Browsing by Author "Perotti, Sara"

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Citation - WoS: 6
Citation - Scopus: 4
Enhancing e-grocery order fulfillment: improving product availability- cost- and emissions in last-mile delivery
(SPRINGER, 2025) Banu Y. Ekren; Sara Perotti; Laura Foresti; Lorenzo Prataviera; Perotti, Sara; Foresti, Laura; Ekren, Banu Y.; Prataviera, Lorenzo
This paper studies e-grocery order fulfillment policies by leveraging both customer and e-grocery-based data. Through the utilization of historical purchase data product popularity trends and delivery patterns allocation strategies are informed to optimize performance metrics such as fill rate carbon emissions and cost per order. The study aims to conduct a sensitivity analysis to identify key drivers influencing these performance metrics. The results highlight that fulfillment policies optimized with the utilization of the mentioned data metrics demonstrate superior performance compared to policies not informed by data. These findings underscore the critical role of integrating data-driven models in e-grocery order fulfillment. Based on the outcomes a grocery allocation policy considering both proximity and product availability emerges as promising for simultaneous improvements in several performance metrics. The study recommends that e-grocery companies leverage customer data to design and optimize delivery-oriented policies and strategies. To ensure adaptability to new trends or changes in delivery patterns continual evaluation and improvement of e-grocery fulfillment policies are emphasized.
Leveraging Additive Manufacturing for Inventory Optimization: A Dual-Sourcing Niodel for Cost and Performance Enhancement in Retail Supply Chains
(Elsevier, 2025) Perotti, Sara; Ekren, Banu Yetkin; Finelli, Matteo
This study examines the integration of additive manufacturing (AM), specifically 3D printing (3DP), into retail supply chains to optimize inventory costs while maintaining high service levels (CSL >= 95%). A dual-sourcing inventory model is developed, balancing demand between traditional suppliers and in-house 3DP production. The model, solved using Microsoft Excel Solver, incorporates economic order quantity (EOQ), economic production quantity (EPQ), and reorder points to minimize total costs. Experimental results show that hybrid sourcing with 3DP reduces inventory costs, particularly at higher demand levels, while capacity constraints limit full adoption. Findings suggest that retailers should invest in AM expansion to maximize cost efficiency. This study provides a data-driven framework for hybrid inventory strategies and highlights future research directions in demand uncertainty, queueing effects, and advanced optimization techniques.
Citation - WoS: 9
Sustainable e-grocery home delivery: An optimization model considering on-demand vehicles
(PERGAMON-ELSEVIER SCIENCE LTD, 2025) Vittoria Tudisco; Sara Perotti; Banu Yetkin Ekren; Emel Aktas; Perotti, Sara; Tudisco, Vittoria; Aktas, Emel; Ekren, Banu Yetkin
The e-grocery sector has experienced a significant boost since the COVID-19 pandemic dramatically changing consumer buying behaviours. As demand for faster and more efficient delivery options grows e-grocery retailers face increasing pressure to optimize home delivery operations. Collaborations with third-party logistics providers (3PLs) although still overlooked have emerged as promising offering operational flexibility and environmental benefits. This work introduces an optimization model that supports the design of an on-demand delivery fleet conjunctly with delivery routings and schedules while considering both cost and environmental impact. To this aim a vehicle routing problem with time windows (VRPTW) is extended to incorporate on-demand fleet design and three different objective functions embodying a cost-efficient an environmentally-effective and a costenvironmental balanced perspective respectively. Numerical experiments based on an Italian case study show that prioritizing environmental objectives reduces emissions by over 90% with marginal increases in annual costs. Besides on-demand vehicles enable flexibility that facilitates the adoption of sustainable delivery options without requiring challenging investments such as delivery fleet. Several contributions are provided: insights into using on-demand vehicles are proposed, a mathematical model jointly optimizing fleet design and delivery routing and scheduling while considering both costs and environmental objectives is developed and its practical application is demonstrated using real-world data. The findings highlight the significant impact of environmental considerations on fleet composition and operational efficiency offering actionable strategies for e-retailers to reduce emissions while maintaining service quality.