A belief-rule-based inventory control method under nonstationary and uncertain demand

作者：Li Bin; Wang Hong Wei^*; Yang Jian Bo; Guo Min; Qi Chao

来源：Expert Systems with Applications, 2011, 38(12): 14997-15008.

DOI：10.1016/j.eswa.2011.05.047

• Inventory
• Nonstationary demand
• Uncertainty
• Evidential reasoning
• Belief rule base

This paper is devoted to investigating inventory control problems under nonstationary and uncertain demand. A belief-rule-based inventory control (BRB-IC) method is developed, which can be applied in situations where demand and demand-forecast-error (DFE) do not follow certain stochastic distribution and forecasting demand is given in single-point or interval styles. The method can assist decision-making through a belief-rule structure that can be constructed, initialized and adjusted using both manager's knowledge and operational data. An extended optimal base stock (EOBS) policy is proved for initializing the belief-rule-base (BRB), and a BRB-IC inference approach with interval inputs is proposed. A numerical example and a case study are examined to demonstrate potential applications of the BRB-IC method. These studies show that the belief-rule-based expert system is flexible and valid for inventory control. The case study also shows that the BRB-IC method can compensate LIFE by training BRB using historical demand data for generating reliable ordering policy.

• 出版日期2011-12
• 单位华中科技大学