A decision support system to investigate food losses in e-grocery deliveries. (March 2018) - Fikar, Christian
Graphical abstract: Highlights: A decision support system to plan e-grocery distribution is introduced. It combines an agent-based simulation with optimization procedures. Food quality models are incorporated to estimate spoilage rates. Experiments investigate the impact of various delivery and picking strategies. Results highlight major trade-offs between food quality and travel distances. Abstract: Delays and inefficiencies in last-mile distribution of e-groceries result in high costs and further contribute to food waste. This work focuses on optimizing inventory and delivery strategies. While in traditional brick-and-mortar operations customers select products based on quality and expiration date, in e-groceries, primarily the provider performs this selection, impacting both food waste and customer satisfaction. Shipping goods close to expiration reduces spoilage, however, customers mainly prefer products with a long-lasting shelf life. To support sustainable provision of food, this work develops a decision support system incorporating an agent-based simulation and dynamic routing procedures to investigate e-grocery inventory and delivery operations. Food quality functions for 48 produces are incorporated to model food decay. Based on test scenarios motivated by an e-grocery provider operating in Vienna, Austria, managerial implications are provided and discussed. Results highlight major trade-offs between minimizing travel distances and food waste as well as the high importance of the selected inventory strategy. Furthermore, insights on the impact of the number of operated stores and individual store utilization are given.