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.

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  1. 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)
  2. 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)
  3. Amin, Fazli; Fahmi, Aliya; Abdullah, Saleem: Dealer using a new trapezoidal cubic hesitant fuzzy TOPSIS method and application to group decision-making program (2019)
  4. Chan, Chi Kin; Zhou, Yan; Wong, Kar Hung: An equilibrium model of the supply chain network under multi-attribute behaviors analysis (2019)
  5. 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)
  6. Jia, Fan; Liu, Peide: A novel three-way decision model under multiple-criteria environment (2019)
  7. Moslemi, Shiva; Izadbakhsh, Hamidreza; Zarinbal, Marzieh: A new reliable performance evaluation model: IFB-IER-DEA (2019)
  8. Qi, Xiuli; Yu, Xiaohan; Wang, Lei; Liao, Xianglin; Zhang, Suojuan: PROMETHEE for prioritized criteria (2019)
  9. Carli, Raffaele; Dotoli, Mariagrazia; Pellegrino, Roberta: A decision-making tool for energy efficiency optimization of street lighting (2018)
  10. Goyal, Raman Kumar; Kaushal, Sakshi: Deriving crisp and consistent priorities for fuzzy AHP-based multicriteria systems using non-linear constrained optimization (2018)
  11. Joshi, Dheeraj Kumar; Beg, Ismat; Kumar, Sanjay: Hesitant probabilistic fuzzy linguistic sets with applications in multi-criteria group decision making problems (2018)
  12. Liern, V.; Pérez-Gladish, B.: Ranking corporate sustainability: a flexible multidimensional approach based on linguistic variables (2018)
  13. Mehlawat, Mukesh Kumar; Grover, Nishtha: Intuitionistic fuzzy multi-criteria group decision making with an application to critical path selection (2018)
  14. Russo Russo, Gabriele; Nardelli, Matteo; Cardellini, Valeria; Lo Presti, Francesco: Multi-level elasticity for wide-area data streaming systems: a reinforcement learning approach (2018)
  15. Bhattacharjee, Kalyan Shankar; Singh, Hemant Kumar; Ray, Tapabrata: An approach to generate comprehensive piecewise linear interpolation of Pareto outcomes to aid decision making (2017)
  16. Falke, Andreas; Hruschka, Harald: A Monte Carlo study of design-generating algorithms for the latent class mixed logit model (2017)
  17. Gitinavard, H.; Mousavi, S. M.; Vahdani, B.: Soft computing-based new interval-valued hesitant fuzzy multi-criteria group assessment method with last aggregation to industrial decision problems (2017)
  18. Guo, Wen-Tao; Huynh, Van-Nam; Sriboonchitta, Songsak: A proportional linguistic distribution based model for multiple attribute decision making under linguistic uncertainty (2017)
  19. Kuo, Ting: A modified TOPSIS with a different ranking index (2017)
  20. Mirzazadeh, Abolfazl; Moslemi, Shiva: Performance evaluation of four-stage blood supply chain with feedback variables using NDEA cross-efficiency and entropy measures under IER uncertainty (2017)

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