From the 1 of 6 linked papers with an AI index.
6 papers
Viable Supply Chain Network Design: Machine Learning-Derived Chance-Constrained Programming
Mohammad Rohaninejad, Behdin Vahedi-Nouri, Elham Jelodari Mamaghani +2
The paper proposes mixed‑integer models for designing a two‑echelon supply chain that remains viable despite facility disruptions, using machine‑learning‑based chance‑constraints a…
A batch production scheduling problem in a reconfigurable hybrid manufacturing-remanufacturing system
Behdin Vahedi-Nouri, Mohammad Rohaninejad, ZdenÄk Hanzálek +1
In recent years, remanufacturing of End-of-Life (EOL) products has been adopted by manufacturing sectors as a competent practice to enhance their sustainability and market share. D…
Optimizing Perishable and Non-Perishable Product Assignment to Packaging Lines in a Sustainable Manufacturing System: An AUGMECON2VIKOR Algorithm
Reza Shahabi-Shahmiri, Reza Tavakkoli-Moghaddam, Zdenek Hanzalek +3
Identifying appropriate manufacturing systems for products can be considered a pivotal manufacturing task contributing to the optimization of operational and planning activities. I…
Optimal Trading of a Charging-Station Company in Auction Markets for Electricity
Farnaz Sohrabi, Mohammad Rohaninejad, Mohammad Reza Hesamzadeh +1
This paper addresses a charging-station company (Chargco) for electric and hydrogen vehicles. The optimal trading of the Chargco in day-ahead and intraday auction markets for elect…
A matheuristic approach for an integrated lot-sizing and scheduling problem with a period-based learning effect
Mohammad Rohaninejad, Behdin Vahedi-Nouri, Reza Tavakkoli-Moghaddam +1
This research investigates a multi-product capacitated lot-sizing and scheduling problem incorporating a novel learning effect, namely the period-based learning effect. This is ins…
Electrification of Transportation: A Hybrid Benders/SDDP Algorithm for Optimal Charging Station Trading
Farnaz Sohrabi, Mohammad Rohaninejad, Július Bemš +1
This paper examines the electrification of transportation as a response to environmental challenges caused by fossil fuels, exploring the potential of battery electric vehicles and…