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A Decision-Support Model for Managing Outbound Logistics: Forecasting, Simulation, and Real-Time Operational Control

Nicola Magaletti, Giancarlo Caponio, Angelo Amodio, Valeria Nortarnicola, Mauro Di Molfetta and Angelo Leogrande

No tnhz5_v1, SocArXiv from Center for Open Science

Abstract: This article presents a decision support system developed as part of a Research and Development project undertaken by La Logistica srl, a third-party logistics company specializing in the storage and distribution of hydro-sanitary products. The approach is methodological and focuses on the comprehensive analysis of a case study related to freight exit processes with the aim of defining and implementing a software application to support the short-term management of picking and loading operations for product delivery. The developed decision support system integrates past data series analysis and projections, time series simulations, What-If analysis capabilities, and real-time monitoring within a single computational paradigm to anticipate peak points in the freight exit process. The developed decision support system is designed to accumulate and structure operational data from the warehouse management system software, to analyse the periodic rhythms of orders received to generate graphical projections of expected peak points and working hours based on the analysis of past data series and is able to dynamically review projections via real-time monitoring capabilities to adapt projections to actual progress made at any given time. Additionally, What-If analytics capabilities facilitate management's use of various workforce combinations to determine the feasibility of the process at any time, while identifying potential bottlenecks before they occur. Test results conducted with the corporate team indicate improvements in workload visibility and readiness for associated short-term programming strategies, while preventing operational disruptions through advance alerts on operational overload points

Date: 2025-11-27
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Persistent link: https://EconPapers.repec.org/RePEc:osf:socarx:tnhz5_v1

DOI: 10.31219/osf.io/tnhz5_v1

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