doi:10.1016/j.eswa.2016.07.034

Cited by 73 publications

(29 citation statements)

References 29 publications

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“…In the future, the proposed algorithm can be extended to the different applications with the different datasets for various tasks [34][35][36]. Also, some multi-objective optimization problems may be solved in the future with the presented algorithm or its variants [37][38][39].…”

Section: Discussionmentioning

confidence: 99%

A Quick Gbest Guided Artificial Bee Colony Algorithm for Stock Market Prices Prediction

et al. 2018

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The objective of this work is to present a Quick Gbest Guided artificial bee colony (ABC) learning algorithm to train the feedforward neural network (QGGABC-FFNN) model for the prediction of the trends in the stock markets. As it is quite important to know that nowadays, stock market prediction of trends is a significant financial global issue. The scientists, finance administration, companies, and leadership of a given country struggle towards developing a strong financial position. Several technical, industrial, fundamental, scientific, and statistical tools have been proposed and used with varying results. Still, predicting an exact or near-to-exact trend of the Stock Market values behavior is an open problem. In this respect, in the present manuscript, we propose an algorithm based on ABC to minimize the error in the trend and actual values by using the hybrid technique based on neural network and artificial intelligence. The presented approach has been verified and tested to predict the accurate trend of Saudi Stock Market (SSM) values. The proposed QGGABC-ANN based on bio-inspired learning algorithm with its high degree of accuracy could be used as an investment advisor for the investors and traders in the future of SSM. The proposed approach is based mainly on SSM historical data covering a large span of time. From the simulation findings, the proposed QGGABC-FFNN outperformed compared with other typical computational algorithms for prediction of SSM values.

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Section: Discussionmentioning

confidence: 99%

A Quick Gbest Guided Artificial Bee Colony Algorithm for Stock Market Prices Prediction

et al. 2018

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“…To date, several approaches have been developed for the measurements of IFS, such as distance measurements (Szmidt & Kacprzyk, ; Yang & Chiclana, ), entropy measurements (Meng & Chen, ; Zhu & Li, ), and similarity measurements (Chen, Cheng, & Lan, ; Nguyen, ). Because of the applicability and simplicity, IFS has been developed by many researchers for solving different problems, including mathematical programming problems (Rani, Gulati, & Garg, ; Singh & Yadav, ), pattern recognition (Chen et al, ; Nguyen, ), and machine learning (Liu, Bi, & Fan, ; Nikdel, Forghani, & Moattar, ).…”

Section: Literature Reviewmentioning

confidence: 99%

A multiperiod hybrid decision support model for medical diagnosis and treatment based on similarities and three‐way decision theory

Yan

Liu

et al. 2019

Expert Systems

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Patients always want a precise diagnosis and appropriate treatment advice when they are diagnosed with a disease. Furthermore, the original information about certain features and symptoms appears in different forms, and the effect of time is always ignored in the process of diagnosis. To overcome these defects, this paper develops a systematic multiperiod hybrid decision support model, which combines the similarity measurement and three‐way decision theory to provide prediction and treatment advice for patients under the fuzzy environment. This multiperiod hybrid decision support model, which considers the effect of time, including transformation module, multiperiod integration module, similarity module, prediction module, and three‐way decision module, provides disease prediction and advice on treatment based on similarities and three‐way decision theory. To validate this model, we construct an illustration composed of four cases, and this ultimately shows that MPH‐SDM can effectively support patients' disease diagnoses and treatment.

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“…Among different approaches with which we can deal with uncertainty in optimization problems, Fuzzy Theory is the most popular method [53]. Depending on the specification of a given problem, different fuzzy approaches has been developed in literature [54][55][56][57][58].…”

Section: Solution Approachmentioning

confidence: 99%

A fuzzy solution approach for supplier selection and order allocation in green supply chain considering location-routing problem

2019

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In the field of supply chain, selecting a suitable green supplier could significantly help us to decrease the cost and the risk involved in the operations as well as increase in the quality and green. In this paper, we develop an integrated two-stage approach based on fuzzy analytic hierarchy process (FAHP) and multi-objective mixed-integer linear programming to select suppliers and order allocation in green supply chain. In the first stage, suppliers are evaluated using FAHP method, and in the second stage, a multi-product multi-period supply chain considering green location-routing problem, discounting, and time window under uncertainty is developed. Then, a fuzzy solution approach is applied to solve proposed model using the data of a pharmaceutical chain in Iran. Results will verify the efficiency of the proposed model. [38], Ware et al. [39], Chai et al. [40], Igarashi et al. [41], Govindan et al. [42], Zimmer et al. [43] and Keshavarz Ghorabaee et al. [44]. Studies in the field of supplier selection can be mainly divided into three categories: supplier evaluation and selection, order allocation and combination of both [3]. In this research, the papers on the Green Supplier Selection and Order allocation are reviewed. Mafakheri et al. [45] used the AHP to determine the criteria weights and obtain the suppliers' scores. They also used a bi-objective mathematical model and a solution approach based on dynamic programming for order allocation. The objective functions simultaneously minimize costs and maximizes the purchase value. Four main criteria of price, delivery, quality and environmental performance were defined for supplier evaluation. Shaw et al. [46] presented a combined approach based on FAHP and fuzzy MOLP for supplier selection and order allocation problem towards minimizing greenhouse gas emissions. They applied the model on garment manufacturing company in India as for model validation. Kannan et al. [13] developed an integrated approach based on FAHP, FTOPSIS and MOLP for supplier selection and order allocation in a green supply chain management. They measured the performance of each supplier based on the cost, quality, delivery, technology capability and environmental competency criteria, using the combination of FAHP and FTOPSIS methods. Then, the resulted scores were used as a factor in the objective function of maximizing purchases from the fitting suppliers. The other objective function was to minimize total cost of purchasing. Using three environmental criteria including environmental management system, pollution and greenhouse emissions, along with other criteria, Azadnia et al. [47] utilized the FAHP method to evaluate suppliers. They developed a multi-objective programming model for allocating orders to suppliers. Govindan and Sivakumar [14] proposed a MOLP model for simultaneously minimizing costs, minimizing defective product purchases, minimizing delays in products delivery, minimizing recycling losses, and minimizing carbon emissions. They used fuzzy TOPSIS method to calculate th...

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Multi-objective non-linear programming problem in intuitionistic fuzzy environment: Optimistic and pessimistic view point

Cited by 73 publications

References 29 publications

A Quick Gbest Guided Artificial Bee Colony Algorithm for Stock Market Prices Prediction

A Quick Gbest Guided Artificial Bee Colony Algorithm for Stock Market Prices Prediction

A multiperiod hybrid decision support model for medical diagnosis and treatment based on similarities and three‐way decision theory

A fuzzy solution approach for supplier selection and order allocation in green supply chain considering location-routing problem

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