6533b86cfe1ef96bd12c8c31

RESEARCH PRODUCT

Reducing waste and ecological impacts through a sustainable and efficient management of perishable food based on the Monte Carlo simulation

Rosa MicalePierluigi TomaGiada La ScaliaPier Paolo Miglietta

subject

0106 biological sciencesTraceabilityComputer scienceSupply chainGeneral Decision SciencesContext (language use)010501 environmental sciences010603 evolutionary biology01 natural sciencesWarehouse managementSupply and demandSettore ING-IND/17 - Impianti Industriali MeccaniciMonte Carlo simulationEcology Evolution Behavior and Systematics0105 earth and related environmental sciencesEcologyEcological impacts Food waste reduction Monte Carlo simulation Shelf life model Sustainability Warehouse managementEnvironmental economicsEcological impactWarehouseProduct (business)SustainabilitySustainabilityShelf life modelCarbon footprintEcological impacts; Food waste reduction; Monte Carlo simulation; Shelf life model; Sustainability; Warehouse managementFood waste reduction

description

Abstract In today’s competitive global market it is mandatory to improve warehousing operations integrating economic, environmental and social aspects. The recent advancement in monitoring technologies can greatly improve the performance of the food supply chain reducing product loss. In particular, in the perishable food supply chain, initially inventory operations are critical because they manage the material flows in very variable conditions. The deterioration level of the products as well as the market demand are the main factors that can influence warehouse strategy. This research aims to consider the application of sustainability principles in the context of warehouse storage, evaluating the combined decision of implementing shelf life based picking policy and pricing strategy. In particular, the proposed approach is based on a referenced shelf life model and on the Monte Carlo simulation. Three different pricing scenarios in a case study for the management of the warehouse were defined and their Economic Traceability Lot was determined on the basis of an economic feasibility analysis. Finally, the carbon footprint for each scenario was determined in terms of emissions produced by temperature-controlled transportations and for the landfilling of product wasted.

https://doi.org/10.1016/j.ecolind.2018.10.041