تصميم گیری چند معیاره تركيبي پویا با روش ویكور فازی نوع دوم برای تصمیم گیری در صنعت تولید كاغذ
محورهای موضوعی : مدیریت صنعتیمیثم جعفری اسکندری 1 * , رامین صادقیان 2 , فتانه یاراحمدی 3 , مصطفی یوسفی طزرجان 4
1 - دانشگاه پیام نور تهران
2 - دانشگاه پیام نور
3 - دانشگاه پیام نور
4 - دانشگاه جامع علمیکاربردی
کلید واژه: تصمیم گیری چند معیاره صنعت کاغذ روش ویکور فازی فازی نوع 2 تصمیم گیرنده.,
چکیده مقاله :
صنعت کاغذ گردش مالی زیادی دارد و تصمیم گیری مناسب برای توسعه آن سودآوری بالایی را بوجود خواهد آورد. در این تحقیق تمرکز بر صنعت کاغذ و ارائه دهندگان این خدمت می باشد و به دنبال اولویت بندی تصمیمات بر اساس ادغام مدل فازی نوع دوم و تصمیم گیری چند شاخصه ی ترکیبی پویا به روش ویکور در صنعت کاغذ هستیم. در این راستا، نخست 5 تصمیم مهم توسط خبرگان صنعت کاغذ شناسایی شده است که شامل 1-تلاش برای ورود تکنولوژی و ماشین آلات جدید، 2-سرمایه گذاری روی محصولات جدید و تنوع بخشی به محصولات ،3- آموزش کارکنان و مدیران ،4- برنامه ریزی فنی تولید، انبارش و مدیریت کارکنان و 5- قیمت گذاری مناسب و تبلیغات برای جذب مشتریان داخلی و خارجی جدید می باشد. همچنین 6 معیار برای ارزیابی این تصمیمات ارائه شده است. در راستای ارزیابی تصمیمات از رویکرد ویکور فازی نوع دوم استفاده شده و پس از طی گام های تحقیق، تصمیمات 1 و 2 حائز بالاترین اولویت شدند.
Paper manufacturing industry is one of the prominent and impactful industries in countries and societies. Leak of knowledge, awareness, information and etc. is affiliate to the existence of paper and without it, there is no chance of saving and recording the information. Each year a significant amount of paper is being produced and consumed in the world and the turnover of this industry is significant. In this research the focus is on paper industry and the providers of this service and we are seeking to prioritize the decisions based on merging of fuzzy model of second type with decision making of several complex dynamic indexes. With VIKOR in paper industry. First of all, 5 important decisions have been identified by the expertise in paper industry that includes 1) An attempt to include technology and new machines 2)Investigating on new products and diversification of products 3) Educating employees and managers 4) Organizing technical production, storage and managing the employers 5) Suitable pricing and advertising to attract new inside and outside consumers Also 6 criterions have been proposed to evaluate these decisions For evaluating the decisions, we have used the fuzzy VIKOR approach of type 2 and after going through research stages, decision number 1 and 2 gained the most priority.
1- امیری ،مقصود ،تصمیم گیری گروهی برای انتخاب ابزار ماشین با استفاده از روش ویکور فازی ،فصلنامه علمی و پژوهشی مطالعات مدیریت صنعتی ،سال ششم ،شماره ی16 ،تابستان 167،1386-188
2- توکلی، حسین و فیاض، محمد و حسن نژاد، مریم، بررسی عملکرد طرح های مرتع داری استان خراسان رضوی با رویکرد دلفی فازی و مدل های تصمیم گیری چند معیاره، نشریه ی اقتصاد و توسعه ی کشاورزی، شماره ی 1، بهار 1392، 50-37.
3- Triantaphyllou, Evangelos (2000). Multi-criteria decision making methods: a comparative study. Applied optimization. Dordrecht, Netherlands: Kluwer Academic Publishers. p. 320. doi:10.1007/978-1-4757-3157-6. ISBN 0792366077.
4- Frensch, Peter A.; Funke, Joachim, eds. (1995). Complex problem solving: the European perspective. Hillsdale, NJ: Lawrence Erlbaum Associates. ISBN 0805813365. OCLC 32131412.
5- Monahan, George E. (2000). Management decision making: spreadsheet modeling, analysis, and application. Cambridge, UK; New York: Cambridge University Press. pp. 33–40. ISBN 0521781183. OCLC 42921287.
6- G. Wei, "Grey relational analysis model for dynamic hybrid multiple attribute decision making," Knowledge Based Systems, vol. 24, pp. 672-679, 7// 2011.
7- Shu-ping Wan, Power average operators of trapezoidal intuitionistic fuzzy numbers and application to multi attribute group decision making Applied Mathematical Modelling, 37 (2013) 4112–4126.
8- Huu-Tho Nguyen, A hybrid approach for fuzzy multi-attribute decision making in machine tool selection with consideration of the interactions of attributes Expert Systems with Applications 41 (2014) 3078–3.
9- Satar Mahdevari a,*, Kourosh Shahriar a, Akbar Esfahani pour b, "Human health and safety risks management in underground coal minesusing fuzzy TOPSIS ," Science of the Total Environment 488–489 (2014) 85–99.
10- Yusuf Tansel _Ic, "A TOPSIS based design of experiment approach to assesscompany ranking. Applied Mathematics and Computation 227 (2014) 630– 647 .
11- Basar Oztaysi, "A decision model for information technology selection using AHP integrated TOPSIS-Grey: The case of content management systems," Knowledge-Based Systems 70 (2014) 44–54.
12- Ming Li a,*, Lei Jin a, Jun Wangb, "journal homepage: www.elsevier.com/locate/asoc A new MCDM method combining QFD with TOPSIS for knowledge management system selection from the user’s perspective in intuitionistic fuzzy environment," Applied Soft Computing 21 (2014) 28–37.
13- Francisco Rodrigues Lima Juniora, Lauro Osirob, Luiz Cesar Ribeiro Carpinettia, A comparison between Fuzzy AHP and Fuzzy TOPSIS methods to supplier selection," Applied Soft Computing 21 (2014) 194–209.
14- Junyi Chai a,*, Eric W.T. Ngai a, James N.K. Liu b. Dynamic tolerant skyline operation for decision making. Expert Systems with Applications 41 (2014) 6890–6903.
15- Feng Zhang a,b, Joshua Ignatius a,*, Chee Peng Lim c, Mark Goh d ,e , A two-stage dynamic group decision making method for processing ordinal information Knowledge-Based Systems 70 (2014) 189–202.
16- Ahmad M .El - Nagar ∗, Mohammad E l - Bardini, Hard ware-in-the-loop simulation of interval type - 2 fuzzy PD controller for uncertain nonlinear system using low cost micro controller. Knowledge-Based Systems 70 (2014) 189–202.
17- Jian Han, Huaguang Zhang n, Ying chun Wang, Yang Liu, Disturbance observer based fault estimation and dynamic output feedback fault tolerant control for fuzzy systems with local nonlinear models. ISA Transactions. Science Direct Accepted 28 August 2015.
18- Changman Son*, Intelligent rule -based sequence planning algorithm with fuzzy optimaization for robot manipulation tasks in partially dynamic enviroments. Information Sciences 000 (2015) 1–13.
19- Mohammad Farhan Khana,*, Xueshi Rena, Ekram Khanb, Semi dynamic fuzzy histogram equalization. Optik 126 (2015) 2848–2853.
20- David stefka a,Martin Hole na , Dynamic classifier aggregation using interaction - sensitive fuzzy measures Fuzzy Sets and Systems 270 (2015) 25–52.
21- Tzu - Liang (Bill) Tsenga , Fuhua Jiangb ,Yongjin (James) Kwonc , n ,Hybrid Type II fuzzy system & data mining approach for surface finish Journal of Computational Design and Engineering 2 (2015) 137–147.
22- N.J. Vinoth Kumar*, M. Mohamed Thameem Ansari 1 , A new design of dual-mode Type-II fuzzy logic load frequency controller for interconnected power systems with parallel ACeDC tie-lines and superconducting magnetic energy storage unit .Energy 89 (2015) 118e137.
23- Bojun Liu, Yushun Fan*, Yi Liu, A fast estimation of distribution algorithm for dynamic fuzzy flexible job-shop scheduling problem. Computers & Industrial Engineering 87 (2015) 193–201.
24- Hari Mohan Dubey a, Manjaree Pandit a, *, B.K. Panigrahi b, Hybrid flower pollination algorithm with timevarying fuzzy selection mechanism for wind integrated multi-objective dynamic economic dispatch Renewable Energy 83 (2015) 188e202.
25- Hari Mohan Dubey a, Manjaree Pandit a, *, B.K. Panigrahi b Esther Rodrígueza, Roberto Pechea, Carlos Garbisub, I˜naki Gorostizac, Lur Epeldeb, Unai Artetxed, Amaia Irizare, Manuel Sotoe, José Ma Becerrild, Javier Etxebarriac. Dynamic Quality Index for agricultural soils based on fuzzy logic. Ecological Indicators 60 (2016) 678–692.