Bulk food recall decisions: Postponement and preponement to sustain food business

Abstract

Without packaging, bulk food is prone to contamination which may lead to external quality failure that demands food recall. Companies need to employ effective recall decisions to prevent major loss and minimize the costs associated with recall. This study aims to determine the most effective disposition timing to reduce such recall costs and to ensure that business remains sustainable. Two disposition timing models that accommodate postponement and preponement decisions are developed: the former through Dynamic Linear Programming and the latter through Dynamic Mix Integer Linear Programming. These models aim to minimize recall costs by optimizing product allocation for each possible disposition alternative. The models were used in a real case scenario in the edible oil industry in Indonesia. The results show that recall costs in the preponement model are lower than in the postponement model when the transportation cost is high to recall back all the products to the factory. • Companies need to employ effective recall decisions to prevent major loss and minimize the costs associated with recall. • This study aims to determine the most effective disposition timing to reduce such recall costs and to ensure that business remains sustainable . • Two disposition timing models: postponement and preponement, are proposed to find the best decision on a trade recall.