Modeling an Inventory Routing Problem for perishable products with environmental considerations and demand uncertainty

• Published in: International journal of production economics 2015-06, Vol.164, p.118-133
• Main Authors: Soysal, Mehmet, Bloemhof-Ruwaard, Jacqueline M., Haijema, Rene, van der Vorst, Jack G.A.J.
• Format: Article
• Language: English
• Subjects: Chance-constrained programming; Cost control; Cost reduction; Distribution costs; Energy consumption; Environmental impact; Food; Greenhouse gas emissions; Inventory management; Inventory routing; Perishability; Perishable goods; Studies; Supply chain management; Supply chains; Transportation problem (Operations research)
• ISSN: 0925-5273; 1873-7579
• DOI: 10.1016/j.ijpe.2015.03.008

The transition to sustainable food supply chain management has brought new key logistical aims such as reducing food waste and environmental impacts of operations in the supply chain besides the traditional cost minimization objective. Traditional assumptions of constant distribution costs between nodes, unlimited product shelf life and deterministic demand used in the Inventory Routing Problem (IRP) literature restrict the usage of the proposed models in current food logistics systems. From this point of view, our interest in this study is to enhance the traditional models for the IRP to make them more useful for the decision makers in food logistics management. Therefore, we present a multi-period IRP model that includes truck load dependent (and thus route dependent) distribution costs for a comprehensive evaluation of CO2 emission and fuel consumption, perishability, and a service level constraint for meeting uncertain demand. A case study on the fresh tomato distribution operations of a supermarket chain shows the applicability of the model to a real-life problem. Several variations of the model, each differing with respect to the considered aspects, are employed to present the benefits of including perishability and explicit fuel consumption concerns in the model. The results suggest that the proposed integrated model can achieve significant savings in total cost while satisfying the service level requirements and thus offers better support to decision makers. •A chance-constrained model for the Inventory Routing Problem is presented.•Model accounts for perishability, explicit fuel consumption and demand uncertainty.•Model can be used to aid food logistics decision-making process in VMI systems.•Results suggest that the model can achieve significant savings in total cost.•A case study on tomato distribution operations of a supermarket shows model applicability.