Modeling the bullwhip effect in supply chains using group problem solving approach

Supply chain management critically affects businesses' abilities to obtain and sustain competitive advantages. The bullwhip effect, however presents a challenge for successful supply chain management by amplifying demands in the supply chains. This paper presents a systematic approach to tackle the issue of bullwhip effect. Firstly, we define the supply chain under a multiagent framework. Secondly, a group problem solving paradigm, which is a rule learning approach, is proposed to enhance the decision making process within the multiagent supply chain framework. The genetic algorithm based on the group problem solving approach is then formlulated as a means to alleviate the bullwhip effect.