A STUDY ON DECISION-MAKING OF FOOD SUPPLY CHAIN BASED ON BIG DATA  

作　　者：Guojun Ji Limei Hu Kim Hua Tan 

机构地区：[1]Collaborative Innovation Center for Peaceful Development of Corss-Strait Relations School of Management, Xiamen University, Xiamen, Fujian,361005, China [2]Operations Management & Information Systems Division, Nottingham University Business School

出　　处：《Journal of Systems Science and Systems Engineering》2017年第2期183-198,共16页系统科学与系统工程学报（英文版）

摘　　要：As more and more companies have captured and analyzed huge volumes of data to improve the performance of supply chain, this paper develops a big data harvest model that uses big data as inputs to make more informed production decisions in the food supply chain. By introducing a method of Bayesian network, this paper integrates sample data and finds a cause-and-effect between data to predict market demand. Then the deduction graph model that translates products demand into processes and divides processes into tasks and assets is presented, and an example of how big data in the food supply chain can be combined with Bayesian network and deduction graph model to guide production decision. Our conclusions indicate that the analytical framework has vast potential for supporting support decision making by extracting value t^om big data.As more and more companies have captured and analyzed huge volumes of data to improve the performance of supply chain, this paper develops a big data harvest model that uses big data as inputs to make more informed production decisions in the food supply chain. By introducing a method of Bayesian network, this paper integrates sample data and finds a cause-and-effect between data to predict market demand. Then the deduction graph model that translates products demand into processes and divides processes into tasks and assets is presented, and an example of how big data in the food supply chain can be combined with Bayesian network and deduction graph model to guide production decision. Our conclusions indicate that the analytical framework has vast potential for supporting support decision making by extracting value t^om big data.

关 键 词：Big data Bayesian network deduction graph model food supply chain 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] X384[自动化与计算机技术—控制科学与工程]