MADM

Decision Making in Manufacturing Environment Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods presents the concepts and details of applications of MADM methods. A range of methods are covered including Analytic Hierarchy Process (AHP), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), VIšekriterijumsko KOmpromisno Rangiranje (VIKOR), Data Envelopment Analysis (DEA), Preference Ranking METHod for Enrichment Evaluations (PROMETHEE), ELimination Et Choix Traduisant la Realité (ELECTRE), COmplex PRoportional ASsessment (COPRAS), Grey Relational Analysis (GRA), UTility Additive (UTA), and Ordered Weighted Averaging (OWA). The existing MADM methods are improved upon and three novel multiple attribute decision making methods for solving the decision making problems of the manufacturing environment are proposed. The concept of integrated weights is introduced in the proposed subjective and objective integrated weights (SOIW) method and the weighted Euclidean distance based approach (WEDBA) to consider both the decision maker’s subjective preferences as well as the distribution of the attributes data of the decision matrix. These methods, which use fuzzy logic to convert the qualitative attributes into the quantitative attributes, are supported by various real-world application examples. Also, computer codes for AHP, TOPSIS, DEA, PROMETHEE, ELECTRE, COPRAS, and SOIW methods are included. This comprehensive coverage makes Decision Making in Manufacturing Environment Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods a key reference for the designers, manufacturing engineers, practitioners, managers, institutes involved in both design and manufacturing related projects. It is also an ideal study resource for applied research workers, academicians, and students in mechanical and industrial engineering.


References in zbMATH (referenced in 126 articles , 1 standard article )

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  1. Acuña-Soto, C.; Liern, V.; Pérez-Gladish, B.: Normalization in TOPSIS-based approaches with data of different nature: application to the ranking of mathematical videos (2021)
  2. Atef, Mohammed; Azzam, A. A.: Covering fuzzy rough sets via variable precision (2021)
  3. Atef, Mohammed; Nada, Shokry I.: On three types of soft fuzzy coverings based rough sets (2021)
  4. Dutta, Bapi; Dao, Son Duy; Martínez, Luis; Goh, Mark: An evolutionary strategic weight manipulation approach for multi-attribute decision making: TOPSIS method (2021)
  5. Ni, Lei; Chen, Yu-wang; de Brujin, Oscar: Towards understanding socially influenced vaccination decision making: an integrated model of multiple criteria belief modelling and social network analysis (2021)
  6. Mamat, Siti Salwana; Awang, Siti Rahmah; Ahmad, Tahir: Preference graph of potential method as a fuzzy graph (2020)
  7. Xian, Sidong; Yu, Dongxu; Sun, Yifei; Liu, Zhou: A novel outranking method for multiple criteria decision making with interval-valued Pythagorean fuzzy linguistic information (2020)
  8. Xiong, Lei; Zhong, Shuqi; Liu, Sen; Zhang, Xiao; Li, Yanfeng: An approach for resilient-green supplier selection based on WASPAS, BWM, and TOPSIS under intuitionistic fuzzy sets (2020)
  9. Zhang, An; Gao, Fei; Yang, Mi; Bi, Wenhao: A new rule reduction and training method for extended belief rule base based on DBSCAN algorithm (2020)
  10. Amin, Fazli; Fahmi, Aliya; Abdullah, Saleem: Dealer using a new trapezoidal cubic hesitant fuzzy TOPSIS method and application to group decision-making program (2019)
  11. Chan, Chi Kin; Zhou, Yan; Wong, Kar Hung: An equilibrium model of the supply chain network under multi-attribute behaviors analysis (2019)
  12. Chang, Leilei; Chen, Yuwang; Hao, Zhiyong; Zhou, Zhijie; Xu, Xiaobin; Tan, Xu: Indirect disjunctive belief rule base modeling using limited conjunctive rules: two possible means (2019)
  13. Gan, Jiawu; Zhong, Shuqi; Liu, Sen; Yang, Dan: Resilient supplier selection based on fuzzy BWM and GMo-RTOPSIS under supply chain environment (2019)
  14. Jia, Fan; Liu, Peide: A novel three-way decision model under multiple-criteria environment (2019)
  15. Moslemi, Shiva; Izadbakhsh, Hamidreza; Zarinbal, Marzieh: A new reliable performance evaluation model: IFB-IER-DEA (2019)
  16. Ploskas, Nikolaos; Papathanasiou, Jason: A decision support system for multiple criteria alternative ranking using TOPSIS and VIKOR in fuzzy and nonfuzzy environments (2019)
  17. Qi, Xiuli; Yu, Xiaohan; Wang, Lei; Liao, Xianglin; Zhang, Suojuan: PROMETHEE for prioritized criteria (2019)
  18. Carli, Raffaele; Dotoli, Mariagrazia; Pellegrino, Roberta: A decision-making tool for energy efficiency optimization of street lighting (2018)
  19. Goyal, Raman Kumar; Kaushal, Sakshi: Deriving crisp and consistent priorities for fuzzy AHP-based multicriteria systems using non-linear constrained optimization (2018)
  20. Joshi, Dheeraj Kumar; Beg, Ismat; Kumar, Sanjay: Hesitant probabilistic fuzzy linguistic sets with applications in multi-criteria group decision making problems (2018)

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