IMP Research Group

JOURNAL PAPER - PUBLISHED
Esamina gli articoli che il gruppo ha scritto sulle principali riviste di settore su tematiche come supply chain risk management, digital twins, inventory control, mass customization, data model, order picking e quality control

COCOA: a model-agnostic framework for forecasting accessories demand
from final product sales
(2026)

Gabellini M., Regattieri A.,

Approfondisci

A novel data-driven approach for integrated inventory replenishment, safety stock and lead time optimization
(2026)

Gabellini M., Regattieri A.,
Marco B., Ronchi M.

Approfondisci

An information-sharing and cost-aware custom loss machine learning framework for 3PL supply chain forecasting
(2025)

Gabellini, M., Calabrese, F., Galizia, F. G., Ronchi, M., Regattieri, A.

Approfondisci

Conceptualization and validation of an intelligent digital twin design framework for supply chain risk management
(2025)

Gabellini, M., Regattieri, A., Bortolini, M., & Ronchi, M.

Approfondisci

A continuous training approach for
risk informed supplier selection and
order allocation
(2025)

M Gabellini, S Mak, S Schoepf, A Brintrup, A Regattieri

Approfondisci

Data Spaces in Manufacturing and Supply Chains: A Review and Insights from European Initiatives (2025)

M Gabellini, L Civolani, M Ronchi, LD Naldi, A Regattieri

Approfondisci

Unlocking the Potential of Mass Customization Through Industry 4.0: Mapping Research Streams and Future Directions (2025)

LD Naldi, FG Galizia, M Bortolini, M Gabellini, E Ferrari

Approfondisci

An MILP Model for Optimizing Quality Inspection Allocation with Technology Selection and Variable Sampling Rates (2025)

M Ronchi, C Cafarella, M Gabellini, A Regattieri, M Gamberi

Approfondisci

Balancing data acquisition benefits and ordering costs for predictive supplier selection and order allocation
(2024)

A Regattieri, M Gabellini, F Calabrese, L Civolani, FG Galizia

Approfondisci

A deep learning approach to predict supply chain delivery delay risk based on macroeconomic indicators: A case study in the automotive sector (2024)

M Gabellini, L Civolani, F Calabrese, M Bortolini

Approfondisci

A hybrid approach integrating genetic algorithm and machine learning to solve the order picking batch assignment problem considering learning and fatigue of pickers (2024)

M Gabellini, F Calabrese, A Regattieri, D Loske, M Klumpp

Approfondisci

CONFERENCE PAPER - PUBLISHED
Esamina gli articoli che il gruppo ha scritto e presentato nelle principali conferenze di settore su tematiche come supply chain risk management, digital twins, inventory control, mass customization, data model, order picking e quality control

A Cluster Based Genetic Algorithm for Product Allocation Across Multiple Warehouse (2026)

Gabellini Matteo, Regattieri, Alberto, Bortolini Marco, di Nardo Pasquale, Siena Riccardo

Approfondisci

Economic Feasibility Assessment of Automatic Optical Inspection
(2026)

Ronchi Michele, Regattieri, Alberto, Gamberi Mauro, Gabellini Matteo, Naldi Ludovica Diletta

Approfondisci

Managing Variety in the Era of Mass Customization: A Decisional Algorithm for Product Platform Design (2026)

Naldi L.D., Venturi R., Galizia F. G., Bortolini M., Gabellini M.

Approfondisci

Energy Network Optimization Model for Supporting Generation Expansion Planning
and Grid Design
(2024)

C Cafarella, M Bortolini, M Gabellini, FG Galizia, V Ventura

Approfondisci

Investigating the Potential of Machine Learning and Deep Learning Models in Probabilistic Supply Risk Forecasting: A Case Study in the Automotive Sector (2025)

Gabellini M, Regattieri A, Bortolini M, Galizia F G

Approfondisci

A Data-Driven Approach
to Predict
Supply Chain Risk
Due to Suppliers’ Partial Shipments
(2024)

M Gabellini, F Calabrese, L Civolani, A Regattieri, C Mora

Approfondisci

A Data Model for Predictive Supply Chain Risk Management (2023)

M Gabellini, L Civolani, A Regattieri, F Calabrese

Approfondisci

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JOURNAL PAPER - PUBLISHEDEsamina gli articoli che il gruppo ha scritto sulle principali riviste di settore su tematiche come supply chain risk management, digital twins, inventory control, mass customization, data model, order picking e quality control

COCOA: a model-agnostic framework for forecasting accessories demand from final product sales (2026)

A novel data-driven approach for integrated inventory replenishment, safety stock and lead time optimization (2026)

An information-sharing and cost-aware custom loss machine learning framework for 3PL supply chain forecasting (2025)

Conceptualization and validation of an intelligent digital twin design framework for supply chain risk management (2025)

A continuous training approach for risk informed supplier selection and order allocation (2025)

Data Spaces in Manufacturing and Supply Chains: A Review and Insights from European Initiatives (2025)

Unlocking the Potential of Mass Customization Through Industry 4.0: Mapping Research Streams and Future Directions (2025)

An MILP Model for Optimizing Quality Inspection Allocation with Technology Selection and Variable Sampling Rates (2025)

Balancing data acquisition benefits and ordering costs for predictive supplier selection and order allocation (2024)

A deep learning approach to predict supply chain delivery delay risk based on macroeconomic indicators: A case study in the automotive sector (2024)

A hybrid approach integrating genetic algorithm and machine learning to solve the order picking batch assignment problem considering learning and fatigue of pickers (2024)

CONFERENCE PAPER - PUBLISHEDEsamina gli articoli che il gruppo ha scritto e presentato nelle principali conferenze di settore su tematiche come supply chain risk management, digital twins, inventory control, mass customization, data model, order picking e quality control

A Cluster Based Genetic Algorithm for Product Allocation Across Multiple Warehouse (2026)

Economic Feasibility Assessment of Automatic Optical Inspection (2026)

Managing Variety in the Era of Mass Customization: A Decisional Algorithm for Product Platform Design (2026)

Energy Network Optimization Model for Supporting Generation Expansion Planning and Grid Design (2024)

Investigating the Potential of Machine Learning and Deep Learning Models in Probabilistic Supply Risk Forecasting: A Case Study in the Automotive Sector (2025)

A Data-Driven Approach to Predict Supply Chain Risk Due to Suppliers’ Partial Shipments (2024)

A Data Model for Predictive Supply Chain Risk Management (2023)

JOURNAL PAPER - PUBLISHED
Esamina gli articoli che il gruppo ha scritto sulle principali riviste di settore su tematiche come supply chain risk management, digital twins, inventory control, mass customization, data model, order picking e quality control

COCOA: a model-agnostic framework for forecasting accessories demand
from final product sales
(2026)

A novel data-driven approach for integrated inventory replenishment, safety stock and lead time optimization
(2026)

An information-sharing and cost-aware custom loss machine learning framework for 3PL supply chain forecasting
(2025)

Conceptualization and validation of an intelligent digital twin design framework for supply chain risk management
(2025)

A continuous training approach for
risk informed supplier selection and
order allocation
(2025)

Balancing data acquisition benefits and ordering costs for predictive supplier selection and order allocation
(2024)

CONFERENCE PAPER - PUBLISHED
Esamina gli articoli che il gruppo ha scritto e presentato nelle principali conferenze di settore su tematiche come supply chain risk management, digital twins, inventory control, mass customization, data model, order picking e quality control

Economic Feasibility Assessment of Automatic Optical Inspection
(2026)

Energy Network Optimization Model for Supporting Generation Expansion Planning
and Grid Design
(2024)

A Data-Driven Approach
to Predict
Supply Chain Risk
Due to Suppliers’ Partial Shipments
(2024)