AN INTELLIGENT DECISION SUPPORT SYSTEM FOR MULTIOBJECTIVE SUPPLY CHAIN MANAGEMENT OF AGROINDUSTRY
This paper presents the development of an intelligent decision support system for optimization of agroindustrial supply chain based on multi-objective genetic algorithms. Unlike in manufacturing industry, a supply chain optimization model of agroindustry often has two conflicting objectives such as cost and quality. Maintaining product quality during transportation and inventory is very important in agroindustry as agricultural products are perishable and bulky. For these reasons, this research aims to develop an optimization model for agroindustrial supply chain. This model consists of two conflicting objectives: i.e. minimization of TSCC (Total Supply Chain Cost) and minimization of ENDP (Expected Number of Deteriorated Product). A genetic algorithm (GA) is then developed to solve this model. The result indicated that the genetic algorithm developed in this work can be used to solve complex supply chain problems in agroindustry successfully. At the end of this paper, the implication of this research to bioplastics agroindustry is discussed.
multi-objective supply chain genetic algorithms agroindustry
Y.Yandra Hiroyuki Tamura
Department of Electrical Engineering and Computer Science, Faculty of Engineering, Kansai University, 3-3-35 Yamate-cho, Suita, Osaka 564-8680, JAPAN
国际会议
北京
英文
90-95
2005-10-14（万方平台首次上网日期，不代表论文的发表时间）