首页 | 本学科首页   官方微博 | 高级检索  
     


Renewal reward processes with fuzzy rewards and their applications to T-age replacement policies
Affiliation:1. Graduate Program in Operations Research and Industrial Engineering, Department of Mechanical Engineering, The University of Texas at Austin, Austin, TX 78712, USA;2. Department of Information Management, National Chi Nan University, Puli, Nan-Tou 545, Taiwan;1. Department of Gastrointestinal Surgery, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, PR China;2. State Key Laboratory of Oncogenes and Related Genes, Shanghai Cancer Institute, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, PR China;1. Division of Cardiology, Department of Medicine, University of California Irvine Medical Center, Orange, CA 92868, USA;2. Department of Cardiology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China;3. Saha Cardiovascular Research Center, University of Kentucky, Lexington 40536-0509, USA;4. Department of Clinical Research and Development, National Cerebral and Cardiovascular Center, 5-7-1 Fujishirodai, Suita 5675-8565, Japan;5. Department of Pathophysiology, Key Laboratory of State Administration of Traditional Chinese Medicine of the People’s Republic of China, School of Medicine, Jinan University, Guangzhou 510632, China;1. School of Traffic and Transportation, Xuchang University, Xuchang, Henan, 461000, China;2. Department of Industrial Engineering, University of Houston, Texas, United States;3. Department of Electrical Engineering, Faculty of Technical Engineering, University of Mohaghegh Ardabili, Ardabil, Iran;4. University of Human Development, Iraq;5. Sulaimani Polytechnic University, Iraq;6. Department of Electrical Engineering, Budapest University of Technology and Economics, Budapest, Hungary
Abstract:The application of fuzzy set theory to renewal reward processes is proposed in this paper. The reward is modeled as a fuzzy random variable. A theorem which presents the long-run average fuzzy reward per unit time is stated. A procedure to obtain the best T-age replacement policy with fuzzy cost structure is developed. The original problem is transformed into a nonlinear program in order to evaluate the membership of the long-run average fuzzy cost per unit time.
Keywords:
本文献已被 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号