![Sample our Computer Science journals, sign in here to start your access, latest two full volumes FREE to you for 14 days]({"type":"image" , "src" : "/sda/5928/TOC-Subject-Sample-2021-Computer-Science.jpg"})
Abstract
In supply chain management, satisfying customer demand is the most concerned for the manager. However, the goods may rot or be spoilt during delivery owing to natural disasters, inclement weather, traffic accidents, collisions, and so on, such that the intact goods may not meet market demand. This paper concentrates on a stochastic-flow distribution network (SFDN), in which a node denotes a supplier, a transfer station, or a market, while a route denotes a carrier providing the delivery service for a pair of nodes. The available capacity of the carrier is stochastic because the capacity may be partially reserved by other customers. The addressed problem is to evaluate the system reliability, the probability that the SFDN can satisfy the market demand with the spoilage rate under the budget constraint from multiple suppliers to the customer. An algorithm is developed in terms of minimal paths to evaluate the system reliability along with a numerical example to illustrate the solution procedure. A practical case of fruit distribution is presented accordingly to emphasise the management implication of the system reliability.
Additional information
Funding
Notes on contributors
Yi-Kuei Lin
Yi-Kuei Lin is currently a Chair Professor and the Head of Industrial Management Department, National Taiwan University of Science and Technology, Taiwan, Republic of China. He received a Bachelor degree in Applied Mathematics from National Chiao Tung University, Taiwan. He obtained his master degree and PhD degree in Industrial Engineering and Engineering Management from National Tsing Hua University, Taiwan, Republic of China. He has the honour to get the Distinguished Research Awards from National Science Council of Taiwan in 2008, 2010, and 2013. His research interest includes performance evaluation, stochastic network reliability, operations research, and telecommunication management. He has published over 160 papers in refereed journals including European Journal of Operational Research, Computers and Operations Research, Reliability Engineering & System Safety, IEEE Transactions on Reliability, IEEE Transactions on Systems, Man, and Cybernetics–Part A: Systems and Humans, International Journal of Industrial Engineering, Computers and Mathematics with Applications, International Journal of Advanced Manufacturing Technology, International Journal of Reliability, Quality and Safety Engineering, Journal of the Operations Research Society of Japan, Mathematical and Computer Modelling, Computers and Industrial Engineering, International Journal of Production Economics, and Applied Mathematics and Computation.
Cheng-Fu Huang
Cheng-Fu Huang is currently a Postdoctoral Fellow in Industrial Management Department, National Taiwan University of Science and Technology, Taiwan, Republic of China. He received his bachelor degree in Industrial Engineering from Feng Chia University, Taiwan, in 2004; master degree in Industrial Engineering and Management from National Chin-Yi University of Technology, Taiwan, in 2006; and the PhD degree in Industrial Management from National Taiwan University of Science and Technology, Taiwan, in 2010. His research interest includes stochastic network reliability, performance evaluation, and quality management.
Cheng-Ta Yeh
Cheng-Ta Yeh is an Assistant Professor in Department of Business Administration from Shih Hsin University, Taipei, Taiwan. He received the bachelor degree in Information Management from Shih Hsih University in 2004, the master degree inCommerce Automation and Management from National Taipei University of Technology, Taiwan, in 2006, and the PhD degree in Industrial Management from National Taiwan University of Science and Technology (NTUST), Taiwan, in 2010. From August 2012 to January 2014, he was a postdoc in the Department of Industrial Management, NTUST. His research interests are in supply chain management, system optimisation, and decision analysis.