Dergiler / Hacettepe Journal of Mathematics and Statistics / 2019 / Cilt: 48 - Sayı: 3

A New Defuzzification Method for Solving FuzzyMathematical Programming Problems

Sayfa
845–858
Yayın Tarihi
2022-10-18
DOI
—
🏛️Bu makalenin bibliyografik verileri ve tam metin bağlantısı DergiPark üzerinden sağlanmıştır.
DergiPark Kaydı ↗
✨

Yapay Zeka Hızlı Bakış & Çıkarımlar

AI Insight
⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

The proposed method generates improved solutions inless time and requires less monitoring during the problem-solving proce-dure.

📌 3 Maddede Bu Makale

🎯
Amaç & Hipotez:Solving a certain type of Fuzzy mathematical programming (FMP)require several steps and manual intervention in the solution process.Therefore, it reduces the optimality and increases the solving time.
📊
Temel Bulgular & Veri:Inthis research, a methodology is pre-sented that, in addition to beingapplicable to all types of FMPs, increases optimali-ty and reduces thesolving time.
💡
Sonuç & Katkı:The proposed method generates improved solutions inless time and requires less monitoring during the problem-solving proce-dure.
🔬Tür:Araştırma Makalesi
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Alan Parametreleri

Abstract

Solving a certain type of Fuzzy mathematical programming (FMP)require several steps and manual intervention in the solution process.Therefore, it reduces the optimality and increases the solving time. Inthis research, a methodology is pre-sented that, in addition to beingapplicable to all types of FMPs, increases optimali-ty and reduces thesolving time. The proposed method generates improved solutions inless time and requires less monitoring during the problem-solving proce-dure.

🔖

Bu Makaleye Atıf Yap

VAHİDİ, A. (2022). A New Defuzzification Method for Solving FuzzyMathematical Programming Problems. Hacettepe Journal of Mathematics and Statistics, Cilt: 48 - Sayı: 3, 845–858. https://ajindex.com/articles/529747

📄 Tam Metin PDF Okuyucu

📄

PDF görüntüleyici hazırlanıyor...

Kaynakça (1)

  1. Attari H. and Nasseri S. H., New Concepts of Feasibility and Efficiency of Solutions inFuzzy Mathematical Programming Problems, Fuzzy Inf. Eng., vol. 6, no. 2, pp. 203221,Jun. 2014. [2]Azadeh A., Moghaddam M.,Khakzad M., and Ebrahimipour V., A flexible neural network-fuzzy mathematical programming algorithm for improvement of oil price es-timation andforecasting, Comput. Ind. Eng., vol. 62, no. 2, pp. 421430, 2012. [3]Azadeh A., Saberi M., Asadzadeh S. M., and Khakestani M., A hybrid fuzzy mathe-maticalprogramming-design of experiment framework for improvement of energy consumption es-timation with small data sets and uncertainty: The cases of USA, Can-ada, Singapore,Pakistan and Iran, Energy, vol. 36, no. 12, pp. 69816992, 2011. [4]Bector C. R. and Chandra S., Fuzzy Mathematical Programming and Fuzzy Matrix Games.Springer, 2005. [5]Bellman R. and Zadeh L. A., Decision Making in a Fuzzy Environment, Manage. Sci., vol.17, pp. 141164, 1970. [6]BilgenB., Application of fuzzy mathematical programming approach to the produc-tionallocation and distribution supply chain network problem, Expert Syst. Appl., vol. 37, no.6, pp. 44884495, 2010. [7]Biswas A., and Modak N., A Multiobjective Fuzzy Chance Constrained Programming Modelfor Land Allocation in Agricultural Sector: A case study, vol. 10. 2017. [8]Carlsson C., and Korhonen P., A Parametric Approach to Fuzzy Linear Programming, FuzzySets Syst., vol. 20, no. 1, pp. 1730, 1986.[9]Chanas S., The Use of Parametric Programming in Fuzzy Linear Programming, Fuzzy SetsSyst., vol. 11, no. 13, pp. 229241, 1983. [10]Cheng C. B,. and Cheng C. J., Available-to-promise based bidding decision by fuzzy mathe-matical programming and genetic algorithm, Comput. Ind. Eng., vol. 61, no. 4, pp. 9931002,2011. [11]Ebrahimnejad A., Tavana M., Lotfi F. H., Shahverdi R., and Yousefpour M., A three-stageData Envelopment Analysis model with application to banking industry, Meas-urement, vol.49, pp. 308319, 2014. [12]Effati S., Pakdaman M., and Ranjbar M., A new fuzzy neural network model for solv-ingfuzzy linear programming problems and its applications, Neural Comput. Appl., vol. 20, no.8, pp. 12851294, 2011. [13]Ezzati R., Khorram E., and Enayati R., A new algorithm to solve fully fuzzy linear pro-gramming problems using the MOLP problem, Appl. Math. Model., Mar. 2013. [14]Farhadinia B., Sensitivity analysis in interval-valued trapezoidal fuzzy number linear pro-gramming problems, Appl. Math. Model., vol. 38, no. 1, pp. 5062, Jan.