A New Insight on Order Quantity Allocation for Coordinated Multi-tier Multiple Supplier Networks Under Demand Uncertainty

Abstract

AbstractIn this paper, new insights on optimal order quality allocation decisions are provided based on the problem analysis of centralized, coordinated multi-tier multiple supplier's network, operating under uncertain demand environment. A mixed-integer nonlinear programming (MINLP) problem is formulated and solved, considering multiple conflicting objectives. The multiple objectives selected are supply network and environmental sustainability costs. Two-stage simulation-based designed experimentation (e.g., Taguchi and factorial design) is used to identify significant variables and their impact on multiple objectives. Analysis based on two different automobile component case data sets reveals that demand rate, unit item price, the standard deviation of demand, inventory holding rate, and carbon price are the significant variables that influence the multiple objectives. The factorial design of experiments confirms that demand rate and unit item price affect supply network cost. In contrast, the standard deviation of demand, inventory holding rate, and carbon pricing price influence the environmental sustainability cost. Based on the case study, the insights provided are expected to help practitioners design sourcing strategies for a centralized multi-tier multiple supplier's network.KeywordsDemand uncertaintyEnvironmental sustainabilityMulti-tier supply networkMixed-integer nonlinear programmingOrder quantity allocationSourcing strategy